sborto86 commented 1 year ago

https://github.com/sborto86/project-II-pipelines

samuelTAIronhack commented 1 year ago

storytelling (README.md)

Clear overall, but there is space for improvement. see if you can add more comments in the readme under all the graphs. This way information of some of the first graphs is forgotten after looking at al the other ones.

Code

Looks good overall
Make sure to add more spacing in your code (example below, this is very dense and harder to read than if it were to have more spacing.
Good job on adding lots of small comments in your code explaining what you are doing.

`# Groupping data by region regions = hotel_country.groupby("continent_name")[['agoda_num','booking_num']].sum()

Creating a new column region

regions["Region"] = list(regions.index)

Renaming columns

regions = regions.rename(columns={"agoda_num": "Agoda", "booking_num": "Booking"}) regions = regions.sort_values(by='Booking', ascending=False)

Flattering table for plotting "each platform will generate a new row"

regions2 = pd.melt(regions, id_vars=["Region"], value_name="Number of Hotels")

Plotting data

regions2 = regions2.rename(columns={"variable":"Platform"}) regions_graph=sns.barplot(data=regions2, x="Number of Hotels", y="Region", hue="Platform", hue_order= ["Booking", "Agoda"]) plt.xticks(rotation=45) regions_graph.set(title = 'Number of Hotels by Region') plt.ticklabel_format(style='plain', axis='x')`

Graphs

Great looking graphs that are self explanatory
Good use of color
Try to angle the country names 45 degrees under the graphs for readability

Organisation

Files are all well organised but maybe you can move the enriching-and-cleaning.ipynb to the src folder also.

In general good work! Keep it up!