Pandas Tutorial · Pandas Tutorial

Pandas Read CSV

Learn all about Pandas Read CSV in this comprehensive tutorial.

5 min read intermediate

Pandas DataFrames

Pandas Read JSON

•A simple way to store big data sets is to use CSV files (comma separated files).
•The number of rows returned is defined in Pandas option settings.

Read CSV Files

A simple way to store big data sets is to use CSV files (comma separated files).

CSV files contains plain text and is a well know format that can be read by everyone including Pandas.

In our examples we will be using a CSV file called 'data.csv'.

Download data.csv. or Open data.csv

python

import pandas as pddf = pd.read_csv('data.csv')print(df.to_string())

Note: Tip: use to_string() to print the entire DataFrame.

If you have a large DataFrame with many rows, Pandas will only return the first 5 rows, and the last 5 rows:

python

import pandas as pddf = pd.read_csv('data.csv')print(df)

max_rows

The number of rows returned is defined in Pandas option settings.

You can check your system's maximum rows with the pd.options.display.max_rows statement.

python

import pandas as pdprint(pd.options.display.max_rows)

In my system the number is 60, which means that if the DataFrame contains more than 60 rows, the print(df) statement will return only the headers and the first and last 5 rows.

You can change the maximum rows number with the same statement.

python

import pandas as pdpd.options.display.max_rows 
  = 9999df = pd.read_csv('data.csv')print(df)

Module quiz

2 questions

Which of the following is true about Pandas Read CSV?

It is strictly typedIt is evaluated at runtimeIt requires explicit memory managementIt is deprecated

What is the most common pitfall when working with Pandas Read CSV?

SyntaxErrorIndentationErrorNameErrorTypeError

Answer all questions to submit.

Pandas DataFrames

Pandas Read JSON

Pandas Read CSV

AI Summary

Read CSV Files

max_rows

Module quiz