Introduction to Python for MATLAB Users/

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Challenge 1: Sales Data Analysis

Challenge 1: Sales Data Analysis

Test your data manipulation skills with the sales dataset in pandas and Matplotlib.

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In this exercise, use the pandas and Matplotlib libraries to analyze sales data from a CSV file. You’ll perform the following tasks.

Task 1: Load the dataset

Load the data into a pandas DataFrame using the pd.read_csv function and store it in a variable called sales_data. The file name is Sales-Data.csv. Display the first five rows of the data at the end.

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main.py
Sales-Data.csv
Date,Product,Sales,Profit,Region
2023-01-01,Product_A,1500,300,North
2023-01-01,Product_B,2000,500,South
2023-01-02,Product_A,1600,350,East
2023-01-02,Product_C,1200,200,West
2023-01-03,Product_B,1800,450,North
2023-01-03,Product_C,1400,250,South
2023-01-04,Product_A,1700,370,East
2023-01-04,Product_B,1900,480,West
2023-01-05,Product_C,1300,220,North
2023-01-05,Product_A,1800,400,South

Task 2: Plot the data

Create a bar plot showing total sales for each product. Use the groupby and sum functions from pandas to calculate the total sales.

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main.py
Sales-Data.csv
Date,Product,Sales,Profit,Region
2023-01-01,Product_A,1500,300,North
2023-01-01,Product_B,2000,500,South
2023-01-02,Product_A,1600,350,East
2023-01-02,Product_C,1200,200,West
2023-01-03,Product_B,1800,450,North
2023-01-03,Product_C,1400,250,South
2023-01-04,Product_A,1700,370,East
2023-01-04,Product_B,1900,480,West
2023-01-05,Product_C,1300,220,North
2023-01-05,Product_A,1800,400,South

Task 3: Manipulate the data

Create a new column in sales_data called Profit Margin that contains the calculated profit margin values using the formula:

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