Pandas provides a function called read_excel() to read Excel files into a Pandas dataframe. Here’s an example:
import pandas as pd
# read the Excel file into a Pandas dataframe
df = pd.read_excel('data.xlsx', sheet_name='Sheet1')
# print the dataframe
print(df)
In this example, we use the read_excel() function to read an Excel file called ‘data.xlsx’ into a Pandas dataframe. We also specify the sheet name to read using the sheet_name parameter, which is set to ‘Sheet1’ in this case. If you don’t specify a sheet name, Pandas will read the first sheet in the Excel file by default.
Once you have a Pandas dataframe, you can manipulate and analyze the data using the various functions available in Pandas. For example, you can filter rows based on a condition, group the data by one or more columns, aggregate the data using various functions, and more.
Finally, you can write the Pandas dataframe back to an Excel file using the to_excel() method. Here’s an example:
# write the dataframe to an Excel file
df.to_excel('output.xlsx', index=False)
In this example, we use the to_excel() method to write the Pandas dataframe back to an Excel file called ‘output.xlsx’. By default, to_excel() writes the data to a sheet named ‘Sheet1’, but you can also specify a sheet name using the sheet_name parameter. The index=False parameter is used to prevent writing the Pandas dataframe index to the Excel file. Check out the pandas documentation for more details on how to handle Excel files in Pandas.