How to Import an Excel File into Python using Pandas?

The dataset may not always be available in CSV format. As a result, Pandas includes functions for converting datasets in different formats to Data frames. The format of an excel file is ‘.xlsx’.

Before we begin, we must first install a few libraries as shown below:

pip install pandas
pip install xlrd

We must use the pandas.read_excel() function to import an Excel file into Python using Pandas.

Syntax:

pandas.read_excel(io, sheet_name=0, header=0, names=None,….)

Return Value: It returns a Dataframe or a dictionary of Dataframes.

Let us take an example of demo.xlsx excel spreadsheet as shown below:

How to Import an Excel File into Python using Pandas

How to Import an Excel File into Python using Pandas?

Example1: Reading an Excel file

Approach:

  • Import pandas module as pd using the import keyword.
  • Read the excel file using the read_excel() function and store it as a DataFrame.
  • The Exit of the Program.

Below is the implementation:

# Import pandas module as pd using the import keyword
import pandas as pd
 
# Read the excel file using the read_excel() function and 
# store it as a DataFrame
data_frme = pd.read_excel('demo.xlsx')
data_frme

Output:

Reading an Excel file

Example2: Selecting a specific column

Approach:

  • Import pandas module as pd using the import keyword.
  • Select a specific column of the excel file using the index_col by passing the column index as an argument to it.
  • The Exit of the Program.
# Import pandas module as pd using the import keyword
import pandas as pd
 
# Select a specific column of the excel file using the index_col by passing the 
# column index as an argument to it
data_frme= pd.read_excel("sample.xlsx",
                   index_col = 0)    
data_frme

Output:

Selecting a specific column

Example3: 

If we don’t want the initial heading of the columns, you can change it to indexes by using the “header” argument.

# Import pandas module as pd using the import keyword
import pandas as pd
 
# Read the excel file using the read_excel() function by passing the 
# file name and header= None as the arguments to it.
# (It modifies the header with indexes)
# store it as a DataFrame
data_frme= pd.read_excel('demo.xlsx',
                   header = None)  
data_frme

Output:

Read the excel file using the read excel

Example4: Changing the datatype of columns

If we wish to modify or change the data type of a certain column, use the “dtype” argument.

# Import pandas module as pd using the import keyword
import pandas as pd
 
# Change the datatype of coulums(Gender, Age) using the dtype parameter 
# and store it in a variable
data_frme=  pd.read_excel('demo.xlsx', 
                   dtype = {"Gender": str,
                            "Age":float})
data_frme

Output:

Changing the datatype of columns

Example5: 

If we have unknown values, you can handle them with the “na_values” argument. It will convert the previously specified unknown values to “NaN.”

# Import pandas module as pd using the import keyword
import pandas as pd
 
# Convert the unknown values to NaN using the na_values argument
data_frme= df = pd.read_excel('demo.xlsx', 
                   na_values =['Mara', 
                               'Philip'])
data_frme

Output:

Changing the datatype of columns nv values

Here we converted unknown/unwanted data (Mara,Philip) to NaN values.

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