Analyzing Uber Trips -EDA using python

Analyzing Uber Trips -EDA using python

What is uber?

Uber is an independent taxicab company that hires drivers who use their personal vehicles while logged into the Uber app on a mobile device. Passengers request rides using the app, inputting pick-up and drop-off locations, and all payment is done through a pre-authorized credit card right through the app.

source:techboomers.com/t/what-is-uber

About this project

This dataset has 1 million rows and four columns. I personally have the interest to know more about uber and its data. And this dataset grabbed my attention to analyze this data.

This dataset contains the uber rides pickups in New York City. All data points lie in September month of 2014.

Features: dateAndTime, Lat, Lon, Base

My Findings

1. Sunday has the least number of trips in a week

And Tuesday has the highest trips in a week weekdays.png

  • Tue: 163230
  • Sat: 162057
  • Fri: 160380
  • Thus: 153276
  • Mon: 137288
  • Wed: 135373
  • Sun: 116532

2.Hourly analysis - 4 PM to 8 PM has more rides in a day

Uber rides get a noticeable hike From 7 AM and again drop in the lunchtime.

At 6 PM uber has the highest number of bookings.

hour counts.png

3.There are significant drops in bookings on weekends

day 13th has the highest bookings in September month (43205 bookings)

day trend.png

4. Hours and Trips have a strong correlation

correlation between Hours and Trips: 0.81205

scratter-hours-trips.png

5. Weekends have more percentage of midnight bookings compared to normal days

uber trips per hour on weekends.png hour counts.png

6. Saturdays and Sundays have a similar amount of bookings

trip counts on saturdays.png

trips counts on sundays.png

7. The B02617 Base(Weiter) has the highest bookings

tlc base count plot.png

8. Manhattan has the highest bookings in NewYork City

heatmap cooridinates-uber trips.PNG

End