Reading and writing CSV files

Comma-separated values (CSV) is one of the most commonly used file formats for storing data. The structure or the way in which you read a CSV file may be familiar to you if you have worked with another DataFrame library such as pandas.

In this recipe, we’ll examine how to read and write a CSV file in Polars with some parameters. We’ll also look at how we can do the same in a LazyFrame.

How to do it...

Here are the steps and examples for how to read and write CSV files in Polars:

1. Read the customer_shopping_data.csv dataset into a DataFrame:

   df = pl.read_csv('../data/customer_shopping_data.csv')
   df.head()

   The preceding code will return the following output:

Figure 2.1 – The first five rows of the customer shopping dataset

2. If the CSV file doesn’t have a header, Polars would treat the first row as the header:

   df = pl.read_csv('../data/customer_shopping_data_no_header...