Replace all occurrences of a string in a pandas dataframe (Python)

Solution 1:

You can use replace and pass the strings to find/replace as dictionary keys/items:

df.replace({'\n': '<br>'}, regex=True)

For example:

>>> df = pd.DataFrame({'a': ['1\n', '2\n', '3'], 'b': ['4\n', '5', '6\n']})
>>> df
   a    b
0  1\n  4\n
1  2\n  5
2  3    6\n

>>> df.replace({'\n': '<br>'}, regex=True)
   a      b
0  1<br>  4<br>
1  2<br>  5
2  3      6<br>

Solution 2:

It seems Pandas has change its API to avoid ambiguity when handling regex. Now you should use:

df.replace({'\n': '<br>'}, regex=True)

For example:

>>> df = pd.DataFrame({'a': ['1\n', '2\n', '3'], 'b': ['4\n', '5', '6\n']})
>>> df
   a    b
0  1\n  4\n
1  2\n  5
2  3    6\n

>>> df.replace({'\n': '<br>'}, regex=True)
   a      b
0  1<br>  4<br>
1  2<br>  5
2  3      6<br>