Tutorials References Exercises Videos Menu
Website Get Certified Pro NEW

Pandas DataFrame describe() Method

❮ DataFrame Reference


Example

Multiply the values for each row with the values from the previous row:

import pandas as pd

data = [[10, 18, 11], [13, 15, 8], [9, 20, 3]]

df = pd.DataFrame(data)

print(df.describe())
Try it Yourself »

Definition and Usage

The describe() method returns description of the data in the DataFrame.

If the DataFrame contains numerical data, the description contains these information for each column:

count - The number of not-empty values.
mean - The average (mean) value.
std - The standard deviation.
min - the minimum value.
25% - The 25% percentile*.
50% - The 50% percentile*.
75% - The 75% percentile*.
max - the maximum value.

*Percentile meaning: how many of the values are less than the given percentile. Read more about percentiles in our Machine Learning Percentile chapter.


Syntax

dataframe.describe(percentiles, include, exclude, datetime_is_numeric)

Parameters

The percentile, include, exclude, datetime_is_numeric parameters are keyword arguments.

Parameter Value Description
percentile numbers between:
0 and 1
Optional, a list of percentiles to include in the result, default is :
[.25, .50, .75].
include None
'all'

datatypes
Optional, a list of the data types to allow in the result
exclude None
'all'

datatypes
Optional, a list of the data types to disallow in the result
datetime_is_numeric True
False
Optional, default False. Set to True to treat datetime data as numeric

 Return Value

A DataFrame object with statistics for each row.


❮ DataFrame Reference