Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
Selected Reading
Write a program in Python to covert the datatype of a particular column in a dataframe
Assume, you have a dataframe, the result for converting float to int as,
Before conversion Name object Age int64 Maths int64 Science int64 English int64 Result float64 dtype: object After conversion Name object Age int64 Maths int64 Science int64 English int64 Result int64 dtype: object
To solve this, we will follow the steps given below −
Solution
Define a dataframe
Convert float datatype column ‘Result’ into ‘int’ as follows −
df.Result.astype(int)
Example
Let’s see the below implementation to get a better understanding −
import pandas as pd
data = {'Name': ['David', 'Adam', 'Bob', 'Alex', 'Serina'],
'Age' : [13,12,12,13,12],
'Maths': [98, 59, 66, 95, 70],
'Science': [75, 96, 55, 49, 78],
'English': [79, 45, 70, 60, 80],
'Result': [8.1,6.2,6.3,7.2,8.3]}
df = pd.DataFrame(data)
print("Before conversion\n", df.dtypes)
df.Result = df.Result.astype(int)
print("After conversion\n",df.dtypes)
Output
Name object Age int64 Maths int64 Science int64 English int64 Result float64 dtype: object Name object Age int64 Maths int64 Science int64 English int64 Result int64 dtype: object
Advertisements
