Pandas read_excel() - Reading Excel File in Python With Examples

We can use the pandas module read_excel() function to read the excel file data into a DataFrame object.

If you look at an excel sheet, it’s a two-dimensional table. The DataFrame object also represents a two-dimensional tabular data structure.

1. Pandas read_excel() Example

Let’s say we have an excel file with two sheets – Employees and Cars. The top row contains the header of the table.

Pandas read_excel()


Excel File Sheets Data

Here is the example to read the “Employees” sheet data and printing it.

import pandas
excel_data_df = pandas.read_excel('records.xlsx', sheet_name="Employees")
# print whole sheet data


   EmpID    EmpName EmpRole
0      1     Pankaj     CEO
1      2  David Lee  Editor
2      3   Lisa Ray  Author
  • The first parameter is the name of the excel file.
  • The sheet_name parameter defines the sheet to be read from the excel file.
  • When we print the DataFrame object, the output is a two-dimensional table. It looks similar to an excel sheet records.

2. List of Columns Headers of the Excel Sheet

We can get the list of column headers using the columns property of the dataframe object.



['EmpID' 'EmpName' 'EmpRole']

3. Printing a Column Data

We can get the column data and convert it into a list of values.



['Pankaj', 'David Lee', 'Lisa Ray']

4. Pandas read_excel() usecols example

We can specify the column names to be read from the excel file. It’s useful when you are interested in only a few of the columns of the excel sheet.

import pandas
excel_data_df = pandas.read_excel('records.xlsx', sheet_name="Cars", usecols=['Car Name', 'Car Price'])


         Car Name      Car Price
0      Honda City     20,000 USD
1  Bugatti Chiron  3 Million USD
2     Ferrari 458   2,30,000 USD

If the excel sheet doesn’t have any header row, pass the header parameter value as None.

excel_data_df = pandas.read_excel('records.xlsx', sheet_name="Numbers", header=None)

If you pass the header value as an integer, let’s say 3. Then the third row will be treated as the header row and the values will be read from the next row onwards. Any data before the header row will be discarded.

6. Excel Sheet to Dict, CSV and JSON

The DataFrame object has various utility methods to convert the tabular data into Dict, CSV, or JSON format.

excel_data_df = pandas.read_excel('records.xlsx', sheet_name="Cars", usecols=['Car Name', 'Car Price'])
print('Excel Sheet to Dict:', excel_data_df.to_dict(orient="record"))
print('Excel Sheet to JSON:', excel_data_df.to_json(orient="records"))
print('Excel Sheet to CSV:n', excel_data_df.to_csv(index=False))


Excel Sheet to Dict: [{'Car Name': 'Honda City', 'Car Price': '20,000 USD'}, {'Car Name': 'Bugatti Chiron', 'Car Price': '3 Million USD'}, {'Car Name': 'Ferrari 458', 'Car Price': '2,30,000 USD'}]
Excel Sheet to JSON: [{"Car Name":"Honda City","Car Price":"20,000 USD"},{"Car Name":"Bugatti Chiron","Car Price":"3 Million USD"},{"Car Name":"Ferrari 458","Car Price":"2,30,000 USD"}]
Excel Sheet to CSV:
 Car Name,Car Price
Honda City,"20,000 USD"
Bugatti Chiron,3 Million USD
Ferrari 458,"2,30,000 USD"

7. References

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