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We will look at methods for converting Pandas DataFrame columns to strings.

• Pandas Series.astype(str)Method
• DataFrame.apply()Methods operate on the elements in a column

We will use the same DataFrame below in this article.

import pandas as pd

df = pd.DataFrame({"A": [1, 2, 3], "B": [4.1, 5.2, 6.3], "C": ["7", "8", "9"]})

print(df)
print(df.dtypes)

   A    B  C
0  1  4.1  7
1  2  5.2  8
2  3  6.3  9

A      int64
B    float64
C     object
dtype: object

Pandas DataFrame Series.astype(str)feature

Pandas Series.astype(dtype) method converts a Pandas Series to the specified dtypedtype.

pandas.Series.astype(str)

As mentioned in this article, it converts Series, DataFrame columns to strings.

>>> df
   A    B  C
0  1  4.1  7
1  2  5.2  8
2  3  6.3  9
>>> df['A'] = df['A'].astype(str)
>>> df
   A    B  C
0  1  4.1  7
1  2  5.2  8
2  3  6.3  9
>>> df.dtypes
A     object
B    float64
C     object
dtype: object

astype()method does not modify the DataFrame data in-place, so we need to assign the returned Pandas Series to a specific DataFrame column.

We can also convert multiple columns to strings at once by enclosing the names within square brackets to form a list.

>>> df[['A','B']] = df[['A','B']].astype(str)
>>> df
   A    B  C
0  1  4.1  7
1  2  5.2  8
2  3  6.3  9
>>> df.dtypes
A    object
B    object
C    object
dtype: object

DataFrame.apply()Methods operate on the elements in a column

apply(func, *args, **kwds)

DataFrame.apply()method funcapplies a function to each column or row.

For simplicity, we can use lambdathe function instead func.

>>> df['A'] = df['A'].apply(lambda _: str(_))
>>> df
   A    B  C
0  1  4.1  7
1  2  5.2  8
2  3  6.3  9
>>> df.dtypes
A     object
B    float64
C     object
dtype: object

You cannot applyapply a function to multiple columns using the method.

>>> df[['A','B']] = df[['A','B']].apply(lambda _: str(_))
Traceback (most recent call last):
  File "<pyshell#31>", line 1, in <module>
    df[['A','B']] = df[['A','B']].apply(lambda _: str(_))
  File "D:\WinPython\WPy-3661\python-3.6.6.amd64\lib\site-packages\pandas\core\frame.py", line 3116, in __setitem__
    self._setitem_array(key, value)
  File "D:\WinPython\WPy-3661\python-3.6.6.amd64\lib\site-packages\pandas\core\frame.py", line 3144, in _setitem_array
    self.loc._setitem_with_indexer((slice(None), indexer), value)
  File "D:\WinPython\WPy-3661\python-3.6.6.amd64\lib\site-packages\pandas\core\indexing.py", line 606, in _setitem_with_indexer
    raise ValueError('Must have equal len keys and value '
ValueError: Must have equal len keys and value when setting with an iterable