Graded Assignment -3 (May Term 2024):- Effective Visualization of Data

[Jimmi-Kr]

After World War II, antibiotics were considered "wonder drugs", since they were easy cures for what had been intractable ailments. To learn which drug worked most effectively for which bacterial infection, the performance of the three most popular antibiotics on 16 bacteria was gathered. The values in the table represent the minimum inhibitory concentration (MIC), a measure of the effectiveness of the antibiotic, which represents the concentration of antibiotic required to prevent growth in vitro. The reaction of the bacteria to Gram staining is described by the covariate “gram staining”. Bacteria that are stained dark blue or violet are Gram-positive. Otherwise, they are Gram-negative.

Your task is to design a chart that you believe effectively communicates the data and provide a short write-up (no more than 4 paragraphs) describing your design.

• Your chart image should be interpretable without recourse to your short write-up.
• Do not forget to include a title, axis labels, or legends as needed!

As different visualizations can emphasize different aspects of a data set, you should document what aspects of the data you are attempting to most effectively communicate. Just as important, also note which aspects of the data might be obscured or downplayed due to your visualization design.

In your write-up, you should provide a rigorous rationale for your design decisions. Document the visual encodings you used and why they are appropriate for the data. These decisions include the choice of visualization type, size, color, scale, and other visual elements, as well as the use of sorting or other data transformations. How do these decisions facilitate effective communication?

Here is the link for the dataset: Butin_antibiotic_data.xlsx

[SURAJARS]

Name - SURAJ ARS Roll No - 21f1005229

About my selection of Clustered Bar Chart:

My chart is a clustered chart for every bacterium, showing the Minimum Inhibitory Concentration (MIC) for Penicillin, Streptomycin, and Neomycin. To recognize Gram-positive and Gram-negative microbes, Used various colors for the bars addressing each kind of microscopic organisms. The reason to use Clustered bar graph takes into consideration direct examination of the MIC upsides of various anti-infection agents for every bacterium. This correlation is significant to understanding which anti-microbial is most effective.It gives a reasonable visual portrayal of the MIC values next to each other, making it simple for comparison. Various colors used for Gram-positive and Gram-negative microorganisms help rapidly separate between the two groups.This variety coding use pre-mindful handling, permitting watchers to distinguish examples and groupings without broad mental exertion rapidly.Arranging microbes by Gram staining accentuates the distinctions in anti-infection viability between Gram-positive and Gram-negative bacteria. Benefit of utilizing this chart is the adequacy of every anti-toxin against different bacteria and the qualification between Gram-positive and Gram-negative microbes are plainly communicated and disadvantage is Individual MIC values might be less stressed for the general example and examination. This design additionally catches no possible cooperations between anti-infection agents.

[21f1006304ds]

Name : Rajesh Saha

Roll No. 21F1006304

Use Case and Assumption:

This visualization is for physician who need to prescribe the most 'effective' antibiotic to her patients. The assumption is that the bacteria that has infected the patient is already been identified. The identified bacteria is one of the bacteria shown in this chart. Only three antibiotics are available to the doctor, namely Penicillin, Streptomycin and Neomycin. In general, all the antibiotics are available, but in special situation, all the three antibiotics may not be available.

Requirement:

The requirement is that, when the name of the bacteria is known, the doctor should be able to find the most effective antibiotic to kill that bacteria quickly and easily. The doctor should be able to take decision about the dosage of the antibiotic quickly. When not all the three antibiotics are available, doctor should be able to take an informed decision about prescribing the antibiotic from the available options.

Design Thinking and Analysis:

As in the given table showing the bacteria and the antibiotics has already been provided, in general, the physician can go through the table and identify the correct antibiotic. Also, as the Minimum Inhibitory Concentration (MIC) has been provided, the dosage can also be obtained from that. However, that would not be easy and quick. As we have discussed earlier about 'effective' antibiotic, we have to define 'effective'. In this case, the antibiotic that can kill bacteria with minimum concentration is more effective. In other words, less MIC is better. As we have also mentioned about 'easily' and 'quickly', we will create a table where the names of bacteria would be in alphabetical order and it will give a visual indication about the effectiveness. Also, doctor should have access to the 'raw' data so that during a critical situation she can refer to the unfiltered data and take an informed decision. After observing the MIC values in the table, it's found that the MIC values vary over a wide range for a particular bacteria as well as for a particular antibiotic. So, it was required to normalize the values for display purpose. Here, I have done the min-max normalization with a scale of 1 to 5. This is an arbitrary choice and only to assist an effective visualization. The formula has been used as *new_value = whole_number(5 - ((old_value-Min_value)/(Max_value-Min_Value))4)**. Next, the Gram Staining has been coded as 'P' and 'N' respectively for 'Positive' and 'Negative'. A clustered bar chart has then created then. As we need to show multiple antibiotics for multiple bacteria, either a horizontal or vertical clustered chart was chosen. Care has been taken so that bacteria names appear in alphabetic order. Then the color of the bar has been customized. Few other aesthetic work has been done to avoid clutter. The axis names and legend has been provided. Then a snapshot of the raw data has been taken and merged with the above chart visualization.

Usage:

The physician should go through the antibiotic names in alphabetic order, find the largest bar which is the most effective antibiotic and prescribe that. In case of conflict, she may choose either one, or refer to the raw data table. If the selected antibiotic would be unavailable, the largest bar from the rest can be chosen. For dosage calculation or in critical situation, she can refer to the MIC table to determine the dosage or select alternative antibiotic.

[neeraj-iit]

Name: Neeraj Yadav Roll No: 21f1005729

Visualization Type and Encodings: I chose a grouped bar chart to visualize the effectiveness of three antibiotics (Penicillin, Streptomycin, Neomycin) on various bacteria. This type of chart allows for straightforward comparison within each bacterium group and between different bacteria. Colors: Different colors represent each antibiotic—blue for Penicillin, green for Streptomycin, and red for Neomycin. Patterns: Different hatch patterns distinguish between Gram-positive and Gram-negative bacteria. Axes: The x-axis lists the bacteria names, grouped by Gram staining type (negative and positive), and the y-axis shows the MIC values on a logarithmic scale to accommodate the wide range of values.

Rationale for Design Decisions: Grouped Bar Chart: This choice facilitates direct comparison of the MIC values for each antibiotic within each bacterium group. By grouping bars by bacteria and using different colors for antibiotics, it is easy to spot which antibiotic is most effective for each bacterium. Logarithmic Scale: The MIC values span several orders of magnitude. Using a logarithmic scale ensures that all values are proportionally represented and comparisons are more meaningful. Color and Patterns: Distinct colors for antibiotics and patterns for Gram staining allow for quick identification and differentiation of the key variables. This encoding ensures the chart is visually intuitive.

Highlights and Downplayed Aspects: Highlighted Aspects: Comparison of Antibiotic Effectiveness: The chart clearly shows which antibiotic has the lowest MIC for each bacterium, providing insights into their relative effectiveness. Gram Staining Correlation: By differentiating Gram-positive and Gram-negative bacteria with patterns, the potential correlation between Gram staining and antibiotic effectiveness is visually emphasized.

Downplayed Aspects: Exact MIC Values: The logarithmic scale and the grouping of bars may make it challenging to read exact MIC values from the chart, focusing instead on relative comparisons. Statistical Analysis: The visualization emphasizes visual comparison rather than detailed statistical analysis, which might require further examination beyond the chart.

[Kaustav-Goswami9]

Name: Kaustav Goswami Roll: 21f001588

To visualize this data effectively, I have used a grouped bar chart, which allows for easy comparison of the MIC values across the three antibiotics for each bacterium. Additionally, I have used text color coding to differentiate between Gram-positive and Gram-negative bacteria.

Aspects to Communicate:

1. Effectiveness Comparison: How effective each antibiotic is against different bacteria.
2. Gram Staining: The difference in effectiveness between Gram-positive and Gram-negative bacteria.

Visual Encodings:

1. Bars: Represent the MIC values for each antibiotic.
2. Text Colors: Represent the Gram staining result.

Chart Description:

The chart effectively visualizes the Minimum Inhibitory Concentration (MIC) values for three antibiotics (Penicilin, Streptomycin, Neomycin) across 16 different bacteria. The x-axis lists the bacteria, while the y-axis represents the MIC values on a logarithmic scale, allowing for a clear comparison despite the wide range of values.

Design Decisions and Rationale:

1. Grouped Bar Chart: This format allows direct comparison of the effectiveness of the three antibiotics against each bacterium. By grouping the bars for each bacterium, it’s easy to see which antibiotic is most effective.

2. Logarithmic Scale: The MIC values vary greatly, so a logarithmic scale on the y-axis ensures that smaller values are distinguishable while larger values don’t dominate the chart. This scaling is crucial for visualizing data that spans several orders of magnitude.

3. Value Transformation: In the original Dataset, the lower MIC value is better for an antibiotic, I have inversed the values to highlight the better ones. In other words, I have taken the reciprocal values and plotted them. This transforms the "lower is better" to "higher is better" and the end user does not have to look for the lowest value in the most cluttered area. Thus improving readability.

4. Color Coding by Gram Staining: While naming the bacteria I have used Green Text for Gram-positive and Red Text for Gram-negative bacteria. This color coding provides a visual cue about the bacteria type, which can be correlated with antibiotic effectiveness. This has also been mentioned in the legend section to provide a better context.

Facilitating Effective Communication:

• Comparison Across Antibiotics: By displaying all three antibiotics side by side for each bacterium, viewers can quickly identify which antibiotic requires the lowest concentration to inhibit growth, indicating higher effectiveness.
• Gram Staining Impact: The color coding allows viewers to assess patterns related to Gram staining, potentially revealing if one type of bacteria (Gram-positive or Gram-negative) is more susceptible to certain antibiotics.

Potential Downplays:

• Specific Numerical Values: The use of a logarithmic scale, while necessary for visualization, may obscure precise MIC values for some viewers. This trade-off is made to facilitate broader comparisons.
• Individual Antibiotic Trends: Trends or patterns within a single antibiotic’s effectiveness across all bacteria might not be as immediately apparent compared to focusing on the grouped comparison.

This visualization highlights the comparative effectiveness of different antibiotics while providing insights into the influence of bacterial type (Gram-positive vs. Gram-negative) on antibiotic efficacy.

[prashantjnvu]

Name: PRASHANT SHARMA Roll No: 21F1004586 Email: 21f1004586@ds.study.iitm.ac.in

Visualization Type and Encodings:

Observing data gives impression that effectiveness of the three antibiotics (Penicillin, Streptomycin, Neomycin) on various bacteria varies based on the 'Gram Straining'. To emphasize this view (performance of drugs with respect to broad class of bacteria - 'Gram Straining') following choices had been made -

Sorting: First data is sorted based on Gram Straining and then alphabatically on bacteria name. Colors: Bacteria reacting +ve on gram straining are colored blue and those reacting negative are colored red. Patterns: Different point patterns are used for different antibiotic types - dot (Pencilin), +(Streptomycin), triangle(Neomycin). Axes: The x-axis lists the bacteria names, first positive gram straining bacteria are listed alphabatically and then negative gram straining, and the y-axis shows the corresponding MIC values.

Rationale for Design Decisions: Scatter plot: This choice enables the direct comparison of the MIC values for each antibiotic within each bacterium group and across the gram straining type as well. Finer major and minor scales: Y axis scale is finer of 25 MIC units Grid Lines; Major and minor gridlines are displayed as white lines over gray background Color: Different color for different Gram straining type Shape: Different shapes for different three antibiotics (Penicillin, Streptomycin, Neomycin)

Highlighted Aspects: Comparison of Antibiotic Effectiveness: This graphic visualization emphasizes and highlights the following aspect inherent in the data - (a) All the three Antibiotics are behaving comparatively well for +ve strained bacteria. (b) Pencilling effectiveness is worst for negative strained bacterias (c) Thew new drugs (Streptomycin, Neomycin) are effective almost uniformally over all bacteria (except Nemocyin on Streptococcus viridans) (4) This visualization clearly display effectiveness vs Gram strain vs drug name. So which drug out of these three need to be administered decision can be taken based on this visualization provided bacteria infection is known.

Downplayed Aspects: (a) Exact MIC quantity comparision (b) Due to large variation in Pencilin effectiveness, the small MIC quantity comparision (even qualitative) gets very difficult as the smaller MIC quantity for a bacteria getting cluttered and appears as at almost at one point but on high resolution the fieerence appears to be sibtle though at lower MIC values.

[muskansindhu]

Name: Muskan Sindhu Roll No: 21f1003710 Email: 21f1003710@ds.study.iitm.ac.in

Objective and Visualization Choice

The chart visualizes the effectiveness of three antibiotics—Penicillin, Streptomycin, and Neomycin—across 16 types of bacteria, categorized by their Gram staining (positive or negative). A grouped bar chart with a logarithmic scale on the y-axis was chosen to facilitate easy comparison of Minimum Inhibitory Concentration (MIC) values, which represent the effectiveness of each antibiotic against bacterial growth.

Visual Encodings and Rationale

Each antibiotic is color-coded for clarity: sky blue for Penicillin, light green for Streptomycin, and light coral for Neomycin. To distinguish between Gram-positive and Gram-negative bacteria, markers ('o' for Gram-positive and 'x' for Gram-negative) are placed above each corresponding bar. This dual encoding of color and marker ensures that viewers can quickly identify both the antibiotic and the Gram classification of each bacterial type.

Facilitating Effective Communication

The use of a logarithmic scale on the y-axis accommodates a wide range of MIC values, aiding in the clear visualization of antibiotic effectiveness across different bacteria. Sorting the bacteria first by Gram staining and then alphabetically enhances the readability, allowing viewers to discern any trends related to Gram classification. Legends positioned side by side in the upper right corner provide clear identification of both antibiotics and Gram staining, ensuring that the chart is informative yet accessible.

Limitations and Considerations

While the chart effectively compares antibiotic effectiveness across bacterial types and Gram classifications, it may obscure finer details in MIC values for bacteria with similar effectiveness levels due to the scale. Additionally, this visualization focuses on relative comparisons rather than absolute effectiveness, which could be further enhanced with additional annotations or statistical indicators.

Overall, this chart design aims to provide a comprehensive overview of antibiotic efficacy against different bacteria, emphasizing both visual clarity and interpretability.

[Ruhil-DS]

Ineffectiveness Of Different Vaccines Against Different Bacteria

This dashboard explains the ineffectiveness of different vaccines against different bacteria varying against the gram strain. This visualization shows that certain vaccines need more concentration to work effectively. The bigger the square/rectangle, the more the concentration of vaccine required to prevent the growth in vitro.

• The dashboard of 3 Mosaic Plots shows that certain viz are used in higher concentration to work.

• A similar colour coding is used. Blue for positive gram straining and lime green for the negative.

• The size of the rectangles varies with the MIC, higher means more area. Hence, less effective

• Penicillin is needed in more concentration for most of the negative gram strain bacteria. For positive gram strain bacteria, penicillin turns out to be very effective

• Neomycin is ineffective towards positive gram strain bacteria while it tends to work effectively for negative gram strain bacteria.

• Streptomycin is somewhere in the middle

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• Mosaic Plots are effective in terms of the following points:

  • Revealing relationships

  • Part-to-whole comparisons

  • Effective space utilization

• Color coding is used according to the gram-straining process. Usually, Positive GS are the ones which get a blue or violet strain. Anything else is gram-negative. Hence, the color coding.

What else could be done is to take the size proportional to the negative MIC. To showcase the effectiveness.

Software used: Tableau Desktop

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Pushpak Ruhil 21f2001180 21f2001180@ds.study.iitm.ac.in

[irshad747]

Name : Sareshwala Irshad Abrar Roll # : DS21f1004835

Visualization 1: Bar Chart of MIC Values for Each Antibiotic on Different Bacteria Description The first visualization is a bar chart that compares the minimum inhibitory concentration (MIC) values of three antibiotics (Penicillin, Streptomycin, Neomycin) across 16 different bacteria. The MIC values are plotted on a logarithmic scale to accommodate the wide range of concentrations and to ensure that smaller values are visible. The bacteria are grouped by their Gram staining type, with Gram-positive bacteria labeled in blue and Gram-negative bacteria labeled in red.

Rationale Bar Chart: This visualization type is ideal for comparing discrete categories (antibiotics) across multiple groups (bacteria). It provides a clear and immediate comparison of MIC values. Logarithmic Scale: Given the wide range of MIC values, a logarithmic scale is used for the y-axis. This ensures that all values, regardless of magnitude, are visible and comparable. Color Coding: Gram staining types are color-coded (blue for positive, red for negative), which allows for quick visual differentiation between Gram-positive and Gram-negative bacteria. Annotations: Each bar is annotated with the Gram staining type above it, reinforcing the visual grouping and aiding in quick identification.

Communication Highlighted Aspects: The bar chart effectively highlights the relative effectiveness of each antibiotic against different bacteria, allowing viewers to quickly identify which antibiotic is most effective for each bacterium. The use of color coding for Gram staining also allows for a visual comparison between Gram-positive and Gram-negative bacteria. Downplayed Aspects: While the chart provides a clear comparison of MIC values, it may not fully capture the distribution and variability of MIC values across all bacteria. Additionally, the detailed numerical differences between antibiotics for the same bacterium might be harder to discern due to the bar heights.

Visualization 2: Box Plot of MIC Values for Each Antibiotic Description The second visualization is a box plot that shows the distribution of MIC values for each of the three antibiotics. This plot uses a logarithmic scale for the y-axis to handle the wide range of MIC values. The box plot highlights the median, quartiles, and potential outliers for each antibiotic's MIC values.

Rationale Box Plot: This visualization type is effective for displaying the distribution of data and identifying central tendencies and variability. It provides a clear summary of the range and spread of MIC values for each antibiotic. Logarithmic Scale: As with the bar chart, a logarithmic scale is used to ensure that all MIC values are visible and comparable. Palette: The "coolwarm" palette is used to enhance visual differentiation between the antibiotics. Communication Highlighted Aspects: The box plot emphasizes the distribution and spread of MIC values, showing the variability and range of antibiotic effectiveness. It highlights the median MIC values, which are critical for understanding the typical effectiveness of each antibiotic. The plot also identifies potential outliers, providing insight into extreme cases. Downplayed Aspects: This plot may obscure individual MIC values for specific bacteria, as the focus is on overall distribution rather than specific comparisons. It also doesn't directly indicate which bacteria are Gram-positive or Gram-negative, which may be less informative for viewers interested in these specific details.

[trxpti]

Introduction In presenting the effectiveness of antibiotics across various bacteria categorized by Gram staining, I have opted for a grouped bar chart as the primary visualization tool. This choice is deliberate, aiming to facilitate clear comparisons of Minimum Inhibitory Concentration (MIC) values for Penicillin, Streptomycin, and Neomycin within each bacterial group. By organizing the data in this manner, the chart allows viewers to quickly discern how these antibiotics perform against Gram-positive and Gram-negative bacteria, thereby providing insights into their comparative efficacy across different microbial classifications.

Color Coding, Annotation and Chart elements The color scheme employed uses muted tones, ensuring each antibiotic is visually distinguishable without overwhelming the viewer. Background shading subtly delineates Gram-positive and Gram-negative groups behind the bars, providing contextual information while keeping the focus on antibiotic effectiveness. Annotations positioned above each bar precisely indicate MIC values, enhancing data interpretation without cluttering the chart. Clear axis labels—Bacteria on the x-axis and MIC (µg/mL) on the y-axis—further aid in understanding the chart’s content and its relevance to microbiological studies.

Rationale The rationale behind sorting the data first by Gram staining and then by bacteria name is to enhance readability and facilitate direct comparisons within and between bacterial groups. This structured approach ensures that viewers can easily discern patterns in antibiotic efficacy based on bacterial classification. Additionally, the use of a logarithmic scale on the y-axis accommodates the wide range of MIC values typically encountered in microbiological research, ensuring that variations in both low and high MIC values are visually distinguishable and meaningful.

Consideration Considerations for chart design include potential challenges such as overlapping annotations or bars, which have been mitigated through careful placement and color choices. These decisions prioritize clarity and ensure that each dataset remains distinct and interpretable, supporting informed analysis of antibiotic efficacy across diverse bacterial strains. Overall, the grouped bar chart effectively communicates the comparative effectiveness of antibiotics, leveraging visual elements to highlight differences in MIC values across different bacterial classifications by Gram staining.

Regards, Tripti Arya 21f1005935

[swethaMThomas]

Name: Swetha Mary Thomas Roll No: 21f1002403 Email: 21f1002403@ds.study.iitm.ac.in

Description

I have created a grouped bar chart to visualize and compare the effectiveness of three different antibiotics: Penicillin, Streptomycin, and Neomycin, across 16 bacterial species. The x-axis lists the various bacteria species, with gram-positive bacteria on the left (highlighted with a green background) and gram-negative bacteria on the right (highlighted with a red background). The y-axis represents the Minimum Inhibitory Concentration (MIC) values on a logarithmic scale, illustrating the effectiveness range of the antibiotics. Three colors are used to distinguish the antibiotics: blue for Penicillin, orange for Streptomycin, and green for Neomycin. A legend in the top right corner provides a reference for the color coding.

Rationale

Grouped Bar Chart: Grouping the bars for each bacterium allows for direct comparison of MIC values for Penicillin, Streptomycin, and Neomycin side-by-side. This layout makes it easy to see which antibiotic is most effective against each type of bacteria.

Logarithmic Scale: To handle the wide range of MIC values in a manageable and visually comprehensible way. It compresses the range of values so that smaller MIC values and larger MIC values can be displayed together without distortion.

Color Coding: Using distinct colors for Penicillin (blue), Streptomycin (orange), and Neomycin (green) ensures that each antibiotic's effectiveness is easily distinguishable. This allows for quick interpretation of the data.

Background Shading: To categorize and separate gram-positive and gram-negative bacteria visually. The green background for gram-positive bacteria and the red background for gram-negative bacteria help in quickly identifying the bacterial classification.

Aspects of Data Effectively Communicated:

Comparative Effectiveness of Antibiotics: The grouped bar chart effectively shows the relative effectiveness of Penicillin, Streptomycin, and Neomycin against each bacterial species. By placing the bars side-by-side for each bacterium, it is easy to see which antibiotic has the lowest MIC value and thus the highest effectiveness.

Distinction Between Gram-positive and Gram-negative Bacteria: The background shading (green for gram-positive and red for gram-negative) clearly distinguishes between these two major groups of bacteria. This helps in understanding if there are any patterns in antibiotic effectiveness specific to either group.

Logarithmic Scale for MIC Values: Using a logarithmic scale allows the visualization of a wide range of MIC values in a compact and readable format. It effectively highlights differences in antibiotic potency, even when these differences span several orders of magnitude.

Aspects of Data That Might Be Obscured or Downplayed:

Absolute Differences in MIC Values: While the logarithmic scale is effective for visualizing a wide range of values, it can obscure the absolute differences between MIC values. For example, a small visual difference on a logarithmic scale can represent a large numerical difference in MIC values.

Outlier Influence: If there are extreme outliers in MIC values, their influence might be minimized on a logarithmic scale. This could obscure important insights about the potency of certain antibiotics against specific bacteria.

Individual Bacterial Characteristics: The chart does not provide information on why certain antibiotics are more effective against specific bacteria. It only shows the end result (MIC values) without context regarding the mechanisms of resistance or susceptibility.

[ShyamSundhar1411]

Assignment-3

Name: Shyam Sundhar Ganesh Reg Number: 21F3001249

Grouped Bar Chart

Objective

This chart depicts the minimum inhibitory concentration (MIC) of three antibiotics (Pencillin, Streptomycin, Neomycin) with 16 bacteria. The y-axis is scaled from 10^-3 to 10^3 to accept range of values in MIC. The x-axis contains the 16 bacteria, and they are grouped by the Gram Staining with positive values marked by green and negative values marked by red.

Visual Encodings and Rationale

• The grouped bar chart is effective in this scenario because it helps to elucidate the information of the data in an efficient way. On grouping, it makes it easier to compare the performance of antibiotics across the bacteria. Additionally, legends have been provided in the top right of the chart to convey the color-coding information as well.

• Each antibiotic's MIC is represented by unique color - Penicillin (Blue), Streptomycin (Red), Neomycin (Green). Along with the Color each chart is annotated with the respective MIC values in the bars. Every bacterium category is grouped based on their MIC values. Furthermore, the respective groups are annotated with Gram Staining classes as well.

Effectively Communicated Aspects

• As analyzed from the chart, it's easy to perceive that Penicillin works effectively for almost all bacteria. The respective gram staining results has been annotated as well. Additionally, the precise MIC value for each antibiotic has been annotated inside the respective bars.
• The analysis also communicates the trends of different antibiotics with respect to the different bacterium which further facilitates the derivation of relationship between gram scaling, MIC values and the antibiotics.

[abirChakrabortyIITM]

Assignment 3: Effective Visualization of Data

Name: Abir Subroto Chakraborty Roll No: 21f2000280 Email: 21f2000280@ds.study.iitm.ac.in

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Your visualization, titled "The Wonder Drugs of World War II," presents the minimum inhibitory concentration (MIC) values for Penicillin, Streptomycin, and Neomycin against 16 different bacteria. The chart effectively uses a bar graph format to convey comparative effectiveness, with different colors representing each antibiotic and the bacteria categorized by Gram staining (positive or negative).

Design Rationale:

• Visualization Type: The bar graph is chosen for its effectiveness in showing comparative data across multiple categories, which is crucial in comparing the effectiveness of three antibiotics.
• Color and Scale: Distinct colors are used for each antibiotic to make comparison straightforward, and a logarithmic scale is employed to handle the large range of MIC values.
• Sorting and Grouping: Bacteria are sorted by their Gram staining property, providing a logical grouping that aids in comparative analysis between Gram-positive and Gram-negative bacteria.

Effectiveness of the Visualization:

1. Clear Comparison:

   • The use of a bar graph with different colors for each antibiotic (blue for Streptomycin, orange for Penicillin, and red for Neomycin) allows for easy comparison of the effectiveness of the three drugs across various bacteria.
   • The logarithmic scale on the y-axis helps in managing the wide range of MIC values, making it easier to compare values that span several orders of magnitude.

2. Categorization by Gram Staining:

   • The grouping of bacteria based on their Gram staining results (negative on the left, positive on the right) provides a clear distinction, aiding in the understanding of how each antibiotic performs against different types of bacteria.

3. Comprehensive Data Representation:

   • Including all 16 bacteria ensures that the viewer has a complete picture of the antibiotics' effectiveness across a broad spectrum of bacterial infections.

Areas for Improvement:

1. Overlapping Data Points:

   • Some bars, particularly those with low MIC values, are very small and can be difficult to distinguish. For example, the bars for Brucella anthracis are so short that differentiating between the values for Penicillin, Streptomycin, and Neomycin could be challenging without the numerical labels.

2. Color Differentiation:

   • The colors chosen for the antibiotics are distinguishable but could be made more visually distinct to cater to viewers with color vision deficiencies. Using patterns or varying shades can improve accessibility.

3. Labeling and Scale:

   • While the logarithmic scale is appropriate, the y-axis could benefit from more intermediate labels to assist in the interpretation of MIC values. Currently, the jump from 0.01 to 0.1, for example, may not be immediately intuitive for all viewers.

4. Additional Context:

   • Including a brief legend or additional context within the chart itself could help viewers who are not familiar with MIC values or Gram staining to understand the significance of the data better.

In conclusion, while the visualization is effective in presenting a comprehensive comparison of antibiotic effectiveness, enhancing color differentiation, addressing potential overlap in data points, refining the scale, and providing additional context can significantly improve clarity and accessibility.

[harsh18n]

Assignment 3

Name: Harshini Natraj Roll: 21f1005191

Visualization Type

For this visualization, I chose a grouped bar chart to represent the Minimum Inhibitory Concentration (MIC) of three antibiotics (Penicillin, Streptomycin, and Neomycin) across different bacteria. The choice of a grouped bar chart effectively facilitates the comparison of MIC values between the antibiotics for each bacterium. Each bacterium's MIC values for the three antibiotics are grouped together, allowing for direct visual comparison.

Logarithmic Scale

MIC values span several orders of magnitude, from as low as 0.001 to as high as 870. To handle this wide range and to enhance interpretability, I used a logarithmic scale for the y-axis. This transformation compresses the range and makes it easier to discern differences in MIC values, especially for lower concentrations, which are critical for understanding antibiotic effectiveness.

Color Encoding

Color is used to differentiate between the three antibiotics:

• Penicillin: Blue
• Streptomycin: Green
• Neomycin: Red

This clear and consistent color scheme helps viewers quickly distinguish between the antibiotics across the chart. Additionally, the background color indicates the Gram-staining property of each bacterium:

• Negative (Gram-negative): Light yellow
• Positive (Gram-positive): Light purple

This secondary use of color provides context about the bacterial characteristics without overcrowding the primary data representation.

Limitations

• Subconscious Bias

One potential limitation of using a bar chart is the subconscious bias it may introduce. Longer bars can create an illusion that the corresponding bacteria are more significant or better in some way. In this context, longer bars represent higher MIC values, indicating lower antibiotic effectiveness. However, viewers might subconsciously associate longer bars with better outcomes, which is contrary to the intended message. To mitigate this, it is important to clearly label the y-axis and provide context in the chart title and legend, emphasizing that lower MIC values correspond to higher effectiveness.

• Labels

Specific MIC values are not labeled on the bars, requiring viewers to estimate based on the y-axis. This can be a limitation for those needing precise values. The chart focuses on overall trends rather than individual data points, which might obscure specific details. This is a trade-off to maintain readability and prevent overcrowding.

[RajRohitYadav19]

Assignment-3

Name: Raj Rohit Yadav Roll. No.: 21f1005377 Email ID: 21f1005377@ds.study.iitm.ac.in

Chart Design and Rationale

The clustered column chart was chosen to effectively communicate the comparative effectiveness of the three antibiotics (Penicillin, Streptomycin, and Neomycin) across different bacteria. This visualization type allows for easy comparison of multiple categories (antibiotics) for each bacterial strain, facilitating a clear visual distinction of performance, less MIC value means more effectiveness.

Visual Encodings and Design Decisions

Visualization Type: A clustered column chart is appropriate because it allows for direct comparison of values across multiple categories (antibiotics) for each bacterial strain. This format is suitable for showcasing the relative effectiveness of each antibiotic.

Color Encoding: The bacteria names on the x-axis are color-coded based on their Gram Staining results: red for Gram-positive and blue for Gram-negative. This color encoding provides an additional layer of information, making it easy to distinguish between Gram-positive and Gram-negative bacteria at a glance.

Y-axis Scale: The y-axis uses a logarithmic scale to accommodate the wide range of Minimum Inhibitory Concentration (MIC) values. This scaling method ensures that smaller values are visible and comparable, which would not be possible with a linear scale due to the high variation in MIC values.

Labels and Legends: Each bar is labeled with its corresponding MIC value, enhancing the interpretability of the chart. Additionally, legends are added for the antibiotics and Gram Staining categories to clearly explain the color coding and data representation.

Sorting and Data Transformations: The bacteria are sorted alphabetically to maintain a consistent and intuitive order. No additional data transformations were applied, ensuring the raw MIC values are presented accurately.

Effective Communication and Potential Limitations

Effectively Communicated Aspects: The comparative effectiveness of the three antibiotics across different bacteria is clearly communicated. The logarithmic scale ensures that all MIC values are visible, preventing smaller values from being obscured. The color coding of bacteria names provides an immediate visual cue about Gram Staining results, which can be useful for microbiologists or healthcare professionals.

Potential Limitations: The clustered column chart may downplay the exact numerical differences between MIC values due to the logarithmic scale. While this scale is necessary for visibility, it may make it harder to perceive small differences between values. Additionally, the color coding relies on viewers being able to distinguish red and blue, which may not be accessible to individuals with color vision deficiencies.

Conclusion

Overall, the clustered column chart with a logarithmic y-axis scale, color-coded x-axis labels, and labeled bars provides a clear and informative visualization of the antibiotic effectiveness data. The design choices facilitate effective communication of the key aspects of the dataset, while potential limitations are acknowledged and justified based on the need for a comprehensive and accessible representation.

[pranam-pagi]

Name: Pranam Premanand Pagi Roll No: 21f3002964

Choice of Visualization Type:

A grouped bar chart is selected because it facilitates a direct comparison of the MIC values for the three antibiotics across different bacteria. This format allows for a clear visual distinction between the effectiveness of each antibiotic on each bacterium.

Logarithmic Scale:

The y-axis is on a logarithmic scale due to the wide range of MIC values, spanning several orders of magnitude. This transformation helps in presenting all data points more compactly and comparably, avoiding the distortion that a linear scale would introduce.

Background Color Coding:

The background color of the bars is based on Gram staining (light blue for positive and light coral for negative), which makes the Gram characteristic distinction clearer. This visual differentiation helps to immediately identify clusters of bacteria based on Gram staining.

Uniform Grid:

A uniform grid with both major and minor ticks ensures that the grid forms squares, making it easier to compare values across different bars and helping with precise reading of the MIC values.

Clarity and Readability:

Axis labels, a title, and a legend are included to ensure that the chart is self-explanatory. The bacteria names are rotated for better readability given the space constraints on the x-axis.

Aspects Emphasized

Effectiveness Comparison: The primary aspect emphasized by this visualization is the comparison of the effectiveness of the three antibiotics against each bacterium. The grouped bar format allows viewers to see which antibiotic has the lowest MIC (indicating the highest effectiveness) for each bacterium.

Gram Staining Patterns: The color-coded backgrounds highlight potential patterns related to Gram staining, helping to visually cluster bacteria by their staining characteristics and revealing any trends in antibiotic effectiveness related to whether bacteria are Gram-positive or Gram-negative.

Aspects Downplayed or Obscured

Exact Numerical Values: While the chart effectively shows relative comparisons, the exact numerical values of MICs are not directly visible. Viewers can interpret the general effectiveness, but for precise values, they would need to refer to the data table.

Individual Bacterial Characteristics: The focus on comparing antibiotics might obscure specific characteristics or behavior of individual bacteria. For instance, differences in MIC values within a single antibiotic for various bacteria are less emphasized compared to the overall comparison among antibiotics.

Subtle Differences at Lower MICs: Despite the logarithmic scale improving visibility for lower MIC values, some subtle differences at the very low end might still be less pronounced compared to differences in higher MIC values.

[Indu16910]

Name: Indumathi Kalla Roll no: ce22b062

Rationale for Design Decisions Choice of Visualization Type

Grouped Bar Chart: This type of chart is selected to facilitate comparison between the effectiveness of Neomycin, Penicillin, and Streptomycin across various bacterial strains. Grouped bars allow viewers to easily compare values side by side. Visual Encodings

Color: Different colors are used for each antibiotic (Neomycin, Penicillin, and Streptomycin). This visual encoding helps in distinguishing between the antibiotics and makes the comparison intuitive. Bars: The length of the bars represents the effectiveness of each antibiotic, which is a common and easily understandable encoding for quantitative data. Size and Scale

Axes: The x-axis represents the bacterial strains, while the y-axes represent the effectiveness of the antibiotics. Each y-axis is scaled appropriately for the measurement units of the respective antibiotics, ensuring accurate representation of the data. Scale Adjustments: Separate scales for each antibiotic are necessary due to the different measurement units, but this also introduces complexity. Sorting and Data Transformations

Grouping by Gram Staining: Bacteria are grouped by Gram staining (Gram-negative and Gram-positive). This grouping is important as it highlights the differential effectiveness of antibiotics based on bacterial classification. Order: Bacterial strains are listed categorically, which may not imply any specific order but aligns with the logical grouping for comparison. Justification for Design Choices Facilitating Effective Communication

Clear Comparisons: The grouped bar chart makes it straightforward to compare the effectiveness of different antibiotics on the same bacterial strain. Intuitive Understanding: The use of distinct colors for each antibiotic helps in quick identification and comparison, reducing cognitive load on the viewer. Accuracy: Separate y-axes ensure that each antibiotic’s effectiveness is accurately represented according to its measurement units. Contextual Grouping: Grouping bacteria by Gram staining adds context to the data, making it clear how the antibiotics perform differently against Gram-positive and Gram-negative bacteria. Enhancing Readability and Interpretation

Legend and Labels: Including a legend and clear axis labels ensures that the graph is self-explanatory. Viewers can easily understand what each bar and color represents. Granularity: While the graph does not include specific numerical labels, the bar lengths provide a visual estimate of effectiveness, which is sufficient for high-level analysis.

[SriNandhiniThiyagarajan]

Name: SriNandhini T Roll. No.: 21f2001390 Email ID: 21f2001390@ds.study.iitm.ac.in

Visualization

Introduction: In designing the chart, I aimed to effectively communicate the performance of three antibiotics (Penicillin, Streptomycin, and Neomycin) against 16 different bacteria, while also indicating their Gram staining reactions. The chosen visualization is a grouped bar chart, as it allows for direct comparison of the minimum inhibitory concentration (MIC) values across multiple categories (bacteria and antibiotics).

Title and Labels: The chart is titled "Minimum Inhibitory Concentration (MIC) of Antibiotics on Various Bacteria" to clearly convey the content. The x-axis is labeled "Bacteria" to indicate the different bacterial species being tested, and the y-axis is labeled "MIC (log scale)" to denote the concentration required to inhibit bacterial growth. The log scale on the y-axis helps in managing the wide range of MIC values, making it easier to compare smaller and larger values.

Color Coding and Legend: Colors are used to differentiate between Gram-positive and Gram-negative bacteria, with a legend indicating this classification. Additionally, different colors represent the three antibiotics (Penicillin in dark blue, Streptomycin in teal, and Neomycin in orange), allowing for quick visual identification and comparison. The color choice is deliberate to ensure clear contrast and readability.

Data Grouping and Sorting: Bacteria are grouped by their Gram staining reaction (Gram-positive and Gram-negative), with a slight background shading to visually separate these two groups. Within each group, the bacteria are sorted alphabetically. This organization aids in highlighting the Gram staining information while maintaining an easy-to-follow structure.

Effectiveness of the Design: The grouped bar chart is effective in showing which antibiotics are more potent against specific bacteria by comparing the heights of the bars within each group. The log scale on the y-axis ensures that both low and high MIC values are discernible, which is crucial for understanding the relative effectiveness of the antibiotics.

Conclusion Overall, the chosen design and visual encodings facilitate effective communication of the antibiotic performance data by emphasizing direct comparisons and clearly indicating Gram staining classifications, while maintaining readability and clarity.

[Arshi81099]

Name: Arshi Khan Roll. No.: 21f3002806

Chart Design and Rationale

The chart designed is a horizontal bar chart titled "Comparison of Antibiotic Effectiveness (MIC) on Bacteria". This visualization effectively communicates the relative effectiveness of three antibiotics (Neomycin, Penicillin, and Streptomycin) across various bacterial strains. The primary goal is to compare the Minimum Inhibitory Concentration (MIC) values for each antibiotic, where lower MIC values indicate higher effectiveness.

Visual Encodings and Design Decisions

Visualization Type: A horizontal bar chart was chosen as it allows for easy comparison across multiple categories. Each bacterial strain is listed on the y-axis, while the MIC values are represented on the x-axis. This layout facilitates straightforward horizontal comparison of MIC values for each antibiotic.

Color Encoding: Different colors are assigned to each antibiotic: blue for Neomycin, orange for Penicillin, and red for Streptomycin. This color differentiation helps in quickly identifying and comparing the effectiveness of each antibiotic across bacterial strains.

Scale and Axes: The x-axis uses a logarithmic scale to accommodate the wide range of MIC values, from very small to very large. This scaling method ensures that smaller values are visible and comparable, which would be difficult with a linear scale. The y-axis lists the bacteria alphabetically for consistent and intuitive order.

Labels and Legends: The chart includes legends for antibiotics and Gram Staining (positive and negative), and the x-axis is labeled "Value" to indicate MIC values. Legends and color-coded bars enhance the interpretability of the chart, making it self-explanatory without additional text.

Effective Communication and Potential Limitations

The horizontal bar chart with a logarithmic x-axis scale, color-coded bars, and labeled axes provides a clear and informative visualization of antibiotic effectiveness. The design choices facilitate effective communication by making comparisons straightforward and ensuring all MIC values are visible. However, the logarithmic scale may obscure small numerical differences between MIC values, and viewers with color vision deficiencies may have difficulty distinguishing between the colors used for antibiotics. Despite these limitations, the chart successfully highlights the key aspects of the dataset.

[Afringowhar]

Name: Syed Afrin Gowhar Roll No. : 21f2001140

1. Chart Type:

   • Bar Chart: A bar chart was chosen to compare the Minimum Inhibitory Concentration (MIC) values for three antibiotics (Penicillin, Streptomycin, Neomycin) against various bacteria. This type of chart allows for a clear comparison of antibiotic effectiveness across different bacterial strains.

   Logarithmic Scale on Y-Axis:

   • MIC Values: The y-axis uses a logarithmic scale to display MIC values. This scale helps in visualizing differences in antibiotic effectiveness that span several orders of magnitude.

Color Coding and Symbols:

• Antibiotics: Different colors are used for each antibiotic (Blue for Penicillin, Green for Streptomycin, Red for Neomycin).
• Gram Staining: Symbols indicate Gram staining results: a circle for Gram-positive bacteria and an "X" for Gram-negative bacteria. This adds an extra layer of information regarding bacterial classification.

Labels and Legends:

• Title and Axis Labels: The chart includes a descriptive title and labeled axes to ensure clarity.
• Legend: A legend explains the color coding and symbols, allowing for quick reference and understanding.

Analysis:

1. Effectiveness of Antibiotics:

   • Penicillin: Generally more effective against Gram-positive bacteria. For example, it has low MIC values for bacteria like Staphylococcus albus and Streptococcus fecalis, indicating high effectiveness. Conversely, it is less effective against Gram-negative bacteria such as Escherichia coli and Pseudomonas aeruginosa, which have higher MIC values.
   • Streptomycin: Shows a broader range of effectiveness, working well against both Gram-positive and Gram-negative bacteria. It is particularly effective against Brucella anthracis, indicated by its low MIC value.
   • Neomycin: Exhibits consistent effectiveness across most bacteria but is slightly less effective against certain Gram-positive bacteria compared to Streptomycin.

2. Influence of Gram Staining:

   • Gram-Positive Bacteria: Typically have lower MIC values for Penicillin, confirming its traditional use for these types of infections.
   • Gram-Negative Bacteria: Often require higher concentrations of Penicillin, underscoring the need for alternative antibiotics like Streptomycin and Neomycin for effective treatment.

3. Notable Observations:

   • High Susceptibility: Brucella anthracis shows very low MIC values for Streptomycin, indicating high susceptibility.
   • Resistance Patterns: Escherichia coli and Pseudomonas aeruginosa have high MIC values for Penicillin, suggesting resistance and highlighting the importance of using other antibiotics for treatment.
   • Streptococcus Species: These bacteria generally show low MIC values for Penicillin, reinforcing its effectiveness in treating infections caused by these species.

• This chart communicates which antibiotics are most effective against different bacteria and how Gram staining influences antibiotic choice.
• The use of color coding and symbols enhances understanding, allowing viewers to quickly grasp the data.
• The alphabetical arrangement of bacteria might not highlight specific trends within bacterial families, it provides an unbiased comparison of individual bacterial responses to antibiotics.
• This design ensures clarity and ease of interpretation, making the data accessible and informative for viewers.

[mnatasha1402]

Name: Natasha Mittal Roll. No.: 21f1005823

Visual Encodings: Chart Type: A grouped bar chart is used because it allows direct comparison of the MIC values of different antibiotics for each bacterium. Color: Different colors are used for each antibiotic to distinguish between them easily. For instance, antibiotic Pencillin is blue, Neomycin is dark blue, and Streptomycin is orange. Grouping: Bacteria are grouped by their Gram staining result (green background: Gram-positive, red background: Gram negative). Within each group, bacteria are sorted alphabetically for clarity. Scale: The Y-axis represents the MIC values on a log scale, which makes it easier to interpret differences in antibiotic effectiveness.

Rationale for Design Decisions: Grouped Bar Chart: This chart type is appropriate because it visually differentiates the performance of each antibiotic for each bacterium. It also makes it easy to compare the effectiveness of antibiotics within the same bacterium and across different bacteria. Color Coding: Using distinct colors for each antibiotic helps in quickly identifying and differentiating the performance of each one. Grouping by Gram Staining: By grouping the bacteria based on their Gram staining result, we can analyze trends related to Gram-positive and Gram-negative bacteria more effectively. It helps in identifying if there is a general difference in antibiotic effectiveness between these two categories.

Potential Limitations: One aspect that might be downplayed is the specific numerical MIC values, as the focus is on visual comparison rather than exact values. Another limitation is that it might be challenging to see very small differences in MIC values due to the scale and bar width, which could obscure subtle variations.

[Kirupa-Krishan]

Name: Kirupa Krishan G Roll No. : 21f1006352

Enhanced Chart Design and Rationale

Chart Description

The heatmap titled "Minimum Inhibitory Concentration (MIC) of Antibiotics on Bacteria" uses the original MIC values and incorporates Gram staining information. Each cell represents the MIC value for a specific antibiotic-bacteria pair, with color intensity indicating the level of effectiveness. Bacteria names are color-coded based on their Gram staining result: blue for Gram-positive and red for Gram-negative.

Design Decisions

1. Heatmap with Original Scale:

   • The heatmap uses the original MIC values to provide a direct view of antibiotic effectiveness. This allows for the immediate understanding of the concentration levels required to inhibit bacterial growth.

2. Color-Coding Gram Staining:

   • Bacteria names on the y-axis are color-coded to indicate Gram staining results Blue:Positive and Red:Negative. This visual differentiation helps understand the relationship between Gram staining and antibiotic effectiveness.

3. Annotation and Scaling:

   • Each cell in the heatmap is annotated with the exact MIC value to maintain precision and clarity.
   • The colour gradient (YlGnBu) effectively highlights differences in MIC values, with lighter colours representing higher antibiotic effectiveness (lower MIC values).

4. Title and Labels:

   • The descriptive title provides context about the chart's content.
   • Axis labels clearly identify the antibiotics and bacteria, ensuring the chart is interpretable without additional context.
   • The x-axis labels are rotated for better readability, preventing overlap and making it easier to read each antibiotic name.

Let's display the basic statistics and analysis directly here:

Basic Statistics for Each Antibiotic

Antibiotic	Penicilin	Streptomycin	Neomycin
Mean	65.091	8.707	3.585
Standard Dev	209.558	24.273	8.029
Min	0.001	0.01	0.001
25th Percentile	0.003	0.25	0.028
Median	0.34	1.5	0.25
75th Percentile	25.0	6.25	2.0
Max	870.0	100.0	40.0

Average MIC Values by Gram Staining

Gram Staining	Penicilin	Streptomycin	Neomycin
Positive	0.622	5.75	5.762
Negative	129.561	11.05	1.408

Analysis

1. Effectiveness of Antibiotics:

   • Penicillin has a wide range of MIC values, with a high standard deviation indicating varied effectiveness across different bacteria. Its mean MIC value is significantly skewed by high outliers (e.g., 870.0 for Aerobacter aerogenes).
   • Streptomycin and Neomycin exhibit lower mean MIC values compared to Penicillin, suggesting higher overall effectiveness against the tested bacteria. Streptomycin shows a particularly high maximum MIC value (100.0), indicating resistance in certain bacteria.

2. Gram Staining Differences:

   • Gram-positive bacteria are generally more susceptible to Penicillin and Neomycin, as indicated by their lower average MIC values.
   • Gram-negative bacteria exhibit higher resistance to Penicillin, with an average MIC value of 129.561, compared to just 0.622 for Gram-positive bacteria. However, Gram-negative bacteria are more susceptible to Neomycin, with a lower average MIC value of 1.408 compared to 5.762 for Gram-positive bacteria.

3. Implications for Treatment:

   • Penicillin may be more effective for treating Gram-positive bacterial infections but less so for Gram-negative infections, highlighting the importance of Gram staining in guiding antibiotic selection.
   • Streptomycin and Neomycin show more consistent effectiveness across both Gram-positive and Gram-negative bacteria, making them versatile options for treatment.

This analysis provides insights into the relative effectiveness of different antibiotics against various bacterial strains and underscores the importance of considering Gram-staining results when selecting appropriate treatments.

Strengths and Limitations

Strengths:

• Comprehensive Analysis: The heatmap enables quick visual comparison of antibiotic effectiveness across multiple bacteria, highlighting which antibiotics are most effective (lowest MIC values) and which bacteria are most resistant (highest MIC values).
• Incorporation of Gram Staining: Color-coding the bacteria names adds an important layer of information without cluttering the heatmap, allowing for a comprehensive analysis.

Limitations:

• Color Perception: Some viewers may have difficulty distinguishing between similar shades of the color gradient. Alternative color schemes or supplementary markers (e.g., symbols) could address this issue.

[Harsehraab]

Name: Harsehraab Singh Sarao Roll no: 21f1000507 Email: 21f1000507@ds.study.iitm.ac.in

Description and Rationale:

The above shown visualization compares the effectiveness of various antibiotic drugs as tested against 16 different bacteria. The visualization uses Minimum Inhibitory Concentration values that are measured using a logarithmic scale. Smaller the value of MIC the more effective the drug seems to be.

Design Decisions:

1) Grouped Bar Chart has been used here to allow easy comparison of the 3 drugs for each bacteria. 2) Gram negative and gram negative bacteria have been separated into different categories for ease of analysis. 3) Colour Encoding, each drug is easy to distinguish due to as each drug is represented by a distinct colour. 4) Logarithmic scale has been used to allow display of MIC values such that the visualization is manageable and easy to understand.

Effective Communication:

1) Effectiveness of the three drugs is clearly outlined in the above visualization. 2) Logarithmic scale prevents the smaller values are not obscured. 3) Colour coding provides a means of providing immediate cue, at a glance.

Limitations:

The visualization supresses the actual difference between MIC values as it is uses the logarithmic scale.

[ranjan-satya]

Satya Ranjan Sahu DS21f1005375

Objective: The bar graphs show the effectiveness of different antibiotics on gram +ve bacteria and gram -ve bacteria individually. It also shows on which bacteria the overall effectiveness of the Antibiotics are more. The informations used in the visual representation of data targets the general audience which include newspaper readers, Television audiences etc.

Rationale: As the visual representation of data targets the general audience and the length of the bars will be inversely proportional to the effectiveness of the antibiotics if presented as per the given data, this might be counter intuitive for the readers. That’s why to make it easy the values of MIC has been inversed in the graph.

After inversing the values, the standard deviations were quite high. The spread of values which are greater than the third quartile are more as compared to other values. So I have squeezed the values between third quartile and maximum value where the values range between third quartile and third quartile + 1.5*IQR. This transformation that has been done will not alter the message that is meant to be conveyed through this visualisation.

The transformations that were carried out were done separately for Gram +ve bacterias and Gram -ve bacterias because of the significant difference in the effectiveness of the antibiotics on the given types of bacterias.

Downplay: The exact values has been washed away due to the transformation which will not affect the objective of the visual representation.

If the difference in the effectiveness of the individual antibiotics on different bacterias will be shown on the same graph, the difference in the height of the columns won’t be properly visible as it is quite vast. So 2 different graphs with different scales has been used for Gram +ve and Gram -ve bacterias.

[Arsh-21]

Assignment-3

Name: Arshpreet Kaur Roll number: 21f1000788

Graph

Description

For this assignment, I created a grouped bar chart to effectively present the Minimum Inhibitory Concentration (MIC) of three antibiotics (Penicillin, Streptomycin, and Neomycin) against 16 different bacteria. The chart is divided into Gram-negative and Gram-positive bacteria to clearly show the differences in antibiotic effectiveness between these two groups.

Design Decisions:

1. Chart Type: I chose a bar chart because it allows for easy comparison of the MIC values for each antibiotic across multiple bacteria. Bar charts are straightforward and effective for displaying categorical data.

2. Color Encoding: I used different colors to represent each antibiotic: red for Penicillin, blue for Streptomycin, and green for Neomycin. This color-coding makes it simple to distinguish between the antibiotics and compare their effectiveness visually.

3. Logarithmic Scale: The MIC values are plotted on a logarithmic scale (10^-3 to 10^3 µg/mL). This decision was made because MIC values span several orders of magnitude. A logarithmic scale ensures that differences in MIC values are visually proportional, making it easier to identify which antibiotics are more effective at lower concentrations.

4. Grouping by Gram Staining: The bacteria are grouped into Gram-negative (shaded blue) and Gram-positive (shaded yellow) categories. This grouping helps to highlight the distinction between the two types of bacteria and observe any patterns in antibiotic effectiveness related to Gram staining.

5. Titles and Labels: The chart includes a clear title, "Minimum Inhibitory Concentration (MIC) of Antibiotics on Different Bacteria," which succinctly describes what the chart represents. The y-axis is labeled "MIC (µg/mL)" to indicate the units of measurement, and the x-axis is labeled "Bacteria" to show the different bacteria tested. A legend is included to identify which color corresponds to which antibiotic.

Effective Communication:

This design highlights several key aspects of the data:

• Comparison of Antibiotics: By using distinct colors for each antibiotic, it’s easy to see which antibiotic is more effective against specific bacteria.
• Effectiveness Across Bacteria: The logarithmic scale allows for a better comparison of MIC values across a wide range of concentrations.
• Gram Staining Impact: Grouping the bacteria by Gram staining helps to observe any trends in antibiotic resistance between Gram-positive and Gram-negative bacteria.

Potential Limitations:

While the chart is effective in many ways, there are some aspects that might be downplayed:

• Specific Values: The exact MIC values are not explicitly labeled on the bars, which might make it harder for someone who needs precise data rather than a visual comparison.
• Density of Information: With 16 bacteria and three antibiotics, the chart can appear cluttered, especially for those unfamiliar with logarithmic scales or interpreting bar charts with numerous data points.

Overall, the design choices were made to facilitate a clear and comparative view of the effectiveness of three antibiotics against a range of bacteria, while also highlighting the impact of Gram staining on antibiotic resistance.

Tools used:

Python (Seaborn) and Excalidraw

[miqbal07]

Name - Iqbal Hossain Roll no. - 21f2000965 Title - Effectiveness of Antibiotics on Various Bacteria

Chart Type: Scatter Plot: The scatter plot is selected to compare the Minimum Inhibitory Concentration (MIC) values for three antibiotics (Penicillin, Streptomycin, Neomycin) against various bacteria. This chart type effectively shows the differences in antibiotic effectiveness across different bacterial strains.

Logarithmic Scale on Y-Axis: The y-axis uses a logarithmic scale to display MIC values, which helps visualize differences in antibiotic effectiveness that span several orders of magnitude. This scale ensures that both small and large MIC values are clearly distinguishable.

Color Coding and Symbols: Antibiotics: Different symbols are used for each antibiotic to facilitate easy comparison: Circle for Penicillin Asterisk for Streptomycin Square for Neomycin Gram Staining: Colors indicate Gram staining results: Blue for Gram-positive bacteria Red for Gram-negative bacteria This dual coding of color and symbols adds an extra layer of information regarding bacterial classification.

Labels and Legends: Title and Axis Labels: The chart includes a descriptive title ("Effectiveness of Antibiotics on Various Bacteria") and labeled axes (x-axis: "Bacteria", y-axis: "Minimum Inhibitory Concentration (MIC)"). Legend: A legend explains the color coding and symbols, allowing for quick reference and understanding. Analysis:

Effectiveness of Antibiotics:

Penicillin: Generally more effective against Gram-positive bacteria. It has low MIC values for bacteria like Staphylococcus albus and Streptococcus fecalis, indicating high effectiveness. Conversely, it is less effective against Gram-negative bacteria such as Escherichia coli and Pseudomonas aeruginosa, which have higher MIC values. Streptomycin: Shows a broader range of effectiveness, working well against both Gram-positive and Gram-negative bacteria. It is particularly effective against Brucella anthracis, indicated by its low MIC value. Neomycin: Exhibits consistent effectiveness across most bacteria but is slightly less effective against certain Gram-positive bacteria compared to Streptomycin.

Influence of Gram Staining: Gram-Positive Bacteria: Typically have lower MIC values for Penicillin, confirming its traditional use for these types of infections. Gram-Negative Bacteria: Often require higher concentrations of Penicillin, underscoring the need for alternative antibiotics like Streptomycin and Neomycin for effective treatment.

Notable Observations: High Susceptibility: Brucella anthracis shows very low MIC values for Streptomycin, indicating high susceptibility. Resistance Patterns: Escherichia coli and Pseudomonas aeruginosa have high MIC values for Penicillin, suggesting resistance and highlighting the importance of using other antibiotics for treatment. Streptococcus Species: These bacteria generally show low MIC values for Penicillin, reinforcing its effectiveness in treating infections caused by these species.

Conclusion: This scatter plot effectively communicates which antibiotics are most effective against different bacteria and how Gram staining influences antibiotic choice. The use of color coding and symbols enhances understanding, allowing viewers to quickly grasp the data. Although the alphabetical arrangement of bacteria might not highlight specific trends within bacterial families, it provides an unbiased comparison of individual bacterial responses to antibiotics.

[sahilrajpal121]

Name: Sahil Rajpal Roll number: 21f1006804

Title: Effectiveness of Antibiotics on Different Bacteria (MIC Values)

This bar chart visualizes the effectiveness of three antibiotics—Penicillin, Streptomycin, and Neomycin—against 16 different bacteria. The effectiveness is measured using the Minimum Inhibitory Concentration (MIC) on a logarithmic scale, where lower values signify higher effectiveness. The chart is divided into two sections: Gram-negative and Gram-positive bacteria, distinguished by light blue and light green backgrounds, respectively.

Design Rationale:

1. Horizontal Bar Chart: A horizontal bar chart is chosen for its readability and effectiveness in comparing MIC values across different bacteria. This format allows for clear labeling along the y-axis and side-by-side comparison of the antibiotics.

2. Logarithmic Scale and Color Coding: The use of a logarithmic scale ensures that both small and large MIC values are effectively displayed, making the differences in antibiotic effectiveness more apparent. Different colors are assigned to each antibiotic (dark blue for Penicillin, green for Streptomycin, and light green for Neomycin) to facilitate easy comparison.

3. Background Differentiation by Gram Staining: The background colors (light blue for Gram-negative and light green for Gram-positive) visually separate the bacteria into two groups, aiding in the identification of patterns related to Gram staining. This sorting emphasizes the relationship between Gram staining and antibiotic effectiveness.

4. Legends and Annotations: The chart includes a title, axis labels, and a legend for clarity. Text annotations label the sections for Gram-negative and Gram-positive bacteria, providing immediate context and enhancing the chart’s interpretability.

This design aims to present a clear and detailed comparison of antibiotic effectiveness while highlighting the distinction between Gram-negative and Gram-positive bacteria, ensuring that the viewer can easily interpret the data and observe relevant patterns.

[vpleaides8]

Comparative Effectiveness of Antibiotics on Bacteria

Name: Kruttika Milind Soni Roll no: 21f1001029 Email: 21f1001029@ds.study.iitm.ac.in

This visualisation aims to showcase the effectiveness of 3 popular antibiotics ; Penicillin, Neomycin and Streptomycin in treating 16 bacteria. It also shows the results of the Gram staining technique, classifying the bacteria as either Gram positive or Gram negative. The main objective is to show the overall difference in effectiveness of antibiotics on Gram positive and negative bacteria. The graph shows a trend that antibiotics perform better against Gram negative bacteria as compared to Gram positive bacteria. This is especially the case for Penicillin.

My rationale for various design decisions is as follows:

1. Visualisation type: I chose a Radar chart as it compares multiple quantitative variables on one plot using different axes and displays multivariate data. Thus bacteria is a quantitative variable on the axes and various antibiotics form the multivariate data points.
2. Size: I have sized it so that the graph takes much of the page. Gram positive bacteria are represented by large columns for easy identification.
3. Colour: All the antibiotics have distinct colours that are easy to differentiate. I used semantic encoding to represent gram positive bacteria as purple columns, though they are lighter than the important antibiotic data.
4. Scale: I have used a logarithmic scale as the range of values was from $10^{-3}$ to $10^{3}$.
5. Visual Elements: The legend at the top right shows that each antibiotic is also represented by a different shape.This reduced errors when the data overlaps. Gridlines are also used to help a studious observer find exactly which antibiotic is most effective against a given bacteria. Additionally, the bacteria names have been shortened from the whole scientific name to just the initial of the genus name and species name. This is a well accepted format for scientific names and reduces the visual complexity.
6. Sorting: The data has been sorted into Gram positive and Gram negative to better show the differences between these two types of bacteria.

This visualisation downplays some aspects of the data to achieve its objective:

1. Specific MIC values cannot be seen here as the scale is logarithmic. Rather than that, the focus is on comparing antibiotics.
2. The user cannot see the full scientific names of the bacteria.
3. Radar chart may distort data making higher values seem more visually important. This is not useful when trying to gauge just how much better an antibiotic is as compared to another for a certain bacterial treatment.

Overall, this visualisation can be used to show a trend for antibiotics and be a case for use of certain antibiotics for Gram negative/positive bacteria. It is meant to be used by medical professionals or researchers who already have expertise in this topic as a general visualisation of the data.

Made on Power BI

[Sa-N98]

Name: Saranya Nayak Roll No. :21f1005767

Aspects to Communicate:

1. Effectiveness of post WW2 antibiotic against different bacterial species
2. See if type of Gram Staining has any correlation with antibiotic effect.

Design Decisions and Rationale

Visualization Type and Layout: The horizontal bar chart, split into Gram-positive and Gram-negative sections, allows for comparison of antibiotic effectiveness across bacterial species and types. Effect: This layout accommodates long bacterial names and multiple bars per species, enhancing readability by using the full width of the display.

Color Encoding: Three distinct colors (teal, dark blue, and red) represent the antibiotics consistently across all bacteria, enabling quick visual comparison. _Effect:_The contrasting colors aid in distinguishing between antibiotics, even with small or overlapping bars.

Scale and Axis: The logarithmic x-axis scale is crucial for representing the wide range of MIC values (0.001 to 100,000). _Effect:_This allows visualization of both very small and large values, facilitating comparison of relative differences rather than absolute ones.

Data Organization: Separating Gram-positive and Gram-negative bacteria allows for comparing antibiotic effectiveness between these categories. _Effect:_The current sorting aids systematic scanning, though sorting based on antibiotic sensitivity could reveal clearer patterns.

Potential Downplays

Specific Numerical Values:

Issue: The use of a logarithmic scale, while necessary for visualization, may obscure precise MIC values for some viewers. Trade-off: This was done to facilitate broader comparisons and manage the wide range of data effectively. Individual Antibiotic Trends:

Issue: Trends or patterns within a single antibiotic’s effectiveness across all bacteria might not be as immediately apparent compared to focusing on the grouped comparison. Trade-off: The focus is on comparative effectiveness across antibiotics rather than trends within a single antibiotic.

[U-Adithyan]

Name: U Adithyan Roll No: 21f1000703

• Here we have compared the MICs of various antibiotics on the given set of Bacteria.
• The visualization was made as a stacked bar chart for easier antibiotic comparison.
• The background Colours help identify the Gram Straining Result for the Bacteria as well.
• The scale for the y-axis was made logarithmic to capture the large scale difference covered by the data, however, it might also be misleading as it can make unwanted comparisons (small differences in the graph, in reality, are very huge)

[Jigyasa2408]

Name - Jigyasa Roll No. - 21f1001644

Design Rationale :

Visualization Type and Scale The chart above is a grouped bar chart with a logarithmic y-axis, which displays the Minimum Inhibitory Concentration (MIC) values of three different antibiotics against various bacteria. The use of a logarithmic scale is crucial here because MIC values can range over several orders of magnitude. This scaling compresses the data range, making it easier to visualize and interpret the relative effectiveness of the antibiotics. Without this scale, the vast differences in MIC values would make the chart difficult to read and analyze.

Colors and Labels Different colors represent each antibiotic: Penicillin (blue), Streptomycin (orange), and Neomycin (green). This color coding helps in quickly distinguishing between the antibiotics. Each bar is labeled with its exact MIC value for precise data communication. Additionally, the bacteria names on the x-axis are colored red for gram-negative and green for gram-positive, which helps in understanding the resistance pattern based on the bacteria type.

Text Annotations Four bullet points below the chart provide additional context and explanations. These annotations clarify terms such as MIC and the significance of gram-positive and gram-negative bacteria, as well as the rationale behind using a logarithmic scale. This textual information complements the visual data, ensuring that the viewer understands the chart’s content and the scientific principles behind it.

Data Sorting and Emphasis The bacteria are sorted on the x-axis by type (gram-positive vs. gram-negative). This sorting helps in identifying antibiotic effectiveness. By grouping similar bacteria, the chart allows viewers to easily compare the effectiveness of antibiotics within and across these groups.

Limitatios The individual variations within each antibiotic's performance might be downplayed due to the logarithmic scaling compressing higher values more significantly.

Conclusion The design decisions in this chart prioritize clear and effective communication of MIC values, with careful consideration of scale, color, and annotations. By using a logarithmic scale, color coding, and detailed labeling, the chart ensures that viewers can easily understand and interpret the data, while also providing necessary context through textual explanations.

[subhashree211002]

Wonder drugs of World War II - A Visualisation

Explanation of Chart Design

Title and Axis Labels

The chart is titled "Antibiotic Effectiveness Against Bacteria" to clearly indicate the purpose of the visualization. The x-axis is labeled "Bacteria," listing the names of the 16 bacteria tested, while the y-axis is labeled "MIC (µg/mL)" to represent the Minimum Inhibitory Concentration, using a logarithmic scale to accommodate the wide range of MIC values.

Chart Type and Visual Encodings

The chart uses a grouped bar chart to display the MIC values for three antibiotics: Penicillin, Streptomycin, and Neomycin, across different bacteria. Each group of bars represents one bacterium, with distinct colors for each antibiotic (purple for Penicillin, red for Streptomycin, and blue for Neomycin). The color gradient in the bars represents the effectiveness of each antibiotic by representing the negative logarithmic value of the MIC -log(MIC) = log(1/MIC) The inverse of MIC value and hence a darker gradient indicates a more effective antibiotic (lower MIC value).

Logarithmic Scale

A logarithmic scale is used for the y-axis to manage the large variability in MIC values and to make it easier to compare the effectiveness of antibiotics across different bacteria. This scale helps to prevent smaller MIC values from being visually overshadowed by larger ones and provides a clearer comparison. For a similar reason values used for the gradient calculation (1/MIC values) are also converted to logarithmic scale for robust visualization.

Gram Staining Classification

The chart presents all gram negative bacteria followed by the gram positive bacteria. In addition, the chart includes the Gram staining classification of each bacterium above the bars (gram-positive in green and gram-negative in orange). This additional layer of information helps to analyze if there is a pattern in antibiotic effectiveness based on the Gram staining properties of the bacteria.

Legends and Gradient Heatmaps

A legend is included to identify the colors representing each antibiotic. Additionally, heatmaps at the bottom right corner provide a visual representation of the logarithmic 1/MIC values for each antibiotic, reinforcing the information conveyed by the gradients used in the bars.

Aspects Emphasized

Two primary aspects are emphasized by this visualization:

• the resistance of each given bacteria to the 3 different antibiotics: The logarithmic scale allows for a better visual comparison of the MIC values across a wide range. The use of colors differentiates each antibiotic within each group corresponding to each bacterium. Within the group, higher the height of the bar, more resistance by the respective bacterium against the corresponding antibiotic. Hence to chose the antibiotic to which the bacterium has least resistance, we need to choose the one with the shortest bar for the given bacterium.
• the effectiveness of a each antibiotic against different bacteria: The use of gradients allows easy comparison of a given antibiotic's effectiveness against different bacteria. The darker the color of the bar, more effective. For example, the darkest of bars for neomycin corresponding to the associated blue color occurs at Staphyllococcus aureus, which reflects that neomycin is the most effective against the given bacterium.
• the pattern of higher resistance by gram negative to antibiotics: the heights of the bars and tend to be naturally higher and the gradients lighter for gram negative bacteria showing that antibiotic effectiveness is low and bacterial resistance is in general high for the gram negative bacteria.

Aspects Downplayed

While the chart effectively communicates the comparative effectiveness of the antibiotics, it might downplay the absolute differences in MIC values due to the logarithmic scale. Some fine details of the MIC values might be less discernible. Additionally, the chart focuses on the MIC values without delving into potential clinical implications or specific resistance mechanisms of the bacteria.

Rationale for Design Decisions

• Grouped Bar Chart: Chosen for its ability to compare multiple categories (antibiotics) across several groups (bacteria).
• Logarithmic Scale: Used to handle the large range of MIC values and to make differences in lower values more visible.
• Color and Gradient: Color distinguishes between bacterial resistance against antibiotics, while the gradient represents antibiotic effectiveness, providing a dual encoding that enhances interpretability.
• Gram Staining Classification: Adds a layer of biological relevance, helping to identify patterns related to bacterial classification.
• Legends and Heatmaps: Aid in the interpretation of the chart, ensuring that viewers understand the significance of the colors and gradients.

This visualization effectively communicates the comparative effectiveness of the antibiotics while also providing contextual information about the bacteria tested, facilitating a comprehensive analysis of the data.

[Nivoceros]

Name : Nivedita Jayaswal Roll : 21f1004471 Email : 21f1004471@ds.study.iitm.ac.in

The chart I have designed is titled "Effectiveness of antibiotics on different bacteria" and it visually represents the effectiveness of three antibiotics—Penicillin, Streptomycin, and Neomycin—on 16 different bacteria. The effectiveness is measured by the minimum inhibitory concentration (MIC), where lower MIC values indicate higher effectiveness. Each antibiotic is represented by a different color: purple for Penicillin, red for Streptomycin, and yellow for Neomycin. The bacteria are listed on the y-axis, while the x-axis represents the effectiveness of the antibiotics in percentage.

Design Rationale

Bar Chart Selection: A horizontal stacked bar chart is used to show the effectiveness of each antibiotic on the bacteria. This type of chart allows for easy comparison of the effectiveness of each antibiotic across the different bacteria. The horizontal orientation facilitates reading the bacteria names and comparing the bar lengths simultaneously.

Sorting: The bacteria are sorted alphabetically. This approach makes it straightforward to locate a specific bacterium and compare its response to the antibiotics. An alternative could have been to sort by effectiveness, but this might obscure the direct comparison between bacteria.

Axes and Labels: Title: Clearly states the purpose of the chart. Y-axis: Lists the bacteria names for easy identification. X-axis: Represents the effectiveness percentage, making it clear how effective each antibiotic is. Labels: Different colors are used to distinguish between the antibiotics. Purple, red, and yellow are chosen for Penicillin, Streptomycin, and Neomycin, respectively. These colors are distinct from each other, reducing confusion and enhancing the chart's readability.

[varunbalaji1303]

Name: Varun Balaji Roll No: 21f1005027

The chart is a bar plot representing the Minimum Inhibitory Concentration (MIC) of three antibiotics (Penicillin, Streptomycin, and Neomycin) against various bacteria. The x-axis uses a logarithmic scale for MIC values, while the y-axis lists the bacteria. The hue represents different antibiotics, and Gram staining is indicated by blue (positive) and red (negative) dots next to the bacteria names.

Aspects Highlighted

1. Comparison of Antibiotic Effectiveness: By using different colors for each antibiotic, the chart clearly shows which antibiotics are more effective against specific bacteria. The log scale on the x-axis allows us to visualize the large range of MIC values effectively.
2. Gram Staining: The small dots next to each bacterium's name indicate whether they are Gram-positive or Gram-negative. This additional information helps to understand patterns in antibiotic effectiveness related to Gram staining.

Design Decisions

1. Bar Plot with Logarithmic Scale: A bar plot was chosen because it allows for easy comparison of MIC values across multiple antibiotics. The log scale is essential due to the wide range of MIC values, making it easier to discern differences, especially among smaller values.
2. Color Coding by Antibiotic: Different colors for each antibiotic make it easy to compare their effectiveness against each bacterium.
3. Gram Staining Indicator: Adding colored dots for Gram staining ensures that this crucial information is visible without overcrowding the chart.

Potential Limitations

1. Complexity: The use of multiple colors and log scale can be complex for some viewers to interpret, especially if they are not familiar with logarithmic scales.
2. Detail Obscured: Some details, such as very small differences in MIC values among antibiotics for the same bacterium, may be less noticeable due to the scale and bar widths.

Overall, this design effectively communicates the key aspects of antibiotic effectiveness and Gram staining while maintaining readability and clarity. ​

[Ashrey30]

Name: Ashrey Roll No. 21f2000448

Antibiotic Sensitivity

Effective Communication Aspects:

• Color Encoding: The heatmap uses color intensity to represent antibiotic sensitivity, allowing for quick visual comparison across bacteria and antibiotics. The color scale from light yellow (low sensitivity) to dark red (high sensitivity) effectively highlights differences in sensitivity levels.
• Data Labeling: Numerical values are included in each cell, providing precise information alongside the color-coded overview. This dual approach caters to both quick visual assessment and detailed data analysis.
• Layout and Organization: Bacteria are listed on the y-axis and antibiotics on the x-axis, facilitating easy comparison of a single bacterium's response to different antibiotics and vice versa. The alphabetical sorting of bacteria aids in locating specific species.

Limitations and Potential Improvements:

• Scale Range Issues: The wide range of sensitivity values (0.00 to 870.00) makes it challenging to represent all data points effectively on a single color scale. This may obscure subtle differences between low values while high values dominate the visual.
• Alternative Sorting: While alphabetical sorting helps in finding specific bacteria, it doesn't highlight patterns based on sensitivity levels. An alternative sorting method could potentially reveal more insightful patterns.
• Scale Adjustment: Implementing a logarithmic color scale or creating separate visualizations for different value ranges could improve the representation of the wide data range.

Rationale for Design Decisions:

• Visualization Type: A heatmap was chosen as it effectively displays three-dimensional data (bacteria, antibiotics, and sensitivity values) in a two-dimensional format, allowing for easy comparisons across multiple variables.
• Color and Scale: The yellow to red color scheme intuitively represents increasing intensity or sensitivity. However, the linear scale may not be optimal for the wide range of values present in the data.
• Data Transformations: Alphabetical sorting of bacteria was used for ease of reference, though this choice prioritizes findability over pattern recognition.

[21f1005544]

Name: John Joshi Alapatt Roll No: 21f1005544

Chart Analysis and Design Rationale

Title and Axis Labels: The chart is titled "Effectiveness of Antibiotics on Different Bacteria", providing a clear and concise description of the data presented. The x-axis is labeled "Bacteria", with each bacterium listed along this axis, and the y-axis is labeled "MIC (Minimum Inhibitory Concentration)", with a logarithmic scale to accommodate the wide range of MIC values.

Legend: The legend is well-designed to include both the antibiotic types and the Gram staining classification:

Penicillin: Green bars Streptomycin: Yellow bars Neomycin: Orange bars Gram-positive: Blue borders Gram-negative: Red borders This dual-legend system ensures that viewers can easily distinguish between different antibiotics and Gram staining classifications at a glance.

Logarithmic Scale: The y-axis uses a logarithmic scale, which is appropriate given the wide range of MIC values (from 0.001 to 870). This scaling allows for better visualization and comparison of smaller MIC values, preventing them from being overshadowed by much larger values.

Bar Clustering: The bars are clustered by bacteria, with each cluster containing three bars representing the effectiveness of Penicillin, Streptomycin, and Neomycin. This clustering facilitates direct comparison of antibiotic effectiveness for each bacterium.

Color Encoding: Color is used effectively to differentiate between antibiotics. The distinct colors (green, yellow, orange) for Penicillin, Streptomycin, and Neomycin, respectively, help in quickly identifying and comparing the effectiveness of each antibiotic. The use of blue and red borders for Gram-positive and Gram-negative bacteria, respectively, adds another layer of information, making it easy to identify any patterns related to Gram staining.

Design Strengths

Clarity and Comparability: The clustered bar chart allows for straightforward comparison of antibiotic effectiveness for each bacterium. Viewers can easily see which antibiotic is most effective. Detailed Legend: The comprehensive legend with both color fill and border information ensures that viewers can interpret the data accurately without additional explanation. Logarithmic Scale: Using a logarithmic scale helps in visualizing data that spans several orders of magnitude, making the chart more readable and the differences in MIC values more apparent. Potential Limitations:

Obscured Absolute Differences: While the logarithmic scale aids in comparison, it might obscure the perception of absolute differences in MIC values, especially for values that are close to each other. Broad Trends: The chart is excellent for within-bacterium comparisons but may require careful inspection to discern broader trends across all bacteria.

This visualization is designed to effectively communicate the relative effectiveness of three antibiotics against various bacteria, with additional insights provided by Gram staining classification. The choice of a clustered bar chart with a logarithmic scale, combined with clear color and border encoding, ensures that viewers can easily interpret the data and identify key patterns.

[Ashutosh-tec]

Name: Ashutosh Kumar Barnwal Roll: 21f1001709

Design of the Chart:

To communicate the effectiveness of three antibiotics on 16 bacteria, a horizontal bar chart was chosen. Each bar represents MIC values for Neomycin, Penicillin, and Streptomycin for each bacterium, with a title, axis labels, and a legend for clarity.

Visual Encodings:

Bar Chart Type: Facilitates comparison of MIC values across different bacteria, showing which antibiotic is more effective (lower MIC). Color Coding: Neomycin in red, Penicillin in yellow, Streptomycin in brown, with a legend to distinguish them. Axis Labels: X-axis for MIC values, Y-axis for bacteria names and Gram staining results, essential for context. Sorting by Gram Staining: Helps identify patterns in antibiotic effectiveness related to Gram staining. Rationale for Design Decisions:

Horizontal Bar Chart: Effective for long category names and comparison across multiple categories. Color and Legend: Distinct colors and a clear legend reduce cognitive load and prevent confusion. Axis Labels and Sorting: Enhances readability and highlights correlations between Gram staining and antibiotic effectiveness.

Emphasized Aspects:

Comparison of Antibiotic Effectiveness: Shows relative MIC values, highlighting the most effective antibiotic for each bacterium. Correlation with Gram Staining: Sorted bacteria reveal any patterns related to Gram staining.

Obscured Aspects:

Detailed MIC Values: Exact values might be harder to read directly off the chart. Other Covariates: Focuses solely on MIC and Gram staining, downplaying other factors. The design facilitates effective comparison and identification of key patterns while maintaining clarity.

[Dheeraj-Sathianarayanan]

Name : Dheeraj S Roll No : 21F1002027 Email : 21f1002027@ds.study.iitm.ac.in

Visualisation Type : This is a clustered column chart that visualises the effectiveness of Penicillin, Streptomycin, Neomycin on various bacteria. It allows efficient comparison within each bacterium group and different bacteria. Colours : Each colour column represents one particular antibiotic- Sky blue for Penicillin, Dark blue for Streptomycin, Orange for Neomycin. Axes: The x-axis consists the bacteria names, and the y-axis shows the MIC values. The y-axis uses logarithmic scale to accommodate the wide range of values.

Rationale: Clustered column chart: This helps in straightforward comparison of the MIC values for each antibiotic within each bacterium group. So it is easy to find out which antibiotic is most effective for treating which bacterium. Logarithmic scale : Since the MIC value spans a vast range, the logarithmic scale ensures better representation and meaningful comparisons.

Highlighted Aspects: The chart clearly visualises the MIC values of each antibiotic. So, we can understand the antibiotic with the least MIC value is the best choice for the particular bacterium.

Downplayed Aspects: The Gram Straining correlation is not visualised in this chart. The chart doesn't focus on statistical comparison instead it is a simplified visual comparison of the different antibiotics.

[srinivesh]

Comparative Effectiveness of Antibiotics on Bacteria

Name: S R Srinivasan

Roll no: 21f1002966

Email: 21f1002966@ds.study.iitm.ac.in

Objective:

The objective of the visualization is to compare the effectiveness of three antibiotics (Penicillin, Streptomycin, and Neomycin) across 16 different bacteria strains. The implementation was designed to highlight the most effective antibiotics for each strain,

Design Decisions

Graph Type:

A radar chart is chosen to represent the MIC values of the three antibiotics for each bacteria strain. While unusual to represent data with vary different scales, this chart type is useful to guide the selection of the most appropriate antibiotic.

Data Transformation:

The choice of the chart type required no major transformation of the data. For the minor objective of indicating the gram staining, the different strains were grouped into two - gram positive and gram negative; within the group, the ordering is alphabetical.

Color Scheme:

Each antibiotic is encoded with a unique color to facilitate clear visualization and easy identification. The detailed name of each antibiotic is provided in the legend along with its corresponding color.

Scale:

The data is represented in log scale. This effectively addresses the variations in the data. Further, the data is presented in reverse order; this places the most effective antibiotic at the outer point of the radar arm.

Other Considerations

As the gram staining nature was a minor factor, a simple line is used to separate the two groups. The chart is useful even without this visual cue. Clear labeling and a detailed legend are provided to aid interpretation and understanding of the visualization.

Limitations

1. The choice of the tool limits the visualization. A simple tabular visualization is very effective for this data, and a sample is found in the lecture video. That visualization seemed difficult to achieve within the chart types provided by Excel.
2. Without a tabular format, a visual encoding of the appropriate antibiotic is infeasible. The positioning in the chart is used to guide this.
3. The actual MIC value is not provided in the chart. Presenting this would increase the accuracy of the visualization.

Tool used: MS Excel

[harshymehta14]

Name - Harsh Y Mehta Roll No - 21F1001295

Keywords:

1. Minimum Inhibitory Concentration (MIC) - a measure of the effectiveness of the antibiotic
2. Vitro - outside the living body and in an artificial environment
3. Gram Staining - a test that checks to see if you have a bacterial infection

Design Decision:

1. Visualization Type - Bar Chart
2. Title - Antibiotics (in MIC) V/s Bacteria
3. X-axis - Bacteria
4. Y-axis - Minimum Inhibitory Concentration (MIC)
5. Scale - Logarithmic scale

Charts:

1. Gram Positive - Green Background (Fig 1)
2. Gram Negative - Red Background (Fig 2) The two charts help to identify whether the bacteria is gram positive or negative.

Process:

1. Data is categorized into Gram-positive and Gram-negative based on staining.
2. MIC values are scaled for comparative clarity.
3. Two charts are plotted using scaled data.
4. Aesthetic choices such as color, size, labels, and legends are applied.

Usefulness of Chart:

1. Easily identifies the most effective antibiotic for each bacterium.
2. Color coding by Gram staining reveals susceptibility patterns between bacterial types.

Downplayed: The chart focuses on comparing antibiotic effectiveness across bacterial species, highlighting trends rather than exact MIC values due to the logarithmic scale and grouped bar layout.

[bhumikaxyz]

About Me

Name: Bhumika Taneja Roll Number: 21f1006329

Visualization

The bar chart created effectively communicates the effectiveness of three antibiotics—Penicillin, Streptomycin, and Neomycin—on 16 different bacteria. The Minimum Inhibitory Concentration (MIC) values, plotted on a logarithmic scale, measure the concentration required to inhibit bacterial growth, with lower values indicating higher effectiveness.

Design Elements and Rationale

1. Chart Type

A bar chart was chosen because it allows for easy comparison of MIC values across multiple bacteria for each antibiotic. Bar charts are intuitive for comparing categorical data, and using different colors for each antibiotic facilitates a clear visual distinction between them.

2. Logarithmic Scale

The y-axis uses a logarithmic scale for the MIC values. Given the wide range of MIC values (spanning several orders of magnitude), a logarithmic scale is essential for accurately representing the data. It ensures that smaller values are not visually compressed, allowing for meaningful comparisons across all bacteria.

3. Color Coding

Each antibiotic is represented by a distinct color:

Penicillin in blue Streptomycin in orange Neomycin in green This color coding is consistent throughout the chart, enabling quick identification and comparison.

4. Gram Staining Classification

The background color of the chart is shaded to indicate Gram-positive (light pink) and Gram-negative (light green) bacteria. This addition provides context for interpreting the effectiveness of antibiotics concerning the Gram staining characteristic, a crucial factor in antibiotic selection.

5. Axis Labels and Title

The chart includes clear axis labels and a title:

The x-axis is labeled "Bacteria," listing the names of the bacteria tested. The y-axis is labeled "Minimum Inhibitory Concentration (log scale)," indicating the measure of antibiotic effectiveness. The title, "Effectiveness of Antibiotics on Different Bacteria," succinctly describes the chart's content.

6. Legend

A legend is included to explain the color coding of the antibiotics and the background shading for Gram staining. This ensures the chart is self-explanatory and can be interpreted without additional descriptions.

Aspects Emphasized and Downplayed

Emphasized

Comparison of Antibiotics: The chart effectively highlights which antibiotic is more effective against each bacterium by comparing the heights of the bars within each bacterial category.

Range of Effectiveness: The use of a logarithmic scale emphasizes the significant differences in antibiotic effectiveness, even when values span several orders of magnitude.

Gram Staining: The background shading provides immediate visual context about whether the bacteria are Gram-positive or Gram-negative, aiding in understanding the antibiotics' varying effectiveness.

Downplayed

Individual Data Points: The chart does not emphasize individual data points or variability within each bacterial category. It focuses on overall trends and comparisons.

Exact MIC Values: While the logarithmic scale accurately represents the range, exact MIC values are not the focus, as the goal is to compare effectiveness visually.

Rationale for Visual Encodings

1. Bar Chart: Suitable for categorical comparison, easy to interpret, and facilitates direct comparison between antibiotics.

2. Logarithmic Scale: Essential for representing data spanning multiple orders of magnitude, ensuring small and large values are both visible.

3. Color Coding: Differentiates antibiotics and Gram staining, making the chart visually accessible and informative.

4. Background Shading: Adds an additional layer of information (Gram staining) without cluttering the chart, aiding in comprehensive understanding.

[arizsiddiqui]

Name: Mohd Ariz Siddiqui Roll No: 21F1002275

Design Decisions

I decided to choose a simple bar chart to display the data in common understandable format. Bar charts are one of the most common form of visualizations, thus most people know how to interpret such charts. Also, since the range of values between the bacteria was very large, I decided to normalize the MIC readings with log₁₀. This makes the bars in the chart more prominent, while also providing context to efficacy in comparison to a baseline value(10). Thus it makes it easier to glean important intuitions just by looking at the graphical features of the chart rather than having to deal with actual numerical values. The bacteria are also grouped by their staining patterns to further inform of the user of potential patterns among these groups of bacteria with their response to the given antibiotics. The colors chosen also have enough contrast to make sure no two information points visually merge with each other, leading to accidentally misinformation for the user.

Limitations

While the aim of the chart is to make the MIC data easily accessible, it is limited in its ability to provide accurate numerical information due to the normalization of the MIC data. It could also provide wrong information to people who do not know what data points to look for and their relationships with each other. Also, the positive and negative scales of the chart may confuse people.

Tool Used: MS Excel and Canva

[Fashmina123]

Name: Fashmina Mohamed Aboobucker Roll No.: 21f3003099

To showcase the data, I have created 2 grouped bar charts to visualise the effectiveness of three antibiotics (Penicillin, Streptomycin, and Neomycin) on bacteria with Gram staining positive and Gram staining negative reactions.

Chart Design: Title: Each chart has a distinct title specifying whether the bacteria are Gram-positive or Gram-negative, ensuring that the chart's subject is immediately clear. Axis Labels: The x-axis labels display the different bacteria tested, while the y-axis labels show the MIC values. This helps viewers easily understand which bacteria and antibiotic concentration levels are being compared. Colour Coding: Different colours are provided to indicate different antibiotics. A legend is also provided to refer to the same. Grouped Bars: Each group represents a specific type of bacteria, allowing for a direct comparison of MIC values for each of the antibiotic. The values are also mentioned for easier reference.

Aspects Highlighted: The deisgn emphasizes the comparative effectiveness of different antibiotics against the same bacterium. This is important for understanding which antibiotic is most effective for each specific type of bacteria.

Aspects Downplayed: While the focus is on comparing antibiotics against individual bacteria, the design doesn't highlight the overall pattern of the bacteria, such as general effectiveness of one antibiotic over the others.

Conclusion: The use of bar charts with clear colour coding and comprehensive labelling effectively communicates the comparative effectiveness of different antibiotics on gram positive and gram negative bacteria. The design choice facilitates interpretation of data and ensures readabilitiy and clarity.

[21f2000265-Abel]

Name: Abel George Roll No: 21f2000265

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Visualization Type

For this visualization, I selected a grouped bar chart to display the Minimum Inhibitory Concentration (MIC) of three antibiotics (Penicillin, Streptomycin, and Neomycin) for different bacteria. The grouped bar chart is an effective choice because it enables a straightforward comparison of MIC values between the antibiotics for each bacterium. Grouping the MIC values together for each bacterium allows for a direct visual comparison.

Logarithmic Scale

Given that MIC values can range significantly, from as low as 0.001 to as high as 870, a logarithmic scale was employed for the y-axis. This approach compresses the wide range of values, making it easier to observe differences in MIC values, particularly at lower concentrations which are crucial for evaluating antibiotic efficacy. Color Encoding

Distinct colors are used to differentiate between the three antibiotics:

Penicillin: Light blue
Streptomycin: Light green
Neomycin: Light red

This consistent color scheme helps viewers easily distinguish between the antibiotics. Additionally, the background color indicates the Gram-staining characteristic of each bacterium:

Gram-negative: Light yellow
Gram-positive: Light purple

This use of background color adds another layer of context regarding bacterial properties without cluttering the main data visualization. The overall background of the chart is set to light grey to improve aesthetics and readability. Additional Features

A custom legend is included to clearly denote the color representations for both antibiotics and Gram-staining properties. This aids in ensuring that the chart is self-explanatory.

Limitations

Perceptual Bias

One potential issue with using a bar chart is the perceptual bias it may introduce. Longer bars might be misconstrued as indicating better or more significant results. In this case, longer bars represent higher MIC values, which actually indicate lower antibiotic effectiveness. To address this, it is crucial to clearly label the y-axis and use the chart title and legend to emphasize that lower MIC values denote higher effectiveness.

Lack of Precise Labels

The chart does not include specific MIC values on the bars, requiring viewers to estimate based on the y-axis. This could be a drawback for those who need exact values. The focus of the chart is on illustrating overall trends rather than specific data points, a compromise made to maintain clarity and avoid overcrowding the visualization.

[shelleyiitm]

Name : Shelley R Roll No: 21f1005512

Visualization Type

For this visualization I have used 2D line graph to show the MIC values in log scale for each bacteria for all three antibiotics. This chart also include the data sheet attached to look into the specific values for each antibiotics related MIC at particular level for each bacteria.

General Interpretation:

Based on the given dataset, The following interpretation are obtained, • Penicillin Resistance: The values indicate the concentration required to inhibit the growth of the bacteria. Lower values suggest higher sensitivity to the antibiotic. • Streptomycin and Neomycin Resistance: Similarly, lower values suggest higher sensitivity to these antibiotics. • Gram Staining: This indicates whether the bacteria are Gram-positive or Gram-negative.

Summary

Gram-negative Bacteria: These include Aerobacter aerogenes, Brucella abortus, Escherichia coli, Klebsiella pneumoniae, Mycobacterium tuberculosis, Proteus vulgaris, Pseudomonas aeruginosa, Salmonella (Eberthella) typhosa, and Salmonella schottmuelleri. They generally have higher resistance to Penicillin compared to Gram-positive bacteria. Streptomycin and Neomycin effectiveness varies widely among these bacteria.

Gram-positive Bacteria: These include Brucella anthracis, Diplococcus pneumoniae, Staphylococcus albus, Staphylococcus aureus, Streptococcus fecalis, Streptococcus hemolyticus, and Streptococcus viridans. They are generally more sensitive to Penicillin, with very low values indicating high susceptibility. Streptomycin and Neomycin resistance is variable, with some strains like Diplococcus pneumoniae showing high resistance to Streptomycin.

Chart Design

• Used Line diagram with highlighted points in each of the line corresponding to various antibiotics.
• Used different colors to differentiate Penicillin, Streptomycin and Neomycin
• Include the data sheet for all the bacteria, to have a proper value comparison
• Title, Legend and Axis title are mentioned clearly
• Used Log scale to make the data fit and readable in the graph
• Middle black line is the separation line between the Negative stain bacteria and the positive staining bacteria, the region is highlighted using black arrow .

[NikitaSharma1]

Name: Nikita Sharma Roll Number: 21f1000637

Visualization

Primary Focus

In this visualization, the main goal is to compare how effective three antibiotics—Penicillin, Streptomycin, and Neomycin—are against 16 different bacteria, using their minimum inhibitory concentration (MIC) values. I chose a grouped bar chart because it allows for easy, side-by-side comparisons of the MIC values for each antibiotic across all the bacteria.

Visualization Design

To make the chart clearer, I used distinct colors for each antibiotic: blue for Penicillin, green for Streptomycin, and red for Neomycin. This color coding really helps viewers quickly recognize which antibiotic is which. Plus, the background color is designed to relate to Gram staining, with a violet bluish color for Gram-positive bacteria and a pink reddish color for Gram-negative bacteria. This choice makes it easier for anyone looking at the chart to connect the information to what they might see in a lab setting.

I also organized the bacteria alphabetically, which makes it simpler to find specific ones without having to hunt around. The y-axis is on a logarithmic scale to handle the wide range of MIC values. This helps highlight differences in antibiotic effectiveness, and when you hover over the bars, you can see the exact MIC values, which is great for detailed understanding.

Potentially Obscured Aspect:

However, one thing to note is that while this format emphasizes the comparison of effectiveness, it might downplay some specific MIC values between different antibiotics for individual bacteria. Subtle differences could be missed unless you engage with the hover feature. Overall, the choices I made—using distinct colors, relatable background colors, alphabetical ordering, and a logarithmic scale—come together to create a clear and informative visualization that helps viewers understand antibiotic efficacy against bacterial infections.

[45sajal]

Name - Sajal Dhingra Roll no - 21f2001213

Chart Description and Design Rationale

The chart is titled "Effectiveness on Different Bacteria" and presents the minimum inhibitory concentration (MIC) values of three antibiotics—Penicillin, Streptomycin, and Neomycin—across 16 different bacterial species. The y-axis represents the MIC on a logarithmic scale, which ranges from (10^{-3}) to (10^{3}), ensuring that the wide range of values is clearly visible and comparable. The x-axis lists the bacteria, with an additional distinction between Gram-positive and Gram-negative bacteria using background shading (light blue for Gram-positive and light grey for Gram-negative).

Visual Encodings and Design Decisions

1. Bar Chart Selection: A grouped bar chart was selected to facilitate direct comparison of the three antibiotics' effectiveness on each bacterial species. This visualization type allows viewers to easily compare the MIC values within each bacterial group and across different bacteria.

2. Color Encoding: Colors are used to differentiate between the antibiotics: red for Penicillin, green for Streptomycin, and blue for Neomycin. This clear color distinction helps in quickly identifying and comparing the performance of each antibiotic across different bacteria.

3. Logarithmic Scale: The y-axis uses a logarithmic scale due to the wide range of MIC values. This scaling method is appropriate because it compresses the large range of data into a manageable visual space, while still maintaining the relative differences between values. It effectively highlights differences in antibiotic effectiveness, even when the differences span several orders of magnitude.

4. Background Shading: The bacteria are categorized into Gram-positive and Gram-negative using alternating background colors (light blue and light grey). This additional layer of information helps to quickly identify any patterns or trends related to Gram staining without overcrowding the chart with additional labels or symbols.

5. Legend: A legend is included in the top-right corner of the chart to explain the color coding for the antibiotics and the background shading for Gram staining. This makes the chart self-explanatory and aids in quick reference without needing to cross-check external explanations.

Aspects Highlighted and Downplayed

• Highlighted Aspects: The chart emphasizes the comparative effectiveness of the antibiotics against each bacterial species. By using a grouped bar chart, viewers can easily see which antibiotic requires the lowest concentration to inhibit bacterial growth, indicating higher effectiveness. The logarithmic scale effectively captures the wide range of MIC values, making small and large values distinguishable.

• Downplayed Aspects: While the chart effectively communicates the differences in antibiotic effectiveness, it may obscure finer details such as slight variations in MIC values for bacteria with very low or very high resistance. Additionally, the use of background shading for Gram staining, while useful, might be less immediately noticeable compared to more prominent categorical indicators like distinct symbols or separate sections.

Facilitation of Effective Communication

The design decisions made for this chart are intended to present the data in a clear, concise, and comparative manner. The use of a grouped bar chart allows for straightforward comparisons within and across bacterial groups. The logarithmic scale ensures that all MIC values, regardless of their range, are easily interpretable. Color coding and background shading provide an intuitive understanding of the different antibiotics and bacterial classifications. By organizing the data in this way, the chart effectively communicates the core message of antibiotic effectiveness, while remaining accessible and easy to interpret without extensive prior knowledge or additional explanation.

[visist16]

Name: Visist Tallam Roll No: 21f2001553 Email: 21f200155@ds.study.iitm.ac.in

Title: "MIC Values for Each Antibiotic on Different Bacteria"

Y-axis: Minimum Inhibitory Concentrations (MIC) in µg/mL on a logarithmic scale This scale allows a wide range of MIC values to be displayed clearly, highlighting both small and large values effectively.

X-axis: Bacteria names, sorted by Gram staining (Gram-negative first, followed by Gram-positive).

Legend: Indicates the antibiotics (Penicillin, Streptomycin, and Neomycin) with distinct colors (purple for Penicillin, green for Streptomycin, and yellow for Neomycin).

Data Labels: Each bar is labeled with its exact MIC value, ensuring precise information is easily accessible.

Design Scale: Logarithmic Scale: The logarithmic scale on the y-axis is chosen due to the wide range of MIC values. This scale allows both very small and very large MIC values to be plotted clearly, preventing smaller values from being visually insignificant.

Color Coding: Different colors for each antibiotic (Penicillin, Streptomycin, and Neomycin) facilitate easy comparison across the antibiotics for each bacterium.

Sorting by Gram Staining: Sorting bacteria by their Gram staining results (Gram-negative first, followed by Gram-positive) allows for easy comparison within these groups, highlighting patterns in antibiotic effectiveness related to Gram staining.

Info Communication: This design effectively communicates the relative effectiveness of different antibiotics against various bacteria, emphasizing patterns based on Gram staining. The logarithmic scale ensures that small but significant MIC values are visible, while larger values are not compressed. This approach provides a clear visual distinction between the performance of antibiotics on Gram-positive and Gram-negative bacteria.

Potential Limitations: While the logarithmic scale is effective for displaying a wide range of data, it may obscure the exact differences between values that are close together. Additionally, the reliance on color coding requires that the chart be printed or viewed in color for full effectiveness. However, the inclusion of data labels mitigates this issue by providing the exact values directly on the chart.

This chart allows for a comprehensive understanding of the antibiotic effectiveness across different bacteria, facilitating quick identification of which antibiotics are more effective against specific bacterial infections.