Convert Integer Columnin in pandas DataFrame to Float in Python (3 Examples)

This tutorial shows how to transform an integer variable in a pandas DataFrame to the float data type in the Python programming language.

Creating Example Data

import pandas as pd                           # Import pandas
df = pd.DataFrame({'A':[4, 9, 12, 1, 7],      # Constructing a pandas DataFrame
                   'B':[10, 9, 77, 22, 24],
                   'C':[35, 41, 41, 1, 13]})
print(df)
#     A   B   C
# 0   4  10  35
# 1   9   9  41
# 2  12  77  41
# 3   1  22   1
# 4   7  24  13
print(df.dtypes)                              # Printing the data types of all columns
# A    int64
# B    int64
# C    int64
# dtype: object

Example 1: Transforming One Column of a pandas DataFrame from Integer to Float

df1 = df.copy()                               # Duplicate pandas DataFrame
df1['A'] = df1['A'].astype(float)             # Converting integer to float
print(df1.dtypes)                             # Printing the data types of all columns
# A    float64
# B      int64
# C      int64
# dtype: object

Example 2: Transforming Multiple Columns of a pandas DataFrame from Integer to Float

df2 = df.copy()                               # Duplicate pandas DataFrame
df2 = df2.astype({'A': float, 'C': float})    # Converting integer to float
print(df2.dtypes)                             # Printing the data types of all columns
# A    float64
# B      int64
# C    float64
# dtype: object

Example 3: Transforming Each Column of a pandas DataFrame from Integer to Float

df3 = df.copy()                               # Duplicate pandas DataFrame
df3 = df3.astype(float)                       # Converting integer to float
print(df3.dtypes)                             # Printing the data types of all columns
# A    float64
# B    float64
# C    float64
# dtype: object

Related Articles & Further Resources

You may find some related Python tutorials on topics such as data conversion and naming data in the following list.

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