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How to import an excel file into Python using Pandas?

Last Updated : 17 Aug, 2020
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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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