Creating a dataframe using Excel files (original) (raw)
Last Updated : 06 Sep, 2024
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)])