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Creating a dataframe using Excel files

Last Updated : 06 Sep, 2024
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Let's see how to read excel files to Pandas dataframe objects using Pandas.

To get the SampleWork.xlsx file click here.

Code #1 : Read the above excel file using read_excel() method of pandas.
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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. 
 

Python
# 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)

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)])


 


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