Convert Integers to Floats in Pandas DataFrame

Two approaches to convert integers to floats in Pandas DataFrame:

(1) The astype(float) approach:

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

(2) The apply(float) approach:

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

Steps to Convert Integers to Floats in Pandas DataFrame

Step 1: Create a DataFrame

To start, create a DataFrame that contains integers.

For example, let’s create a simple DataFrame based on the following data (where the Price column contains the integers):

Here is the complete code to create the DataFrame in Python:

import pandas as pd

data = {'Product': ['AAA', 'BBB', 'CCC', 'DDD'],
        'Price': [300, 500, 700, 900]
        }

df = pd.DataFrame(data)

print(df)
print(df.dtypes)

Run the code, and you’ll see that the Price column contains integers:

  Product  Price
0     AAA    300
1     BBB    500
2     CCC    700
3     DDD    900
Product    object
Price       int64
dtype: object

Note that print(df.dtypes) was added at the bottom of the code to check the data type of each column in the DataFrame.

Step 2: Convert the Integers to Floats in Pandas DataFrame

You can apply the first approach of astype(float) in order to convert the integers to floats in Pandas DataFrame:

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

For our example, let’s convert the ‘Price‘ column (which currently contains the integers) to float:

df['Price'] = df['Price'].astype(float)

So this the complete code to perform the conversion is:

import pandas as pd

data = {'Product': ['AAA', 'BBB', 'CCC', 'DDD'],
        'Price': [300, 500, 700, 900]
        }

df = pd.DataFrame(data)

df['Price'] = df['Price'].astype(float)

print(df)
print(df.dtypes)

As you can see, the values under the ‘Price’ column are now floats:

  Product  Price
0     AAA  300.0
1     BBB  500.0
2     CCC  700.0
3     DDD  900.0
Product     object
Price      float64
dtype: object

Alternatively, you may use apply(float) to convert to float values:

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

For our example:

df['Price'] = df['Price'].apply(float)

The complete Python code:

import pandas as pd

data = {'Product': ['AAA', 'BBB', 'CCC', 'DDD'],
        'Price': [300, 500, 700, 900]
        }

df = pd.DataFrame(data)

df['Price'] = df['Price'].apply(float)

print(df)
print(df.dtypes)

Run the code in Python, and you’ll get the float values:

  Product  Price
0     AAA  300.0
1     BBB  500.0
2     CCC  700.0
3     DDD  900.0
Product     object
Price      float64
dtype: object

At times, you may need to convert strings to floats. If that’s the case, you may want to check the following guide that explains the steps to convert strings to floats in Pandas DataFrame.