How to Convert Integers to Strings in Pandas DataFrame

Need to convert integers to strings in pandas DataFrame?

Depending on your needs, you may use either of the 3 methods below to perform the conversion:

(1) Convert a single DataFrame Column using the apply(str) method:

df['DataFrame Column'] = df['DataFrame Column'].apply(str)

(2) Convert a single DataFrame Column using the astype(str) method:

df['DataFrame Column'] = df['DataFrame Column'].astype(str)

(3) Convert an entire DataFrame using the applymap(str) method:

df = df.applymap(str)

Let’s now see the steps to apply each of the above methods in practice.

Steps to Convert Integers to Strings in Pandas DataFrame

Step 1: Collect the Data to be Converted

To start, collect the data that you’d like to convert from integers to strings.

For example, I gathered the following data about products and their prices:

Product	Price
ABC	350
DDD	370
XYZ	410

The goal is to convert the integer values under the ‘Price’ column into strings.

Step 2: Create the DataFrame

Next, create the DataFrame to capture the above data in Python.

This is the code to create the DataFrame for our example:

import pandas as pd

Data = {'Product': ['ABC','DDD','XYZ'],
          'Price': [350,370,410]}

df = pd.DataFrame(Data)
print (df)
print (df.dtypes)

Once you run the code in Python, you’ll see that the ‘Price’ column is set to integers:

Step 3: Convert the Integers to Strings in Pandas DataFrame

Finally, you can use the apply(str) template to assist you in the conversion of integers to strings:

df['DataFrame Column'] = df['DataFrame Column'].apply(str)

In our example, the ‘DataFrame column’ that contains the integers is the ‘Price’ column.

Therefore, the full Python code to convert the integers to strings for the ‘Price’ column is:

import pandas as pd

Data = {'Product': ['ABC','DDD','XYZ'],
          'Price': [350,370,410]}

df = pd.DataFrame(Data)
df['Price'] = df['Price'].apply(str)

print (df)
print (df.dtypes)

Run the code, and you’ll see that the ‘Price’ column is now set to strings (i.e., where the data type is now object):

Alternatively, you may use the astype(str) method to perform the conversion to strings:

df['DataFrame Column'] = df['DataFrame Column'].astype(str)

So the full Python code would look like this:

import pandas as pd

Data = {'Product': ['ABC','DDD','XYZ'],
          'Price': [350,370,410]}

df = pd.DataFrame(Data)
df['Price'] = df['Price'].astype(str)

print (df)
print (df.dtypes)

As before, you’ll see that the ‘Price’ column now reflects strings:

Convert the Entire DataFrame to Strings

Let’s say that you have more than a single column that you’d like to convert from integers to strings.

For example, let’s suppose that you have the following dataset with 3 columns:

Product	Price	Original Cost
ABC	350	200
DDD	370	230
XYZ	410	280

The goal is to convert the last two columns (i.e., the ‘Price’ and ‘Original Cost’ columns) from integers to strings.

Here is how DataFrame would look like:

import pandas as pd

Data = {'Product': ['ABC','DDD','XYZ'],
        'Price': [350,370,410],
        'Original Cost': [200,230,280]
        }

df = pd.DataFrame(Data)

print (df)
print (df.dtypes)

Run the code, and you’ll see that the last two columns are currently set to integers:

In that case, you may use applymap(str) to convert the entire DataFrame to strings:

df = df.applymap(str)

Here is the complete code for our example:

import pandas as pd

Data = {'Product': ['ABC','DDD','XYZ'],
        'Price': [350,370,410],
        'Original Cost': [200,150,100]
        }

df = pd.DataFrame(Data)
df = df.applymap(str)

print (df)
print (df.dtypes)

Run the code, and you’ll see that all the columns in the DataFrame are now strings:

You may also wish to check the following tutorials that review the steps to convert: