Home Backend Development Python Tutorial How Can I Use Pandas Groupby to Join Values with a Delimiter?

How Can I Use Pandas Groupby to Join Values with a Delimiter?

Dec 09, 2024 pm 03:49 PM

How Can I Use Pandas Groupby to Join Values with a Delimiter?

Pandas Groupby with Delimiter Join

Using the Pandas library, you can group rows with multiple values using the groupby function. However, by default, the values are concatenated without a delimiter. This article addresses the issue of introducing a delimiter to separate the values within each group.

You initially attempted to use the apply() function to join the values with a dash (-), but this resulted in the entire string being concatenated instead of separating the individual values.

A more straightforward approach is to use the agg() function with the join parameter. Here's how you can achieve the desired output:

group = df.groupby('col')['val'].agg('-'.join)
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This will join the values within each group using a dash as the delimiter. The result will be:

col
A    Cat-Tiger
B     Ball-Bat
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Note that the index is still present in the output, if you want to convert it to a column, you can use the reset_index() function:

df1 = group.reset_index(name='new')
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This will convert the index to a new column named new. The final output will be:

  col  new
0   A  Cat-Tiger
1   B  Ball-Bat
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Alternatively, you can use the squeeze() function (note this function was made as_nunique function in Pandas 1.4.0) to remove the index entirely and obtain a Series object:

group.squeeze()
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This will result in a Series with the grouped values joined by the specified delimiter:

col
A    Cat-Tiger
B     Ball-Bat
Name: val
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