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Common Data Analyst interview questions

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It's a one of great videos I used when have been preparing for my first MEAL officer position interview. The video not focused on some app or tecnologie qusetions, but it can give you an advice, what kind of topics you may meet at the interview. If you aren't focused on the senior DA position, you should repeat what you have already known, but there are too many different information and this video can give a hint about priority knowledge areas.  
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Power BI simple custom line chart with Python visual and matplotlib

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Step-by-step instruction: To convert an existing line chart into a Python visual, you will utilize the matplotlib library. Select your visual and change its type to Python by selecting correspond button on the right panel. Begin by importing the necessary module with the following code: import matplotlib.pyplot as plt . Define the x-axis and y-axis variables for your chart. For the x-axis, you will use the "month name" column from your dataset. For the y-axis, you need to define three variables: y1 for the current year's profit, y2 for the previous year's profit, and y3 for the profit growth or decline. Make sure to accurately identify and assign the corresponding columns from your dataset to these variables. Proceed to define the plots for each y-axis variable using the plt.plot() function. You will create three separate plots, one for each variable. Begin with y1 by using plt.plot(x, y1) where x represents the x-axis values and y1 represents the y-axis ...
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Power BI ETL and simple visuals with Python matplotlib

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Step-by-step instruction Open Power BI and navigate to the "Get Data" section. Click on "More options" and select the "Python" option. In the Python script editor, start by importing the pandas library as pd. This library will be used to handle the data. Create a variable called "my_data" and assign it the value of reading the Excel file using pandas. Specify the file location as "d:\Python tutorials\Power BI advanced dashboard advanced\dashboard advanced.xlsx". Use the pivot table function to summarize the data. Create a variable called "summary" and assign it the result of the pivot table operation. Set the index to the "city" column and use the "sum" aggregation function to calculate the sum of revenue and duration for each city. Use the "reset_index()" function to include the city names as part of the resulting table. Press "OK" to initiate the data processing. Explain that this...
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