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:

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:

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:

• Strings to integers
• Strings to floats
• Integers to floats