Pandas
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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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Merging rows within a group together in Pandas
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Pandas
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To merge rows within a group together in Pandas we can use the agg(~)
method together with the join(~)
method to concatenate the row values.
Example
Consider the following DataFrame:
import pandas as pd
df
Name Hobbies0 Mary Cooking1 Sky Travel2 James Cooking
To group by 'Hobbies'
and merge names of all people with each hobby into a single row:
Notice how the names of people sharing the same hobby appear in a single line separated by ' '
.
Specifying delimiter
We can specify the delimiter to use by placing it before the join(~)
method like so:
Here we specify the delimiter as a comma followed by a space.
Published by Arthur Yanagisawa
Edited by 0 others
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