CSV to DataFrame (1)

Putting data in a dictionary and then building a DataFrame works, but it's not very efficient. What if you're dealing with millions of observations? In those cases, the data is typically available as files with a regular structure. One of those file types is the CSV file, which is short for "comma-separated values".

To import CSV data into Python as a Pandas DataFrame you can use read_csv().

Let's explore this function with the same cars data from the previous exercises. This time, however, the data is available in a CSV file, named cars.csv. It is available in your current working directory, so the path to the file is simply 'cars.csv'.

This exercise is part of the course

Intermediate Python

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Exercise instructions

To import CSV files you still need the pandas package: import it as pd.
Use pd.read_csv() to import cars.csv data as a DataFrame. Store this DataFrame as cars.
Print out cars. Does everything look OK?

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import pandas as pd


# Import the cars.csv data: cars


# Print out cars

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