Download apcdata_week.csv, which contains bus route information for a full week. This data file is 92 MB and contains nearly a million rows of data.

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October 6, 2020

Download apcdata_week.csv, which contains bus route information for a full week. This data file is 92 MB and contains nearly a million rows of data.

Download apcdata_week.csv, which contains bus route information for a full week. This data file is 92 MB and contains nearly a million rows of data. In the same directory as this data file develop a Jupyter Notebook namedmarta-analysis. Your notebook should have the following parts:

Part 0 – Header

Include a Markdown cell

Part 1 – Basic Metrics

For each of the following, include a Markdown cell with the question, and a code cell which computes and displays the answer.

  • What is the stop_name where the most people got on?
  • What is the stop_name where the most people got off?
  • Which direction has the highest passenger traffic? (Passenger traffic is determined by the sum of the number of people getting on at any stop along a route in a given direction)
  • Which direction has the lowest passenger traffic?
  • What is the route_name of the most popular route? (The most popular route is the one with the highest average passenger traffic in either direction.)
  • Which date has the highest passenger traffic?
  • Which date has the lowest passenger traffic?

Part 2 – Visualization

Often single answers don’t give enough information. For example, perhaps the second-busiest stop is close to the busiest but all others are far behind.

For each of the following, include a Markdown cell with the question/description and a code cell that produces the visualization. Choose a graphic display that would clearly present the information.

  • System-wide passenger traffic (ons + offs) totals for each date
  • Five busiest stops (ons + offs), ranked buy passenger traffic
  • How busy is each route compared to the other routes?
  • How busy is each direction (north, south, east, west) compared to other directions?

I have already made the queries I am mostly confused about the jupyter notebook please check queries

queries here

 

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