# 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

Updated on: 24-Feb-2021

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