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)

 

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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