**Pandas**

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**Data Aggregation Cookbook**

Applying a function to multiple columns in groupsCalculating percentiles of a DataFrameCalculating the percentage of each value in each groupComputing descriptive statistics of each groupDifference between a group's count and sizeDifference between methods apply and transform for groupbyGetting cumulative sum of each groupGetting descriptive statistics of DataFrameGetting multiple aggregates of a column after groupingGetting n rows with smallest column value in each groupGetting number of distinct rows in each groupGetting size of each groupGetting specific group after groupbyGetting the first row of each groupGetting the last row of each groupGetting the top n rows with largest column value in each groupGetting unique values of each groupGrouping by multiple columnsGrouping without turning group column into indexMerging rows within a group togetherNaming columns after aggregationSorting values within groups

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# Getting descriptive statistics of DataFrame in Pandas

*schedule*Mar 5, 2023

local_offer

Tags Python●Pandas

*toc*Table of Contents

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Check out the

**interactive map of data science**To get the descriptive statistics of DataFrame in Pandas, use the DataFrame's `describe(~)`

method.

# Example

Consider the following DataFrame:

```
df
A B C0 a 3 11 b 5 22 c 7 3
```

To get the descriptive statistics of each column:

```
B Ccount 3.0 3.0mean 5.0 2.0std 2.0 1.0min 3.0 1.025% 4.0 1.550% 5.0 2.075% 6.0 2.5max 7.0 3.0
```

Here, the `50%`

percentile represents the median.

Published by Isshin Inada

Edited by 0 others

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