How to Efficiently Join Grouped Values in Pandas with a Delimiter?

Joining Grouped Values with a Delimiter in Pandas

When using the groupby function to group data with multiple values, it's common to encounter the issue of concatenating these values without a delimiter. To resolve this, you can leverage the agg method.

Consider the following DataFrame:

col | val
-----|-----
A    | Cat
A    | Tiger
B    | Ball
B    | Bat

To group these rows based on the col column and concatenate the values in the val column, use the following code:

import pandas as pd
df = pd.DataFrame({'col': ['A', 'A', 'B', 'B'], 'val': ['Cat', 'Tiger', 'Ball', 'Bat']})
grouped = df.groupby('col')['val'].agg('-'.join)

This approach should yield the desired result:

col | val
-----|-----
A    | Cat-Tiger
B    | Ball-Bat

However, if the apply method is used as an alternative, it can lead to an unexpected outcome with hyphenated values occurring multiple times, as seen below:

df.groupby('col')['val'].apply(lambda x: '-'.join(x))

col | val
-----|-----
A        | C-a-t-T-i-g-e-r
B          | B-a-l-l-B-a-t

To avoid this issue, use the agg method instead, as demonstrated in the example above.

Additionally, to convert the grouped index or MultiIndex to regular columns, you can use the reset_index method:

df1 = grouped.reset_index(name='new')

The above is the detailed content of How to Efficiently Join Grouped Values in Pandas with a Delimiter?. For more information, please follow other related articles on the PHP Chinese website!