Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Python - Convert one datatype to another in a Pandas DataFrame
Use the astype() method in Pandas to convert one datatype to another. Import the required library −
import pandas as pd
Create a DataFrame. Here, we have 2 columns, “Reg_Price” is a float type and “Units” int type −
dataFrame = pd.DataFrame(
{
"Reg_Price": [7000.5057, 1500, 5000, 8000, 9000.75768, 6000],
"Units": [90, 120, 100, 150, 200, 130]
}
)
Check the datatypes of the columns created above −
dataFrame.dtypes
Convert both the types to int32 −
dataFrame.astype('int32').dtypes
Example
Following is the code −
import pandas as pd
# Create DataFrame
dataFrame = pd.DataFrame(
{
"Reg_Price": [7000.5057, 1500, 5000, 8000, 9000.75768, 6000],
"Units": [90, 120, 100, 150, 200, 130]
}
)
print"DataFrame ...\n",dataFrame
print"\nDataFrame Types ...\n",dataFrame.dtypes
print"\nCast all columns to int32..."
print"\nUpdated DataFrame Types ...\n",dataFrame.astype('int32').dtypes
Output
This will produce the following output −
DataFrame ... Reg_Price Units 0 7000.50570 90 1 1500.00000 120 2 5000.00000 100 3 8000.00000 150 4 9000.75768 200 5 6000.00000 130 DataFrame Types ... Reg_Price float64 Units int64 dtype: object Cast all columns to int32... Updated DataFrame Types ... Reg_Price int32 Units int32 dtype: object
Updated on: 16-Sep-2021
306 Views
Advertisements