Pandas Read CSV

Reading CSV Files with Pandas

CSV (Comma-Separated Values) files offer a simple and widely used format for storing large datasets. Since they contain plain text, CSV files are both human-readable and compatible with many tools — including Pandas, a powerful data analysis library in Python.

In this tutorial, we’ll demonstrate how to read a CSV file using Pandas. The file we'll use is named data.csv.

You can download or view the sample file : data.csv

use to_string() to print  the entire dataframe.

Program:

Load csv into data frame

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

Print data frame without to_string()

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

max_ rows in Pandas

Pandas has built-in display settings that control how many rows are shown when you print a DataFrame. One of these settings is max_rows, which determines the maximum number of rows that will be displayed.

You can check the current setting on your system using:

Program:   

Check number of maximum returned rows

import pandas as pd

print(pd.options.display.max_rows)

you can check system's maximum rows with pd.options.display.max_rows

Output:

60