How to read excel multiple sheets in pandas? To read multiple sheets from an Excel file using Pandas, you can use the pd.read_excel() function. sheet_name param on pandas.read_excel() is used to read multiple sheets from excel. This supports reading excel sheets by name or position. When you read multiple sheets, it creates a Dict of DataFrame, each key in Dictionary is represented as Sheet name and DF for Dict value.
1. Pandas Read Excel Multiple Sheets
sheet_name param also takes a list of sheet names as values that can be used to read multiple sheets into Pandas DataFrame. Not that while reading multiple sheets it returns a Dict of DataFrame. The key in Dict is a sheet name and the value would be DataFrame.
This param takes values str, int, list, or None, default 0. When None is used it reads all sheets from excel. By default, it is set to 0 meaning the first sheet.
Let’s see with an example, I have an excel file with two sheets named 'Technologies' and 'Schedule'.
import pandas as pd
# Read excel file with sheet name
dict_df = pd.read_excel('c:/apps/courses_schedule.xlsx',
sheet_name=['Technologies','Schedule'])
Since we are reading two sheets from excel, this function returns Dict of DataFrame. You can get the DataFrames from Dict as follows.
# Get DataFrame from Dict
technologies_df = dict_df .get('Technologies')
schedule_df = df.get('Schedule')
# Print DataFrame's
print(technologies_df)
print(schedule_df)
The 'Technologies' sheet is converted into DataFrame as follows. Note that empty values are converted into NaN on DataFrame.
# Output:
Courses Fee Duration Discount
0 Spark 25000 50 Days 2000
1 Pandas 20000 35 Days 1000
2 Java 15000 NaN 800
3 Python 15000 30 Days 500
4 PHP 18000 30 Days 800
And the 'Schedule' sheet is converted into DataFrame as follows.
# Output:
Courses Days Time
0 Spark MON, THU 7:00 AM to 9:00 AM
1 Pandas MON, WED 8:00 AM to 10:00 AM
2 Java WEN, FRI 7:00 PM to 9:00 PM
3 Python TUE, THU 6:00 PM to 8:00 PM
4 PHP WEN, THU 8:00 AM to 10:00 AM
Frequently Asked Questions on Read Excel Multiple Sheets in Pandas
To read multiple sheets from an Excel file using Pandas, you can use the pd.read_excel() function and specify the sheet_name parameter. The sheet_name parameter can take several values.
After reading multiple sheets from an Excel file using Pandas, the data is typically stored in a dictionary of DataFrames where the keys are the sheet names. To access a specific sheet, you can use the sheet name as the key to retrieve the corresponding DataFrame.
You can concatenate all sheets into a single DataFrame using the pd.concat() function. After reading multiple sheets into a dictionary of DataFrames, you can use pd.concat() to combine them into a single DataFrame.
You can use the skiprows or skipfooter parameters to skip rows at the beginning or end of each sheet. If you want to skip a specific sheet, you can remove it from the dictionary after reading.
To handle missing values (NaN or Not a Number) while reading multiple sheets from an Excel file using Pandas, you can use the na_values parameter within the pd.read_excel() function. The na_values parameter allows you to specify a list of values that should be treated as NaN during the reading process.
You can specify the header row for each sheet independently when reading multiple sheets from an Excel file using Pandas. You can use the header parameter within the pd.read_excel() function. The header parameter can take different values.
Conclusion
In this article, you have learned how to read an excel with multiple sheets and convert it to pandas DataFrame. Since it returns a Dict of DataFrame, you have also learned how to get each DF from the dict.
Happy Learning !!
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