Reputation: 3161
I am a Pandas DataFrame as follows:
df = pd.DataFrame({
'id': [1,2 ,3],
'txt1': ['Hello there1', 'Hello there2', 'Hello there3'],
'txt2': ['Hello there4', 'Hello there5', 'Hello there6'],
'txt3': ['Hello there7', 'Hello there8', 'Hello there9']
})
df
id txt1 txt2 txt3
1 Hello there1 Hello there4 Hello there7
2 Hello there2 Hello there5 Hello there8
3 Hello there3 Hello there6 Hello there9
I want to concatenate column txt1
, txt2
, and txt3
. So far I am able to achieve it as follows:
df['alltext'] = df['txt1'] + df['txt2'] + df['txt3']
df
id txt1 txt2 txt3 alltext
1 Hello there1 Hello there4 Hello there7 Hello there1Hello there4Hello there7
2 Hello there2 Hello there5 Hello there8 Hello there2Hello there5Hello there8
3 Hello there3 Hello there6 Hello there9 Hello there3Hello there6Hello there9
but how to introduce space character between the two column strings while concatenating in Pandas?
I have just started learning Pandas.
Upvotes: 5
Views: 13356
Reputation: 863791
You can also add separator between columns:
df['alltext'] = df['txt1'] + ' ' + df['txt2'] + ' ' + df['txt3']
Or filter by DataFrame.filter
only columns with txt
in column name and use join
per rows with apply
:
df['alltext'] = df.filter(like='txt').apply(' '.join, axis=1)
Or filter only object columns by DataFrame.select_dtypes
- most times a Series
with a dtype of object is going to be a string
- but it could be any Python object
:
df['alltext'] = df.select_dtypes('object').apply(' '.join, axis=1)
Or select columns by positions - all columns without first by DataFrame.iloc
:
df['alltext'] = df.iloc[:, 1:].apply(' '.join, axis=1)
Thank you, @Jon Clements for solution for better matching columns names with txt
and numeric:
df['alltext'] = df.filter(regex=r'^txt\d+$').apply(' '.join, axis=1)
Upvotes: 11
Reputation: 5795
Simply add space between that,
df['alltext'] = df['txt1'] + ' ' + df['txt2'] + ' ' + df['txt3']
Upvotes: 1