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Often you may wish to convert one or more columns in a pandas DataFrame to strings. Fortunately this is easy to do using the built-in pandas function.

This tutorial shows several examples of how to use this function.

Example 1: Convert a Single DataFrame Column to String

Suppose we have the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E'],
                   'points': [25, 20, 14, 16, 27],
                   'assists': [5, 7, 7, 8, 11]})

#view DataFrame 
df

        player	points	assists
0	A	25	5
1	B	20	7
2	C	14	7
3	D	16	8
4	E	27	11

We can identify the data type of each column by using dtypes:

df.dtypes

player     object
points      int64
assists     int64
dtype: object

We can see that the column “player” is a string while the other two columns “points” and “assists” are integers.

We can convert the column “points” to a string by simply using astype(str) as follows:

df['points'] = df['points'].astype(str)

We can verify that this column is now a string by once again using dtypes:

df.dtypes

player     object
points     object
assists     int64
dtype: object

Example 2: Convert Multiple DataFrame Columns to Strings

We can convert both columns “points” and “assists” to strings by using the following syntax:

df[['points', 'assists']] = df[['points', 'assists']].astype(str)

And once again we can verify that they’re strings by using dtypes:

df.dtypes

player     object
points     object
assists    object
dtype: object

Example 3: Convert an Entire DataFrame to Strings

Lastly, we can convert every column in a DataFrame to strings by using the following syntax:

#convert every column to stringsdf = df.astype(str)

#check data type of each column
df.dtypes
player     object
points     object
assists    object
dtype: object

You can find the complete documentation for the astype() function .