What is info function in Pandas?

The info function in Pandas is displays a summary of the dataframe. It displays column names, data types, the number of non-null values, and memory usage.

Syntax

The syntax of the info function is as follows:

DataFrame.info(verbose=None, buf=None, max_cols=None, memory_usage=None, show_counts=None, null_counts=None)

Parameters

All parameters are optional for the info function. Parameters and their descriptions are given below:

Parameters	Description
`verbose`	Determines whether the full summary is to be printed. Takes a `bool` value. By default, the setting in `pandas.options.display.max_info_columns` is followed.
`buf`	Determines where to send the output. By default, the output is printed to `sys.stdout`.
`max_cols`	Determines when to switch from the verbose to the truncated output. Takes an `int` variable. If the dataframe has more than `max_cols` columns, the truncated output is used. By default, the setting in `pandas.options.display.max_info_columns` is used.
`memory_usage`	Determines whether total memory usage of the dataframe elements (including the index) should be displayed. By default, this follows the `pandas.options.display.memory_usage` setting.
`show_counts`	Determines whether to show non-null value counts or not. A value of True will always show the counts, while False never shows the counts.

Return value

The info function does not return anything. Instead, it outputs a concise summary of the dataframe.

Examples

The code snippet below shows how we can use the info function in Pandas:

If verbose = False, column information is not printed.

memory_usage can be altered while dealing with larger dataframes.

import pandas as pd
import numpy as np
# Creating a dataframe
int_values = [1, 2, 3, np.NAN, 5]
text_values = ['alpha', 'beta', 'gamma', 'delta', 'epsilon']
float_values = [0.0, 0.25, 0.5, 0.75, 1.0]
df = pd.DataFrame({"int_col": int_values, "text_col": text_values,
    "float_col": float_values})
print("Original Dataframe")
print(df)
print('\n')
# With verbose = True
print(df.info(verbose=True))
print('\n')
# With verbose = False
print(df.info(verbose=False))
print('\n')
# Changing mempry usage
print(df.info(memory_usage='deep'))

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