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How to import an excel file into Python using Pandas?
  • Last Updated : 17 Aug, 2020

It is not always possible to get the dataset in CSV format. So, Pandas provides us the functions to convert datasets in other formats to the Data frame. An excel file has a ‘.xlsx’ format. 

Before we get started,  we need to install a few libraries. 

pip install pandas
pip install xlrd

 For importing an Excel file into Python using Pandas we have to use pandas.read_excel() function.

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

Return: DataFrame or dict of DataFrames.



Let’s suppose the Excel file looks like this:

Excel file

Now, we can dive into the code. 

Example 1: Read an Excel file.

Python3




import pandas as pd
  
df = pd.read_excel("sample.xlsx")
print(df)

Output:

dataframe

Example 2: To select a particular column, we can pass a parameter “index_col“. 



Python3




import pandas as pd
  
# Here 0th column will be extracted
df = pd.read_excel("sample.xlsx",
                   index_col = 0)  
  
print(df)

Output:

select a particular column

Example 3: In case you don’t prefer the initial heading of the columns, you can change it to indexes using the parameter “header”.

Python3




import pandas as pd
  
df = pd.read_excel('sample.xlsx',
                   header = None)
print(df)

Output:

dataframe without header

Example 4: If you want to change the data type of a particular column you can do it using the parameter “dtype“.

Python3




import pandas as pd
  
df = pd.read_excel('sample.xlsx'
                   dtype = {"Products": str,
                            "Price":float})
print(df)

Output:

data type change

Example 5: In case you have unknown values, then you can handle it using the parameter “na_values“. It will convert the mentioned unknown values into “NaN” 

Python3




import pandas as pd
df = pd.read_excel('sample.xlsx'
                   na_values =['item1'
                               'item2'])
print(df)

Output:

Dataframe with NaN value

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