Graded Assignment -3 (Jan Term 2023):- 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

[cheriangeorge]

Design decisions

A conscious design decision was made to represent more effective antibiotics with smaller drops as this is closest to reality. Initial explorations with quite a few number transformations to visually encode 'larger is better' were unsatisfactory. This visualisation does not represent precise concentrations (hard to show the difference between 0.005 and 0.001) and the exact numerical values have been deliberately avoided in the visualisation.

Visual Encoding, Colour and Scale

The light-blue circle represents a petri-dish with the bacteria (10,00,000 units of area) and the dark-blue drop represents the antibiotic. The size of the drop represents the minimum concentration of antibiotic required to prevent bacterial growth in vitro. The largest drop represents 8,70,000 units of area and the smallest drop represents 1 unit of area.

The smaller the drop size the more effective the antibiotic is against that specific bacteria. The legend provided shows the concentration corresponding to each drop size.

The reaction of bacteria to covariate gram staining has been represented by pink (negative) and violet (positive) circles. The positive staining bacteria and negative staining bacteria have been bunched separately.

Icons:

• Petri Dish by Tini Sumiarsih from Noun Project
• drop by HideMaru from Noun Project

  Typography:

• Ubuntu (bold/regular/italic) Typeface

  Tools:

• Krita

[imaadansari1]

Imaad Ansari - 21f1004808

Design Decisions

• Here a clustered column chart is used to display the minimum inhibitory concentration (MIC) of Penicillin, Streptomycin and Neomycin respectively.
• The data is first divided into Positive and Negative Gram Staining first.
• This division makes it easier to represent the Gram Staining on the chart.
• Then the data is sorted by the average of MIC of all three antibiotics from the smallest to the largest.
• Sorting makes the interpretation easier as the bacteria on which the MIC score was low comes first.

Scale, Color and Visual Encoding

• The scale use is a Logarithmic Scale instead of a linear one, since the data has a wide range of values.
• The colors used for the antibiotics are contrasting to each other while still maintaining a harmony, and go easy on the eyes.
• Colors used for Gram staining positive and negative are violet and pink respectively, because bacteria stained violet are positive and pink are negative.
• Visual encodings are kept simple so as to keep the chart less cluttered, neat and easy to read.

Tools

• MS Excel
• Adobe Illustrator

[Chaitanya-Kumaria]

Name : Chaitanya Kumaria

Roll No: 21f1000479

Aim Of The Visualization

• To highlight differences in the MIC (minimum inhibitory concentration) of different types of Antibacteria's on different strains of Bacteria.
• Theoretically, MIC ( minimum inhibitory concentration) is the lowest concentration of a chemical, usually a drug, which prevents a bacterium's or bacteria's visible growth. MIC depends on the microorganism, the affected human being, and the antibiotic itself.
• So, in simple words, the lower the MIC, the more effective the anti-bacteria

  Design Decision

• My main aim is to highlight the differences in the efficacy of antibacterial on bacteria. Also in the data, the bacteria are divided into two groups based on Gram Staining (Positive and Negative),
• So first clustered bacteria on the basis of their Gram-Staining value and then further combined them on the antibacterial used.
• Scales have been left unchanged in order to highlight the magnitude of difference in the effectiveness of a drug.

  Scale, Visual Encoding, and color

• As mentioned earlier, scales have been used as it is to highlight the magnitude of the difference of a drug vis-à-vis others
• Visual Encoding has been set as a comparison between the positive and the negative strained bacteria. Also combining has been done based on Antibacterial and not bacteria, to highlight the difference between them
• Background color has been set to black and bars do not have any fill to highlight the length of the bars in a more prominent manner, color on the bars represent the bacteria.

Tools

• Microsoft Excel
• Python (Plotly Library)
• Figma

[Supe-Tushar]

Name: Tushar Supe Roll: 21F1003637

Design Decisions

• The given data consists of MIC (Minimum Inhibitory Concentration) for three anti-bacteria (Penicillin, Streptomycin and, Neomycin) which were tested on 16 types of bacteria.
• My aim for the data visualization is to compare effect of each anti-bacteria on different types of bacteria. The data is splitted into 2 sets based on Gram-positive and Gram-negative.
• Then the mic values are converted to log (base 10) values. The reason for doing this is that the values are ranging from 0.001 to 870. This is a wide range and only 16 data records are available. So comparing effect of anti-bacteria will be difficult without scaling because all small values will be close to zero and we won't be able to visualize those properly.
• The visualization is done with 6 radial bar chart, where each chart is for one of the anti-bacteria and postive/negative gram staining.
• The data values are sorted alphabetically based on bacteria type. This is done so that while comparing charts, its easier for the user to look at the values if each chart is having same sequence of labels.
• The radial charts are not available in MS Excel so for that, the donut chart is plotted and is then modified into radial chart.
• The visualization focuses on the comparison of the effect of a anti-bacteria on different bacteria (positive or negative but not both together).
• So, it does not include comparison between different anti-bacteria themselves (for knowing which is stronger).

Scale, Visual Encoding, and Color

• Logarithmic scale is used due to huge range of data values.
• Visual Encoding is a comparison.
• Each bacteria is assigned a color which is common among all radial charts. The colors are similar to rainbow but intensity is reduced slightly to make them aesthetically pleasing.
• The background is dark black and grey so that the colors and text is properly visible.
• The text size in charts is larger so that when all charts are combined, the text is still readable.

Tools used

• Microsoft Excel for radial charts
• Python with pandas for data manipulation
• Figma for extra visual features.

[kun101]

Kunal Chaturvedi 21f1003353 Flourish Link : https://public.flourish.studio/visualisation/12908416/

Purpose of the chart The given data conveys how certain medicines worked effectively to treat ailments caused by certain bacteria after World War 2. As mentioned, these were called Wonder Drugs and worked very well against the above mentioned bacteria. The primary objective of the visualization is to present to the user a quick overview where he/she can quickly determine which drug works better against a certain bacteria.

Data Processing I have normalized the MIC values using the median (1) so that the smaller values become larger and the larger values become smaller, as the goal of the visualization is to show effectiveness of the medicines and the really small values, like 0.001 can be converted to larger values. I then proceed to plot these in a donut chart as mentioned below using Flourish, as it is easy to plot and edit the visualizations on it.

Design Decision I have used a grid of donut charts to represent this information as it is easier to read for the user. I considered using a sunburst chart for this as this is a hierarchical data, but the leaves of the sunburst chart start getting crowded around the same level and it gets difficult to read unless it is an interactive data visualization.

Further I have explained all the metrics and the title/description of the visualization clearly along with footnotes to the reader for better understanding.

I have added the positive and negative Gram Straining readings along with the names of the bacteria to make a distinction while reading the chart itself.

Lastly, a legend has been added to identify the medicines by colour clearly.

Shortcomings My chart doesn't clearly suggest the concentration of the medicine required to treat the ailment but only presents the most effective medicines, showing which cure is the best.

Tools Used Google Sheets for Data Processing Flourish for Data Visualization

[Chirag-Goel-17]

Chirag Goel 21f2000540

Design Decision

• To analyse gram strain modified Gantt Chart is used with one axis used to divide chart int 2 parts positive and negative strain.
• To highlight differences in MIC(Minimum Inhibitory Concentration) of different antibiotics, a bar's are used.
• Division of chart into 2 parts is done to highlight the difference in MIC of different antibiotics.
• Data is sorted in descending order of bacteria name to highlight the difference in MIC of different antibiotics.

Scale, Color and Visual Encoding

• The scale of the chart is logarithmic scale because difference in MIC of different antibiotics is very high.
• The color of the chart is used to highlight the difference in MIC of different antibiotics.
• The visual encoding is used to highlight the difference in MIC of different antibiotics.
• positive strain is represented by Dark blue color and negative strain is represented by red color.

Tools used

• Microsoft Excel
• Figma

[aryab-sudo]

Personal Details

Name: Arya Bhattacharyya Roll Number: 21f2000436

Final Visualization (Submitted for Grading)

Please note: For some reason the GitHub upload looks very hazy. However, on clicking on the image, the image opens on a separate tab and looks clearer. My earnest request would be to kindly look at the visualization separately by clicking on the image. Thank You!

Audience And Purpose

The main purpose of this visualization is to inform the common citizen about the efficacies of three common drugs available in the market. The efficacy is with regards to the bacteria under consideration and the corresponding MIC values of the different drugs.

Design Decisions

1. In common thought process, usually we associate the left side to be the negative side and the right side to be the positive side. The visualization is in line with the same by having gram negative bacteria on the left of the Gram-positive bacteria.
2. Given that we know that the strain of the Gram-positive bacteria is dark blue/violet, the colour of the container rectangle corresponding to the Gram-positive bacteria is violet/dark blue in colour. Since the strain of the Gram-negative bacteria are any colour apart from the ones that belong to gram positive, I chose red colour to contrast it better from the Gram-positive bacteria.
3. Regarding the actual plot, I chose a scatter plot because I felt it was the most appropriate for this kind of data wherein, we need to compare the efficacy of each drug for different bacteria. Column Charts were also a viable option but, in my opinion, they increase the clutter a bit especially when across different bacteria the order of efficacy could change, and average efficacy might be difficult to understand/visualize. Line Chart helps to fully visualize the changing efficacies across different bacteria strains, but when explicitly connecting dots (on the main chart) across the different bacteria like the following chart:

could lead to misrepresentation on what the connecting lines across dots could mean, because line charts like these are usually used for time series and the connecting lines imply intermediate values, which is not the case here. (PS: This chart is only used to explain the design decision and is not the final chart. Only the first chart is to be considered for final grading. Thank You!)

4. Since this chart is meant for the common citizen, a separate "Did You Know" blob is added with the usual bulb symbol to help the possibly unaware audience that the lesser value of MIC is considered better and more efficient. This reduces confusion from the common feeling of "more the better" or "bigger the better" which common citizens are exposed to in most of everyday life.
5. Since this visualization is not designed to act as a manual for actual doctors/medical practitioners who want to prescribe medicines, it doesn't detail the exact value of the MIC corresponding to each data point. It simply plots the values against the axis.
6. The provided excel sheet was reorganized to have Gram-negative bacteria first and then the Gram-positive bacteria. This helps me to club them according to their strain and also in such a way that gram negative is on the left of the gram positive bacteria.
7. The grid lines are kept intact so that the audience can quickly get a rough idea of the MIC value of the different drugs corresponding to each of the different bacteria.
8. The visual encoding for the different drugs is assigned in a way that the audience can easily differentiate between the various dots corresponding to the different drugs.
9. The size of the dots is kept as small as possible to avoid overlaps unless they have the same value. In the case of an unavoidable overlap because of space constraints, the different dots are labelled with arrows to indicate the specific drugs that they correspond to.
10. The scale used for this visualization is the log scale (with some intermediate helper values) because of wide range of the data at hand and the possible loss of discernment when using the linear scale like in the following chart: (PS: This chart is only used to explain the design decision and is not the final chart. Only the first chart is to be considered for final grading. Thank You!)

Things that my visualization misses

1. As mentioned earlier, the exact MIC value is not mentioned in this static rendering of the chart. (However, the same is available on the flourish link, on the hovering of the mouse.
2. There could be more factors to consider while choosing a particular drug, like its price, side effects, specific allergies of different people, etc. This visualization is not meant to be a prescribing tool. And therefore, it misses out on this information too and only focusses on the MIC values as the criteria of effectiveness.

Tools used

1. Flourish for the main plot (Link to the main plot on flourish: https://public.flourish.studio/visualisation/12930156/)
2. Figma for additional touches of design.

[puvvadasaikiran]

Puvvada Saikiran (21f1005095)

Data Specifications/Overview:

• provided the data corresponding to dosage details of antibiotics to fight off bacteria infection
• gram stain result is provided, helps to classify bacteria
• MIC (minimum inhibitory concentration) is provided w.r.t each bacterial infection
• MIC (value is inversely proportional to effectiveness)

Objective

• Primary Objective is to visualize most effective antibiotic for specific bacteria

Data Decisions

• Given the Scale of MIC is larger and might affect the objective, there came the need to normalize the scale to visualize it data better
• Relative Dosage Effectiveness is derived quantity from raw data to achieve better metrics for visualization
• A conscious decision taken to avoid plotting MIC as the larger numbers might hinder communicating real representation of data
• Sorting of data is done to group bacterial infections by their gram stain result

Rationale behind design decisions

• usage of Stacked chart to provide visual comparison of effectiveness of respective anti biotic
• used faded/neutral colors as human bias might take green/red glow as positive/danger
• Scale of Relative Dosage Effectiveness is percentage
• info assist at the top is used to make user familiarize with visual template
• shaded regions to distinguish between different types of bacterial infections based on gram stain result
• Appropriate Labels and scales provided for reference

Tools Used

• Google Sheets
• Figma

[Saha-Sumistha]

Name - Sumistha Saha

Roll No - 21F1000276

Visualization Link - Click Here

Design Decisions

During the post-World War II period, antibiotics were considered "wonder drugs".Here this given data consists of which drug worked most effectively for which bacterial infection. On 16 types of bacteria, the three most popular antibiotics(Penicilin, Streptomycin, Neomycin) were evaluated.

• The purpose of the data visualization is to assess the impact of each anti-biotic on different types of bacteria.The visualization illustrates the effect of a specific anti-biotic against different types of bacteria (gram positive or gram negative but not both at the same time). The design of this chart and its color palette were carefully selected to ensure that anyone can understand it with minimal knowledge.
• The visualization is done with Grid Stacked Bar chart, where each chart is for different antibiotics with their minimum inhibitory concentration(MIC) value which represents the concentration of antibiotic required to prevent growth in vitro.
• The data values are sorted based on their value. By using the same sequence of labels on all charts, the user will be able to compare the values more easily.

Scale, Visual Encoding, and Color

• Although this graph has a wide range of values but still we are using Linear scale to keep it's simplicity.
• The background is white here which makes it aesthetically pleasing.
• Each anti-biotic which is common for all bacteria is assigned a different color with good contrast.
• Every color code for Gram staining positive and negative are same so that it will be easy to understand when the user will apply the filter.
• Every data labels are on an axis with bold weight and axis points are with light weight to create a visual attraction on the data points.

Improvement Point :

Due to the wide range of data values if we omitted the data labels then the visualization would have conveyed the wrong message for the lower-position bacteria

Tools Used

• Google Excel
• Flourish

[Laha-Dibyendu]

Name : Dibyendu Laha

Roll : 21F1006498

Link to the visualization :- Click Here

Design Decisions

The given data consists of which wonder drug worked most effectively against bacterial infection. On 16 types of bacteria, the three most popular antibiotics(Penicilin, Streptomycin, Neomycin) were evaluated.

• The purpose of the data visualization is to show how each drug contributes to preventing bacterial infection.
• The design of this chart is carefully selected as a column stacked chart which is easy to understand and interpret for any person of any background. The X-axis represents the name of the bacteria and Y-axis represents the percentage value.
• The data values are shown in two visualization side by side one is for gram-positive bacteria and the other one is for gram-negative.
• The colours chosen for representing Penicilin, Streptomycin, and Neomycin are in contrast with one another so that the drugs can be easily identified.
• Every data label are given white colour so that it can be easily seen and the axes labels are also given to convey the visualization properly.

Aspects of the data which is missing

• My visualization is not representing the actual data, so if anyone is eager to know the actual data he/she will not be able to get it.

Tools Used

• Flourish

[midhuncrajan]

Name - Midhun Rajan Roll No - 21F1006973 Visualization link: https://public.flourish.studio/visualisation/12941428/

Design and data preprocessing A conscious design decision was made to represent more effective antibiotics with larger the better pattern. But the data is in the form of lesser the better format. I tried few varieties of visualization without preprocessing the data. But result was not that much good as expected. I have taken the inverse of all MIC data, then normalized it by diving with maximum value of corresponding row. I have used excel to do the transformations.

I have decided to use stacked bar chart to do the visualization so that a viewer can easily understand the effectiveness of antibiotics very quickly in a larger the better manner. I selected one of the color palette from flourish and proceed with it. I have decided to create a interactive visualization to distinguish between gram positive and gram negative category to avoid a congested feeling in the visualization.

Legends and annotations I have given all the metrics in the the visualization and added footnotes also to avoid any confusion. Legend has been added for antibiotics with color to identify effectively. Bacterial names are included in the Y axis. X axis is using to denote the effectiveness. Filter option has been added to switch between positive and negative gram stains.

Shortcomings MIC values are not showing in the visualization as I transformed it to visualize in larger the better format. Can't easily distinguish the gram negative and positives without filtering

Tools used MS Excel- Preprocessing Flourish studio - Visualization

[21f1004861-HarshithaSrikanth]

Name:Harshitha Srikanth Roll number:21f1004861

Link to flourish visualization:https://public.flourish.studio/visualisation/12942153/

Design Decisions:

• This visualization helps understand the effect of the three drugs under consideration on 16 different types of bacteria.
• A line and area chart has been used and three separate graphs for each drug is used.
• Negative and positive gram bacteria are separately visualized for better clarity
• The visualization is kept extremely simple and interpretable with clear annotation of values
• As the scale is large two Y-axis of different scales have been used as shown to accommodate the large range.
• The colour palette is extremely simple and makes sure to not deviate attention for the actual story the visualization is trying to tell.

Scale, Visual Encoding, Colour:

• Each bacteria is assigned one colour to retain clarity.
• Background is off-white so that focus is not deviated from the actual visualization and there is clarity in the representation.
• Multiple Y-axis with two different scales has been used to accommodate the large range of the data.
• The complete range of MIC values has been captured in the visualization.
• Simple grid is used to enable effective value-reading.
• Visual encodings are minimal so that its easy to understand and interpret inferences.

Shortcomings:

• The use of two y-axis scales may lead to some confusions.
• Multiple graphs for each drug has been plotted making comparison slightly difficult.

Tools used: Flourish

[ShagunDwivedi]

Effective Visualization of Data

Shagun Dwivedi 21F1001731

Wonder Drugs (antibiotics) were easy cures for ailments considered ailments during the Second World War. The visualisation is primarily meant to find the most effective antibiotic out of the three wonder drugs, Penicillin, Streptomycin, and Neomycin on different bacterial infections. Moreover, these bacteria can be categorised into Gram-Positive (purple/blue stained) or Gram-Negative (pink stained), based on their reaction to Gram staining.

Description and Rationale

• Data Transformation: The data has been primarily divided into the two categories of the 'Gram Staining' variable for better proximity in the visualisation and then sorted alphabetically with respect to the 'Bacteria' variable for efficient search.

• Basic Visualisation: The clustered bar chart, divided vertically into two halves for Gram-Positive and Gram-Negative bacteria, compares the MIC values of the three antibiotics on a given bacteria one under the other (due to Principle of Proximity). The antibiotics have been color-coded consistently throughout the visualisation (to make use of the Principle of Similarity) and a legend has been provided for reference at the top. Similarly, colored pictorials have been added next to the Gram-Stain Labels on Y-Axis for reference.

• Smallest/Best MIC Value: The MIC value isn't just a comparison metric but also provides the required concentration of the antibiotic, which might come in handy to the person administering the drug. Hence, the best MIC value labels have been highlighted for easy detection, they have also been placed closer to the Y-axis for the same reason.

• X-Axis Scale: Since most of the lowest MIC values were in the range of 0.001 to 0.1, the range on the X-axis has been kept pretty minute. Larger bars were truncated, and labeled at the right end. If one bacteria cluster has multiple bars exceeding the 1.6 limit, they have been labeled left to right in increasing order of their value (if the person administering the drug does not have the drug with the lowest MIC, they could go with the second lowest, the one adjacently right to the lowest value (detected next).

Downplayed Elements

• Magnitude of Difference between the MIC values: The values 2 and 850 are labeled right next to each other. This has been allowed as our focus is to find the lowest MIC value, and the extreme imbalance amplifies effectiveness of the best antibiotic, rendering the other two irrelevant.
• No Mention of Best MIC value Criterion: The visualisation is based on the assumption that one would understand just by the highlighted labels that the lowest MIC is the best, however that may not be true.

  Thank You.

[yatinchug01]

Name: Yatin Chug Roll no: 21f1007066

Design Decisions

• The main purpose of this visualization is to inform the common citizen about the efficacies of three common drugs available in the market. The efficacy is with regards to the bacteria under consideration and the corresponding MIC values of the different drugs.My aim for the data visualization is to compare effect of each anti-bacteria on different types of bacteria.
• The data is splitted into 2 sets based on Gram-positive and Gram-negativeThe data values are sorted alphabetically based on bacteria type.
• This is done so that while comparing charts, its easier for the user to look at the values if each chart is having same sequence of labels
• .Each column is each department(bacteria) represented by same color and it made easy to uderstand the proportion of each antibiotics by its own scale
• .The scale use is a Logarithmic Scale instead of a linear one, since the data has a wide range of values.
• Visual encodings are kept simple so as to keep the chart less cluttered, neat and easy to read.

[jemma-mg]

Name: Jemma Mariya George Roll no: 21f1001937

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Visual Encoding, Colour and Scale of Design

• Minimum Inhibitory Concentration (MIC) is the concentration of antibiotic required to prevent growth in vitro and the Lower the MIC more effective the antibiotic is. This concentration of antibiotic is visually encoded using the opacity of the light green colour.
• Most effective antibiotic and its minimum concentration required to treat the bacterial infection is highlighted with a teal border circle, higher font size and weight for denoting the precise number which facilitates easier comparison.

  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.

• As per the statement Gram Positive bacteria are given a text colour of blue-violet and Gram Negative bacteria are denoted with magenta colour.
• The Data is sorted in alphabetical order of bacterial names

Legends and annotations:

Legends and annotations have been provided to facilitate effective communication of the given data.

Shortcomings:

In this visualization, only 3 levels of opacity have been defined so that it is easily distinguishable. But it does not precisely represent concentrations as per the color opacity level (eg: 0.001*100% = 0.1% opacity).

Tools used:

Figma, Excel

[Devjyoti-Chakrabarti]

Roll Number: 21f1006240 Name: Devjyoti Chakrabarti

Clear thinking made visible. At the outset, it is essential to recognise that this is a lot of data, while there are only 16 records, each record has minimum inhibitory concentration (MIC) values for 3 antibiotics and information about gram staining. Thus effective communication of this data required some thought. The MIC is a measure of the effectiveness of a drug where the lower the MIC value, the lesser the amount of drug required to inhibit the growth of the organism, drugs with lower MIC scores are more effective antimicrobial agents. So I created two more columns in the given excel sheet, one column containing the lowest MIC values among the three antibiotics and another having the name of the antibiotic with the least MIC.

Instead of creating multiple charts, I wanted to create a single chart which housed all this information neatly. What I wanted to convey in my visualization was that these antibiotics have different gram staining on different bacteria and how effective these antibiotics are against these microbes (as reflected by the MIC values). Using the updated data, I proceeded with plotting a bubble chart, the choice of this type of chart will soon become clear. The antibiotics are on the Y-axis and the bacteria are on the X-axis. A dot represents which antibiotic is most effective against a particular type of bacteria. The colour of the dot varies according to whether gram staining is positive or negative. Additionally, albeit an antibiotic might be most effective among the three against a specific bacteria, the MIC value shows how much of the antibiotic is required in inhibiting the bacteria. So the size of the dots varies depending on the MIC value. For instance, the very small dot against penicillin and brucella anthracis, reflects that a very small amount of penicillin (just 0.001 μg/mL) is required in stopping its growth. Hence why the choice of bubble chart in showing this multi-dimensional data.

(Note: Please click the below link to view the complete visualization where hovering over each dot shows information about the differing MIC values which is not visible in the above image. https://public.flourish.studio/visualisation/12934357/)

Moreover, the choice of the title and subtitle adequately conveys the message and goal of the visualization and what each dot represents. And the legend on the top right corner helps to identify the colour coding of the dots. The footer at the bottom defines MIC for viewers possibly not familiar with such terminology. Thus, through pre-processing of data, the choice of chart type and heuristics about titles, headers and footers, my visualization manages to make visible the necessary information effectively that I had intended to convey.

Tools Used: Flourish Studio

[ayushpatidar14]

Name: Ayush Patidar
Roll No: 21f1004981

---

Purpose:

Idea behind creating the visualization is to compare and highlight the performance/effectiveness of the three antibiotics drugs against different bacteria. It makes it easier to select most effective antibiotic to fight any particular bacteria.

Design decisions and rationale behind it:

• Bar chart is used to visualize the data. In order to highlight the effectiveness, we are required to highlight the difference in performance of each drug on each bacteria which could be done using bar chart.
• Log scale used on x-axis. Since, values of MIC range from 0.001 to 870. Log scale lets us plot drastically different values like 0.001 and 850 on a single axis.
• Color coding was kept simple. All the bars are colored dark blue except some. Bars corresponding to most effective antibiotic against each bacteria are highlighted using bright yellow color.
• Data was sorted on gram staining. This helped in grouping all the negative gram staining bacteria together and all the positives ones together. Within each positive/negative class, bacteria names follow natural alphabetical ordering.
• Label for gram staining is put along with the bacteria names on the y-axis. This makes it easy to find groups of positive and negative gram staining bacteria without looking anywhere else.
• Both the axes are labelled accordingly. Title clearly mentions the purpose of the visualization.

Shortcomings:

• Since, we made a design decision to use log scale on x-axis, it came with its trade-offs. One can easily tell which drug is most effective but the margin of difference between effectiveness of two drugs could not be grasped just by visuals.

[rajanways]

Name: Rajan Kumar Roll Number: 21f1006139

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                          ****Butin's Antibiotic Data** **Final Data Visualisation****

Design Decision AND Scale, Colour and Visual Encoding

The data presented evaluates the effectiveness of three popular antibiotics - Penicillin, Streptomycin, and Neomycin - against 16 types of bacteria to determine which wonder drug works best against bacterial infection. The purpose of the visualization is to demonstrate the contribution of each drug to the prevention of bacterial infection. A Bar Chart was carefully selected as the design for its ease of interpretation by individuals of any background. The Y-axis displays the name of the bacteria while the X-axis displays the MIC value. The data values are presented in two visualizations, one for gram-positive bacteria and the other for gram-negative. To distinguish between the drugs, contrasting colors were chosen for Penicillin, Streptomycin, and Neomycin. White-colored data labels were used to ensure ease of readability, and axes labels were included to properly convey the visualization.

Legends and annotations: To enable clear communication of the presented data, explanatory notes and labels have been included.

Tools used Microsoft Excel

F.N.:- The Minimum Inhibitory Concentration (MIC) refers to the amount of antibiotic necessary to inhibit in vitro growth, and the effectiveness of the antibiotic increases as the MIC decreases.

[mukeshonlinesiitm]

Name: Mukesh Kumar Singh Roll no: 21f1000350

Design Decisions:

The data set reveals information about MIC (Minimum Inhibitory Concentration) of three antibiotics against 16 bacterias. As per rule the lower the value of MIC the more effective a particular antibiotic is considered. While doing the analysis of data I feel that ratio scale of MIC is vary from 0.001 to 850 in different antibiotics against bacteria. Plotting any graph on such data set hide some of antibiotics value as values are very low but in reality these values needs to show in graph as lower the MIC more effective bacteria. So I derived MIC value into LOG so that it reduce to lower values but as log make some value to negative and showing negative and positive ration is not effective in graph. Then I used Exponential function on top of log as Exponential always return +ve value and it scale the entire data between 0.04 to 19.

On derived data, I plotted 2d cluster bar plot make X-axis as Bacteria and Y-axis the derived value and cluster for antibiotic. In Cluster for each antibiotic used hollow block with different colour. Purpose of hollow block is that I can fill colour to make which antibiotic is more effective against specified bacteria. I used red colour to fill as it make reader to understand faster. To distinguished the Gram staining I used different colour based on actual Gram-Stain colour. For Gram Positive “crystal violet” colour and Gram Negative “pink” colour is used.

Addition to above also reader can notice that the Penicillin is most effective against Gram Positive 4 out of 7 that means around 57% effective. Whereas Penicillin is less effective against Gram Negative.

Neomycin is more effective in general 11 out of 16 that means around 69% effective and Streptomycin is less effective. Above graph is just to prove above statement only.

Legends and annotations: All Legends and annotations are added to make chart self-readable.

Tools used Microsoft Excel and manually some annotation used in excel to make chart effective.

Downplayed: As i used the derivied value to display the chart which make diffculate readed to know the actual value of MIC.

[SamandeepSinghTomar]

Name: Samandeep Singh Tomar
Roll No: 21f1001112

Design decisions:

Visualization type: I chose a percentage stacked bar chart because it effectively shows the relative effectiveness of each antibiotic for each bacteria. The stacked bars allow for easy comparison of the antibiotic effectiveness across bacteria, while the percentage scale facilitates comparison of the relative contribution of each antibiotic to the overall effectiveness.

Size: I opted for a medium-sized chart to ensure that all the data is legible and easy to compare.

Scale: The x-axis represents the bacteria, sorted alphabetically, and the y-axis represents the percentage effectiveness of the antibiotics. The percentage scale facilitates comparison between antibiotics and bacteria.

Effectiveness of antibiotics for bacterial infections:

The percentage stacked bar chart visualizes the relative effectiveness of three antibiotics – Penicillin, Streptomycin, and Neomycin – on 16 different bacterial infections. The stacked bars are sorted alphabetically by bacteria name on the x-axis and show the percentage effectiveness of each antibiotic on the y-axis.

In conclusion, the percentage stacked bar chart is an effective way to visualize the relative effectiveness of antibiotics on different bacterial infections. It allows for easy comparison of the effectiveness of each antibiotic across all bacteria and can help in identifying the most effective antibiotic for each bacterial infection. The use of color coding, percentage scale, and sorting by bacteria name facilitates easy interpretation and comparison of the data.

Tools Used: Flourish

[deysanjeeb]

Name: Sanjeeb Dey Roll Number: 21f1002729 Visualization can be seen here

Design Decisions: Using a stacked bar chart we can see which antibiotic is most effective for every bacterial infection by utilizing MIC. The bar chart is arranged in descending order according to the effectiveness. I have utilized vivid colors to make it easy to look at the bars.

Tools used: Google Sheets and Flourish

[royjohn15]

Name: Roy John

Roll number: 21f1007054

Design Decisions

I went with a radial tree as it is a compact way of visualizing our data. It is also aesthetically pleasing. It effectively communicates the intention of the dataset. The colors used in the chart clearly distinguish between the negative and positive gram stains. The bars that are colored red are negatively stained bacteria and that are colored blue are positively colored. For each antibiotic a separate radial tree ensures a better understanding of the data. The length of the bars encodes the minimum inhibitory concentration (MIC). The hierarchy of the graph is: Gram Staining -> Bacteria.

Shortcomings

The bars for low values of MIC are not visible. It is hard to compare between the low values.

Tools used

Flourish Studio and Photoshop

[deekshaChutani]

Deeksha Chutani: 21F1002583

Design Decisions

• A radial chart has been employed to analyze and compare the minimum inhibitory concentrations (MICs) of multiple antibiotics.
• The chart has been designed to differentiate between three main categories of antibiotics, namely Penicillin, Neomycin, and Streptomycin, by using color coding.
• Furthermore, to indicate the existence of two types of Gram Staining, wherein bacteria stained dark blue/violet are considered Gram-positive, the chart has been labeled using Dark Blue for Gram-positive stainers and Black for Gram-negative stainers.
• To avoid any potential confusion that may arise due to the presentation of multiple charts, the use of a single radial chart has been preferred.
• Radial charts can be an efficient tool to present complex data with cyclical patterns or multiple categories. In this case, the use of color to differentiate between antibiotic categories and bacteria types aids in facilitating comprehension of the data presented.

Visual Encoding, Colour and Scale

• Bar charts have been employed on top of the radial chart for presenting the MIC values.
• The MIC values have been directly for the data to be more familiar to the viewers.
• The legend provided shows the color corresponding to each type.
• The Background colour has been kept white for simplicity.

Shortcomings

I haven't effectively presented labels and can certainly improve upon them.

Tools Used

• Microsoft Excel
• Flourish Studio
• Figma

[kumar-cmd]

Kumar Chandan: 21F1004845

Mathematics of Visualization At first i thought to create some bar chart or pie chart to show the relative effectiveness of antibiotics but again thought to analyse it mathematically before going to design. Then i thought that how many attribute and dimension we can extract from this table using statistical analysis.

So I found few things:

• Three attribute for antibiotics for each bacteria.
• Gram Staining test for each bacteria
• Relative effectiveness of antibiotics : Again here we can think two way.
• 1. Relative powerful antibiotic in same bacteria
• 2. powerful antibiotic in among all bacteria
• More powerful bacteria

Design Decisions:

Now we can see that we have almost 5 dimension for this visualisation . Once i got the idea that how many things i need to actually convey through pictorial way, then i started thinking about shape , color, size to display all things visually and better way. After going multiple shape i chose the multilayered donut chart.

Since the design i thought mentally was not available at my known visual tools. So i decided to make it using javascript over web from core level myself and here i chose D3.JS to design the shape.

Scale, Visual Encoding, Colour:

Scale : Since data is distributed exponentially , So i need to scale it before making smooth visual distributions . I chose the to scale at logarithmic scale(log base 2) . I used Pandas to scaling and analysis the data which is shown below

Details about Visual Encoding and Colour :

• inner circle : represent the gram staining test for each bacteria
• inner petal : represent the three bacteria with different color
• outer petal : here i used gradient concept to show the strength of antibiotic. More dark more strength
• heat map : i used concept of heat map to show the antibiotic strength. Here it can show the relative strength for a single bacteria as well as for all bacterias too.
• size of donut : using size of donut i try to convey that the bigger the size bigger strength of bacteria

Tools used: I didn't use any pre existing tools cause it was not able to satisfy my requirements (based on the tools i am familiar with ).So i chose the make using basic level. For visual : JavaScript , D3.JS, HTML, SVG For data analysis : Colab, pandas, numpy

[21f1003953]

Aim of the Visualization:

• To clearly convey the impact of three medications on 16 different bacterial strains.
• To investigate the connection between the covariate of Gram staining and the efficiency of the antibiotics.

Design Decision:

• A stacked bar chart is used to illustrate the data, making it simple to compare the efficacy of the various antibiotics.
• Red, green, and blue are used in the graphic to distinguish between the three antibiotics.
• To clearly explain the colour scheme that was utilised in the graphic, a legend was included.

Scale, Visual Encoding, and Color:

• The effectiveness of the antibiotics, which is displayed on the y-axis of the chart, sets the scale.
• The height of the bars, which represents the efficiency of the antibiotics against various microorganisms, is the visual decoding employed.
• Red, green, and blue are the chosen colours for the chart, and each hue stands for a particular antibiotic. This makes the chart easier to read and aids in differentiating the various antibiotics.

Tools Used:

• Microsoft Excel
• Python
• matplotlib

[Ajay-Kumar-1998]

Ajay Kumar- 21F1000200

Design Decisions

• The Main moto of the design was to show the relative strength of 3 Antibiotics of 16 different types of bacteria.
• Each Pie chart shows which bacteria takes more amount of Antibiotics to get treated.

Visual Encoding, Colour and Scale

• The MIC values have not been scaled.
• Colors encoded have no specific purpose, as they have nothing to do with bacteria.

Shortcomings

• I was not able to display all the 16 bacteria due to space constraints and also due to their low values, Exploring new graphs which can perfectly depict that kind of data.

Tools Used

• Google Sheets
• Inkscape

[kevin-IITM]

Kevin Varghese - 21f1004582

Design Decisions Represent the data in a hierarchal structure splitting based on the antibiotic used to emphasize the strong influence of penicillin.

Visual Encoding, Colour and Scale

• Bright colors such as pink, blue and purple are used to distinguish
• The scale is kept the same as in the dataset to show the significant numbers projected by penicillin

Tools used Google Sheets Google Colab Flourish Studio

[shaifalivashistha]

Name : Shaifali Vashistha Roll No. : 21f1003257 Link to Vizualizarion: Minimum Inhibitory Concentration (MIC) of Antibiotics on Bacterial Strains by Gram Staining

Design Decision:

Based on the dataset, I designed a grouped bar chart to effectively communicate the minimum inhibitory concentration (MIC) of three popular antibiotics (Penicillin, Streptomycin, and Neomycin) on 16 different bacterial strains, grouped by their Antibiotics used on them. The chart is titled "Minimum Inhibitory Concentration (MIC) of Antibiotics on Bacterial Strains by Gram Staining." The choice of a grouped bar chart is appropriate because it allows the comparison of the MIC values of the three antibiotics on each bacterial strain, while also providing an easy comparison between three antibiotics Penicillin, streptomycin, and Neomycin.

Legends, Annotation, Visual encoding, and coloring of the visualization:

The chart has the Bacteria names on the x-axis, and the MIC values on the y-axis, with the Gram staining variable represented by a switch present above the visualization. The bars are colored pink for Penicillin, Violet for Streptomycin, and peach for Neomycin antibiotic The bars are labeled with MIC values to facilitate easy comparison and interpretation of the effectiveness of the antibiotics against the different bacterial strains. The color encoding of the bars also makes it easy to identify which antibiotic is Penicillin, which is Streptomycin, and which is Neomycin, without requiring the reader to refer to a legend. For better differentiation the switch between Gram-negative and Gram-positive bacteria is present.

Observations: The chart clearly shows that Penicillin is most effective against Gram-positive bacteria, while Streptomycin and Neomycin are more effective against Gram-negative bacteria.

Possible Drawbacks of the Visualization: However, the chart design may obscure some details such as the actual MIC values of each antibiotic used on bacteria. Therefore, the chart may not be suitable for readers who need detailed information on the specific MIC values for each Antibiotic. Overall, the chart design effectively communicates the relative effectiveness of the two different bacterial strains grouped by antibiotics used on them.

Tools used:

• MS Excel
• Flourish