O'Reilly logo

Practical Data Science Cookbook - Second Edition by Abhijit Dasgupta, Benjamin Bengfort, Sean Patrick Murphy, Tony Ojeda, Prabhanjan Tattar

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

How to do it...

The following steps will lead us through our investigation:

  1. Let's look at how makes and models of cars inform us about fuel efficiency over time. First, let's look at the frequency of makes and models of cars available in the U.S., concentrating on 4-cylinder cars. To select the 4-cylinder cars, we first make the cylinders variable unique to see what the possible values are:
In [30]: pd.unique(vehicles_non_hybrid.cylinders) 
    ...:  
Out[30]: array([ 4., 12., 8., 6., 5., 10., 2., 3., 16., nan])

Both 4.0 and 4 are listed as unique values; this fact should raise your suspicion. Remember, when we imported the data, pandas warned us that several variables were mixed types, and one of these variables was cylinders.

  1. Let's convert ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required