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Questions tagged [pandas-groupby]

To be used for grouping variables together based on a given condition. And only to be used with relevance to `pandas` library

pandas.DataFrame.groupby allows you to group variables in a DataFrame or a certain number of columns in different categories.

After grouping, one can also obtain the mean and perform other operations as well.

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Aggregation in Pandas

How can I perform aggregation with Pandas? No DataFrame after aggregation! What happened? How can I aggregate mainly strings columns (to lists, tuples, strings with separator)? How can I aggregate counts? How can I create a new column filled by…
jezrael
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How to get number of groups in a groupby object in pandas?

This would be useful so I know how many unique groups I have to perform calculations on. Thank you. Suppose groupby object is called dfgroup.
wolfsatthedoor
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Python - rolling functions for GroupBy object

I have a time series object grouped of the type . grouped.sum() gives the desired result but I cannot get rolling_sum to work with the groupby object. Is there any way to apply rolling…
user1642513
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Renaming Column Names in Pandas Groupby function

Q1) I want to do a groupby, SQL-style aggregation and rename the output column: Example dataset: >>> df ID Region count 0 100 Asia 2 1 101 Europe 3 2 102 US 1 3 103 Africa 5 4 100 Russia …
Baktaawar
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Python Pandas Group by date using datetime data

I have a column Date_Time that I wish to groupby date time without creating a new column. Is this possible the current code I have does not work. df = pd.groupby(df,by=[df['Date_Time'].date()])
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What is the equivalent of SQL "GROUP BY HAVING" on Pandas?

what would be the most efficient way to use groupby and in parallel apply a filter in pandas? Basically I am asking for the equivalent in SQL of select * ... group by col_name having condition I think there are many uses cases ranging from…
Mannaggia
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Use pandas.shift() within a group

I have a dataframe with panel data, let's say it's time series for 100 different objects: object period value 1 1 24 1 2 67 ... 1 1000 56 2 1 59 2 2 46 ... 2 1000 64 3 1 …
Alexandr Kapshuk
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Pandas - dataframe groupby - how to get sum of multiple columns

This should be an easy one, but somehow I couldn't find a solution that works. I have a pandas dataframe which looks like this: index col1 col2 col3 col4 col5 0 a c 1 2 f 1 a c 1 2 f 2 a …
Axel
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How to move pandas data from index to column after multiple groupby

I have the following pandas dataframe: token year uses books 386 xanthos 1830 3 3 387 xanthos 1840 1 1 388 xanthos 1840 2 2 389 xanthos 1868 2 2 390 xanthos 1875 1 1 I aggregate the…
prooffreader
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Sample each group after pandas groupby

I know this must have been answered some where but I just could not find it. Problem: Sample each group after groupby operation. import pandas as pd df = pd.DataFrame({'a': [1,2,3,4,5,6,7], 'b': [1,1,1,0,0,0,0]}) grouped =…
gongzhitaao
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What is the difference between pandas agg and apply function?

I can't figure out the difference between Pandas .aggregate and .apply functions. Take the following as an example: I load a dataset, do a groupby, define a simple function, and either user .agg or .apply. As you may see, the printing statement…
David D
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How to do a conditional count after groupby on a Pandas Dataframe?

I have the following dataframe: key1 key2 0 a one 1 a two 2 b one 3 b two 4 a one 5 c two Now, I want to group the dataframe by the key1 and count the column key2 with the value "one" to get this result: key1 …
Sethias
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Is there an "ungroup by" operation opposite to .groupby in pandas?

Suppose we take a pandas dataframe... name age family 0 john 1 1 1 jason 36 1 2 jane 32 1 3 jack 26 2 4 james 30 2 Then do a groupby() ... group_df = df.groupby('family') group_df =…
mkln
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What is the pandas equivalent of dplyr summarize/aggregate by multiple functions?

I'm having issues transitioning to pandas from R where dplyr package can easily group-by and perform multiple summarizations. Please help improve my existing Python pandas code for multiple aggregations: import pandas as pd data = pd.DataFrame( …
B.Mr.W.
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Use Pandas groupby() + apply() with arguments

I would like to use df.groupby() in combination with apply() to apply a function to each row per group. I normally use the following code, which usually works (note, that this is without groupby()): df.apply(myFunction, args=(arg1,)) With the…
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