You can use the following basic syntax to specify the dtype of each column in a DataFrame when importing an Excel file into pandas:

df = pd.read_excel('my_data.xlsx',
                 dtype = {'col1': str, 'col2': float, 'col3': int})

The dtype argument specifies the data type that each column should have when importing the Excel file into a pandas DataFrame.

The following example shows how to use this syntax in practice.

Example: Specify dtypes when Importing Excel File into Pandas

Suppose we have the following Excel file called player_data.xlsx:

If we import the Excel file using the read_excel() function, pandas will attempt to identify the data type for each column automatically:

import pandas as pd

#import Excel file
df = pd.read_excel('player_data.xlsx')

#view resulting DataFrame
print(df)

  team  points  rebounds  assists
0    A      24         8        5
1    B      20        12        3
2    C      15         4        7
3    D      19         4        8
4    E      32         6        8
5    F      13         7        9

#view data type of each column
print(df.dtypes)

team        object
points       int64
rebounds     int64
assists      int64
dtype: object

From the output we can see that the columns in the DataFrame have the following data types:

• team: object
• points: int64
• rebounds: int64
• assists: int64

However, we can use the dtype argument within the read_excel() function to specify the data types that each column should have:

import pandas as pd

#import Excel file and specify dtypes of columns
df = pd.read_excel('player_data.xlsx',
                   dtype = {'team': str, 'points': float, 'rebounds': int,
                            'assists': float})

#view resulting DataFrame
print(df)

  team  points  rebounds  assists
0    A    24.0         8      5.0
1    B    20.0        12      3.0
2    C    15.0         4      7.0
3    D    19.0         4      8.0
4    E    32.0         6      8.0
5    F    13.0         7      9.0

#view data type of each column
print(df.dtypes)

team         object
points      float64
rebounds      int32
assists     float64
dtype: object

From the output we can see that the columns in the DataFrame have the following data types:

• team: object
• points: float64
• rebounds: int32
• assists: float64

These data types match the ones that we specified using the dtype argument.

Note that in this example, we specified the dtype for each column in the DataFrame.

Note: You can find the complete documentation for the pandas read_excel() function .

The following tutorials explain how to perform other common tasks in pandas: