Column-wise string concatenation of multiple rows in pandas.DataFrame with specific separator

Question

is there an efficient way to concatenate strings column-wise of multiple rows of a DataFrame such that the result is a single row whose value for each column is the concatenation of each value of the same column of all given rows?

Example

Combine the first four rows as explained above.

>>> df = pd.DataFrame([["this", "this"], ["is", "is"], ["a", "a"], ["test", "test"], ["ignore", "ignore"]])
>>> df
        0       1
0    this    this
1      is      is
2       a       a
3    test    test
4  ignore  ignore

Both accepted results:

          0              1
0  this is a test  this is a test

          0
1  this is a test
2  this is a test

jezrael · Accepted Answer · 2021-03-11 13:40:11Z

1

If need join all rows without last use DataFrame.iloc with DataFrame.agg:

s = df.iloc[:-1].agg(' '.join)
print (s)
0    this is a test
1    this is a test
dtype: object

For one row DataFrame add Series.to_frame with transpose:

df = df.iloc[:-1].agg(' '.join).to_frame().T
print (df)
                0               1
0  this is a test  this is a test

For all rows:

s = df.agg(' '.join)
print (s)
0    this is a test ignore
1    this is a test ignore
dtype: object


df = df.agg(' '.join).to_frame().T
print (df)
                       0                      1
0  this is a test ignore  this is a test ignore

answered Mar 11, 2021 at 13:40

jezrael

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2 Comments

cspecial Over a year ago

Thank you very much for your answer, jezrael. I tested it against my solution df.iloc[rows, :].apply(lambda column: " ".join(column), axis=0) (rows is a list consisting of row indices) and both performed equally well. Maybe we will find an even better solution!

jezrael Over a year ago

@cspecial - Yes, it is good solution, similar like my answer, axis=0 is default value, so should be removed.

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