In the context of using Python with Excel, the DataFrame is a crucial data object. It essentially represents a table, capable of being formed either from Excel spreadsheet data or from calculations executed by Python within Excel.
An example demonstrates the creation of a DataFrame from an Excel spreadsheet. The process involves the xl()
command, which requires two parameters. The first parameter is a range of Excel cells, like “A2:A4”, and the second parameter includes options for the DataFrame. In this instance, the command is spend=xl("A2:A4", headers=True)
, indicating that the DataFrame should be created from the cell range A1:A4, with the first row serving as the header.
![](https://pythonandexcel.com/wp-content/uploads/2023/11/Screenshot-2023-11-23-123406.png)
Once the DataFrame is established, basic manipulations can be performed. For example, to aggregate values in the ‘spend’ column, the following code is used:
spend = xl("A1:A4", headers=True)
s = spend.sum(axis=0)
![](https://pythonandexcel.com/wp-content/uploads/2023/11/Screenshot-2023-11-23-123443.png)
By pasting this code into the Python for Excel formula, the cell is marked as a DataFrame, indicating its creation and availability for use.
![](https://pythonandexcel.com/wp-content/uploads/2023/11/Screenshot-2023-11-23-123505.png)
To display the output of this DataFrame, simply type s
into another Python for Excel formula cell. To ensure that the data from the DataFrame spills over into other Excel cells, it’s important to select “Python Output -> Excel Value” in the popup menu for the Python DataFrame cell.
![](https://pythonandexcel.com/wp-content/uploads/2023/11/Screenshot-2023-11-23-123547.png)
Lastly, to see the sum of ‘spend’ displayed and to initiate recalculation, it’s necessary to press Ctrl+Enter after completing the Python in Excel formula.
![](https://pythonandexcel.com/wp-content/uploads/2023/11/Screenshot-2023-11-23-123606.png)