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How to Concatenate Strings from Multiple Rows in Pandas Using Groupby?

Susan Sarandon
Release: 2024-12-15 12:17:14
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How to Concatenate Strings from Multiple Rows in Pandas Using Groupby?

Concatenate Strings from Multiple Rows using Pandas Groupby

When working with dataframes, there may be situations where you need to consolidate strings from multiple rows while grouping them by specific criteria. Pandas offers a convenient solution for this through its groupby and transform functions.

Problem Statement

Given a dataframe with columns 'name,' 'text,' and 'month,' the goal is to concatenate the strings in the 'text' column for each unique combination of 'name' and 'month.' The desired output is a dataframe with unique 'name' and 'month' combinations and the concatenated 'text' values.

Solution

To achieve this, you can utilize the following steps:

  1. Group the dataframe by 'name' and 'month' using the groupby() function.
  2. Use the transform() function to apply a lambda expression that joins the 'text' entries for each group.
  3. To remove duplicate rows, drop the duplicates from the resulting dataframe using the drop_duplicates() function.

Here's an example code:

import pandas as pd
from io import StringIO

data = StringIO("""
"name1","hej","2014-11-01"
"name1","du","2014-11-02"
"name1","aj","2014-12-01"
"name1","oj","2014-12-02"
"name2","fin","2014-11-01"
"name2","katt","2014-11-02"
"name2","mycket","2014-12-01"
"name2","lite","2014-12-01"
""")

# load string as stream into dataframe
df = pd.read_csv(data, header=0, names=["name", "text", "date"], parse_dates=[2])

# add column with month
df["month"] = df["date"].apply(lambda x: x.month)

df['text'] = df[['name','text','month']].groupby(['name','month'])['text'].transform(lambda x: ','.join(x))
df[['name','text','month']].drop_duplicates()
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The above code generates a dataframe with the desired result:

    name         text  month
0  name1       hej,du     11
2  name1        aj,oj     12
4  name2     fin,katt     11
6  name2  mycket,lite     12
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Alternative Solution

Instead of using transform(), you can also utilize apply() and then reset_index() to achieve the same result. The updated code would be:

df.groupby(['name','month'])['text'].apply(','.join).reset_index()
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This simplified version eliminates the lambda expression and provides a more concise solution.

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