Part 2 of 3: Chicago Transit Authority: Bus Ridership And Its Communities

I mentioned in my previous post that I had two dataframes: 1) for the monthly averages and totals for all CTA bus routes, back to 2001 and up until November of 2016 and 2) for the bus route groups. I named them df_ridership and df_groups, thus:

df_ridership
df_groups

Joining these two dataframes by the route column, I came up with a dataframe of bus routes with associated route groups. I stored this in new dataframe object called df_joined.

df_joined

Having this dataframe in this form, I can now visualize the bus routes grouped by route groups. Here’s some of the examples as images:

“I am just image. I can’t make my tooltip hover effect work for you here.“
“I am just image. I can’t make my tooltip hover effect work for you here.“
“I am just image. I can’t make my tooltip hover effect work for you here.“

For better user experience on interactive tooltip hover effect, please click on this URL http://nbviewer.jupyter.org/github/HeyAlmer/cta_share/blob/d4576563b4223660a1f2a436ae30dd385dd4013c/CTA_Bus_Routes_Monthly-YEAR-Line-_share.ipynb to see my Jupyter Notebook showing my codes and all of the charts of 13 route groups.


In my next post, I am going to discuss about the Chicago community and bus routes shapefiles I used and another dataset for population density I collected online.

See you later.