Changing the datatype of columns in pandas dataframe is very easy. Here I am using stype() function to perform the typecase operation.  Refer to the following example. The type conversion is happening in the line number 10 of the code.


import pandas as pd
# create a sample dataframe
df = pd.DataFrame({'emp_id': ['111', '112', '113'], 'salary': ['40000', '50000', '60000'], 'name':['amal', 'sabitha', 'edward']})
# print the dataframe
print(df)
# print the datatypes in the dataframe
print(df.dtypes)
# now let us convert the data type of salary to integer
df = df.astype({'salary':'int'})
# print the dataframe
print(df)
# print the datatypes in the dataframe
print(df.dtypes)

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convert_datatype.py

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You can add as many columns as you want to convert the data type or typecast. For example if you want to typecast the columns emp_id and salary, use the following syntax.

> df = df.astype({‘salary’:‘int’, ’emp_id’:’int’})

 

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