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’})
