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power query editor in power bi allows you to transform and manipulate data before it is visualized. one of the powerful features is the ability to run python scripts directly within power query. this allows users to harness the capabilities of python libraries for data manipulation and analysis.

### running python scripts in power query editor: a step-by-step tutorial

#### prerequisites

1. **power bi desktop**: ensure you have power bi desktop installed.
2. **python installation**: you need to have python installed on your machine. you can download it from the [official python website]([ Ссылка ]).
3. **python libraries**: ensure that you have the necessary libraries installed (e.g., `pandas`, `numpy`). you can install them using pip:



4. **enable python in power bi**: in power bi desktop, go to `file` `options and settings` `options`. under the `python scripting` section, specify your python installation path.

#### step 1: load data into power bi

1. open power bi desktop.
2. load the data that you want to manipulate. for instance, you can import a csv file:
- click on `home` `get data` `text/csv`.
- choose your file and click `load`.

#### step 2: open power query editor

1. after loading your data, click on `transform data` to open the power query editor.

#### step 3: add a python script

1. in the power query editor, go to the `home` tab.
2. click on `run python script`.

#### step 4: write your python script

in the dialog box that appears, you can write your python script. here’s a basic example where we will use a python script to perform some data manipulation using the `pandas` library.

**example scenario**: assume you have a dataset with sales data, and you want to calculate the total sales and categorize them into 'high', 'medium', and 'low'.



#### step 5: load the result

1. after writing your script, click `ok`.
2. if there are no errors in your script, you will see a new table created in the power query ...

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