Import Data
For this section you need to download IRIS dataset which is publicly available. You can download the dataset from https://gist.github.com/netj/8836201. Once the data is downloaded save it in the csv format.1. Import the sample data by clicking on Get data> Text/CSV ‘.
2. Select the CSV file and click on ‘Load’ data.
Data Manipulation using Python Scripts
The process of changing the raw data is known as Data Transformation. Data can easily be manipulated using the powerful Python Libraries. We can manipulate our dataset to display information in a more organized and meaningful manner.
For more data transformation guides: click here
Let’s Calculate “Area” by multiplying “Petal.length” into “Petal.width”.
1. The first step is to load the data set into Power BI. Click Get data in the Home Tab.
2. Select the type of dataset you want to load. After that browse the file explorer, choose your dataset and click on Load.
You can apply data manipulation using python scripts, but before running the python scripts you have to change/adjust the privacy levels.
3. Click on File > Options and Settings.
4. Click on Data Source Settings.
5. The following window will appear. Now click on Edit Permissions.
6. Now change the privacy levels and click OK.
In this example we have changed the privacy level to Public but you can choose according to your requirement.
7. Click on Edit Queries in the Home tab to open Power BI Query Editor.
The following window will appear.
8. Click on Transform Tab.
9. Click on Run Python Scripts in the Scripts Section.
The following window will appear.
10. You will write all the Python scripts in this window. In this manual we will explain how you can perform different arithmetic operations on the loaded data set.
11. Now write the code as shown below to perform multiplication of two columns of our dataset.
12. Click OK to execute the script.
The result of the multiplication operation has to be stored in a separate column. For this, we are creating a new column “Area” using python script.
13. The following window will appear, mark the Ignore Privacy Levels checkbox, and click on
After clicking save, Power BI will start running your Python Script.
14. The result of the script will appear as below.
15. Click on the Table to see the results of this multiplication of columns.
A result table will appear in the bottom showing the results of the multiplication.
Here you can see that the result of the multiplication is stored in a new column named ‘Area’ which we created in the Python script. You can scroll through all the rows to see the result by using these navigation buttons.
Conclusion:
Python is becoming popular due to its healthy and active support community, capacity to handle big data and its amazing libraries. Power BI now provides its users with the option to integrate python with Power BI. In this blog post, importing and manipulating in Python scripts has been discussed.
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- Power BI Basic training course across Australia.
- Power BI Advanced training course across Australia.
- Power BI DAX training course across Australia.
- Power BI Corporate training across Australia.
