Numeric data or ... ?
In this exercise, and throughout this chapter, you'll be working with bicycle ride sharing data in San Francisco called ride_sharing
. It contains information on the start and end stations, the trip duration, and some user information for a bike sharing service.
The user_type
column contains information on whether a user is taking a free ride and takes on the following values:
1
for free riders.2
for pay per ride.3
for monthly subscribers.
In this instance, you will print the information of ride_sharing
using .info()
and see a firsthand example of how an incorrect data type can flaw your analysis of the dataset. The pandas
package is imported as pd
.
This exercise is part of the course
Cleaning Data in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Print the information of ride_sharing
print(____.____())
# Print summary statistics of user_type column
print(ride_sharing['____'].____())