Twitter 
Facebook
chevron_left
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
0
0
0
new
Getting size of each group in Pandas
Programming
chevron_rightPython
chevron_rightPandas
chevron_rightCookbooks
chevron_rightDataFrame Cookbooks
chevron_rightData Aggregation Cookbook
schedule Jul 1, 2022
Last updated Python●Pandas
Tags tocTable of Contents
expand_more To get the size of each group in Pandas, use the groups' size() method.
Example
Consider the following DataFrame about some products:
df = pd.DataFrame({"price":[500,300,700, 200,900], "brand":["apple", "google", "apple", "google","apple"], "device":["phone","phone","computer","phone","phone"]}, index=["a","b","c","d","e"])df
price brand devicea 500 apple phoneb 300 google phonec 700 apple computerd 200 google phonee 900 apple phone
To get the number of products offered by each brand:
df.groupby("brand").size() # returns a Series
brandapple 3google 2dtype: int64
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
Ask a question or leave a feedback...
0
0
0
Enjoy our search
