Converting Data Types in a DataFrame Using astype() in Pandas

Last update on December 21 2024 09:14:43 (UTC/GMT +8 hours)

Pandas: Data Cleaning and Preprocessing Exercise-9 with Solution

Write a Pandas program to convert data types using astype().

In this exercise, we have converted the data types of columns in a DataFrame using the astype() method.

Sample Solution :

Code :

import pandas as pd

# Create a sample DataFrame with mixed types
df = pd.DataFrame({
    'ID': ['1', '2', '3'],
    'Price': ['10.5', '20.0', '30.5']
})

# Convert 'ID' to integer and 'Price' to float
df['ID'] = df['ID'].astype(int)
df['Price'] = df['Price'].astype(float)

# Output the result
print(df)

Output:

   ID  Price
0   1   10.5
1   2   20.0
2   3   30.5

Explanation:

• Created a DataFrame with columns in string format.
• Used astype() to convert 'ID' to integer and 'Price' to float.
• Returned the DataFrame with updated data types.

Python-Pandas Code Editor:

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