Let’s see how to read excel files to Pandas dataframe objects using Pandas.
Code #1 : Read an excel file using read_excel() method of pandas.
# import pandas lib as pd import pandas as pd
# read by default 1st sheet of an excel file dataframe1 = pd.read_excel( 'SampleWork.xlsx' )
print (dataframe1)
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Output :
Name Age Stream Percentage 0 Ankit 18 Math 95 1 Rahul 19 Science 90 2 Shaurya 20 Commerce 85 3 Aishwarya 18 Math 80 4 Priyanka 19 Science 75
Code #2 : Reading Specific Sheets using ‘sheet_name’ of read_excel() method.
# import pandas lib as pd import pandas as pd
# read 2nd sheet of an excel file dataframe2 = pd.read_excel( 'SampleWork.xlsx' , sheet_name = 1 )
print (dataframe2)
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Output :
Name Age Stream Percentage 0 Priya 18 Math 95 1 shivangi 19 Science 90 2 Jeet 20 Commerce 85 3 Ananya 18 Math 80 4 Swapnil 19 Science 75
Code #3 : Reading Specific Columns using ‘usecols’ parameter of read_excel() method.
# import pandas lib as pd import pandas as pd
require_cols = [ 0 , 3 ]
# only read specific columns from an excel file required_df = pd.read_excel( 'SampleWork.xlsx' , usecols = require_cols)
print (required_df)
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Output :
Name Percentage 0 Ankit 95 1 Rahul 90 2 Shaurya 85 3 Aishwarya 80 4 Priyanka 75
Code #4 : Handling missing data using ‘na_values’ parameter of the read_excel() method.
# import pandas lib as pd import pandas as pd
# Handling missing values of 3rd sheet of an excel file. dataframe = pd.read_excel( 'SampleWork.xlsx' , na_values = "Missing" ,
sheet_name = 2 )
print (dataframe)
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Output :
Name Age Stream Percentage 0 Priya 18 Math 95 1 shivangi 19 Science 90 2 Jeet 20 NaN 85 3 Ananya 18 Math 80 4 Swapnil 19 Science 75
Code #5 : Skip starting rows when Reading an Excel File using ‘skiprows’ parameter of read_excel() method.
# import pandas lib as pd import pandas as pd
# read 2nd sheet of an excel file after # skipping starting two rows df = pd.read_excel( 'SampleWork.xlsx' , sheet_name = 1 , skiprows = 2 )
print (df)
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Output :
shivangi 19 Science 90 0 Jeet 20 Commerce 85 1 Ananya 18 Math 80 2 Swapnil 19 Science 75
Code #6 : Set the header to any row and start reading from that row, using ‘header’ parameter of the read_excel() method.
# import pandas lib as pd import pandas as pd
# setting the 3rd row as header. df = pd.read_excel( 'SampleWork.xlsx' , sheet_name = 1 , header = 2 )
print (df)
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Output :
shivangi 19 Science 90 0 Jeet 20 Commerce 85 1 Ananya 18 Math 80 2 Swapnil 19 Science 75
Code #7 : Reading Multiple Excel Sheets using ‘sheet_name’ parameter of the read_excel()method.
# import pandas lib as pd import pandas as pd
# read both 1st and 2nd sheet. df = pd.read_excel( 'SampleWork.xlsx' , na_values = "Missing" ,
sheet_name = [ 0 , 1 ])
print (df)
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Output :
OrderedDict([(0, Name Age Stream Percentage 0 Ankit 18 Math 95 1 Rahul 19 Science 90 2 Shaurya 20 Commerce 85 3 Aishwarya 18 Math 80 4 Priyanka 19 Science 75), (1, Name Age Stream Percentage 0 Priya 18 Math 95 1 shivangi 19 Science 90 2 Jeet 20 Commerce 85 3 Ananya 18 Math 80 4 Swapnil 19 Science 75)])
Code #8 : Reading all Sheets of the excel file together using ‘sheet_name’ parameter of the read_excel() method.
# import pandas lib as pd import pandas as pd
# read all sheets together. all_sheets_df = pd.read_excel( 'SampleWork.xlsx' , na_values = "Missing" ,
sheet_name = None )
print (all_sheets_df)
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Output :
OrderedDict([('Sheet1', Name Age Stream Percentage 0 Ankit 18 Math 95 1 Rahul 19 Science 90 2 Shaurya 20 Commerce 85 3 Aishwarya 18 Math 80 4 Priyanka 19 Science 75), ('Sheet2', Name Age Stream Percentage 0 Priya 18 Math 95 1 shivangi 19 Science 90 2 Jeet 20 Commerce 85 3 Ananya 18 Math 80 4 Swapnil 19 Science 75), ('Sheet3', Name Age Stream Percentage 0 Priya 18 Math 95 1 shivangi 19 Science 90 2 Jeet 20 NaN 85 3 Ananya 18 Math 80 4 Swapnil 19 Science 75)])