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‎10-Data Analysis With Python/10.1-numpy.ipynb‎

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‎10-Data Analysis With Python/10.2-pandas.ipynb‎

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‎10-Data Analysis With Python/10.3-datamanipulation.ipynb‎

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‎10-Data Analysis With Python/10.4-readdata.ipynb‎

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‎10-Data Analysis With Python/10.5-matplotlib.ipynb‎

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‎10-Data Analysis With Python/10.6-seaborn.ipynb‎

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‎10-Data Analysis With Python/data.csv‎

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Date,Category,Value,Product,Sales,Region
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2023-01-01,A,28.0,Product1,754.0,East
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2023-01-02,B,39.0,Product3,110.0,North
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2023-01-03,C,32.0,Product2,398.0,East
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2023-01-04,B,8.0,Product1,522.0,East
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2023-01-05,B,26.0,Product3,869.0,North
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2023-01-06,B,54.0,Product3,192.0,West
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2023-01-07,A,16.0,Product1,936.0,East
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2023-01-08,C,89.0,Product1,488.0,West
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2023-01-09,C,37.0,Product3,772.0,West
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2023-01-10,A,22.0,Product2,834.0,West
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2023-01-11,B,7.0,Product1,842.0,North
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2023-01-12,B,60.0,Product2,,West
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2023-01-13,A,70.0,Product3,628.0,South
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2023-01-14,A,69.0,Product1,423.0,East
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2023-01-15,A,47.0,Product2,893.0,West
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2023-01-16,C,,Product1,895.0,North
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2023-01-17,C,93.0,Product2,511.0,South
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2023-01-18,C,,Product1,108.0,West
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2023-01-19,A,31.0,Product2,578.0,West
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2023-01-20,A,59.0,Product1,736.0,East
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2023-01-21,C,82.0,Product3,606.0,South
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2023-01-22,C,37.0,Product2,992.0,South
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2023-01-23,B,62.0,Product3,942.0,North
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2023-01-24,C,92.0,Product2,342.0,West
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2023-01-25,A,24.0,Product2,458.0,East
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2023-01-26,C,95.0,Product1,584.0,West
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2023-01-27,C,71.0,Product2,619.0,North
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2023-01-28,C,56.0,Product2,224.0,North
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2023-01-29,B,,Product3,617.0,North
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2023-01-30,C,51.0,Product2,737.0,South
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2023-01-31,B,50.0,Product3,735.0,West
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2023-02-01,A,17.0,Product2,189.0,West
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2023-02-02,B,63.0,Product3,338.0,South
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2023-02-03,C,27.0,Product3,,East
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2023-02-04,C,70.0,Product3,669.0,West
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2023-02-05,B,60.0,Product2,,West
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2023-02-06,C,36.0,Product3,177.0,East
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2023-02-07,C,2.0,Product1,,North
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2023-02-08,C,94.0,Product1,408.0,South
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2023-02-09,A,62.0,Product1,155.0,West
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2023-02-10,B,15.0,Product1,578.0,East
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2023-02-11,C,97.0,Product1,256.0,East
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2023-02-12,A,93.0,Product3,164.0,West
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2023-02-13,A,43.0,Product3,949.0,East
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2023-02-14,A,96.0,Product3,830.0,East
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2023-02-15,B,99.0,Product2,599.0,West
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2023-02-16,B,6.0,Product1,938.0,South
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2023-02-17,B,69.0,Product3,143.0,West
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2023-02-18,C,65.0,Product3,182.0,North
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2023-02-19,C,11.0,Product3,708.0,North

‎10-Data Analysis With Python/data.xlsx‎

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‎10-Data Analysis With Python/df_excel‎

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‎10-Data Analysis With Python/sales1_data.csv‎

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Date,Product,Sales,Region
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2023-01-01,Product3,738.0,West
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2023-01-02,Product2,868.0,North
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2023-01-03,Product2,554.0,West
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2023-01-04,Product1,618.0,South
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2023-01-05,Product3,501.0,East
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2023-01-06,Product1,,West
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2023-01-07,Product3,339.0,South
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2023-01-08,Product3,280.0,South
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2023-01-09,Product2,806.0,North
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2023-01-10,Product2,816.0,South
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2023-01-11,Product3,469.0,West
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2023-01-12,Product3,,East
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2023-01-13,Product3,,East
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2023-01-14,Product3,676.0,East
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2023-01-15,Product1,183.0,South
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2023-01-16,Product1,424.0,South
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2023-01-17,Product1,,South
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2023-01-18,Product1,,South
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2023-01-19,Product2,124.0,North
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2023-01-20,Product3,732.0,West
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2023-01-21,Product2,,West
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2023-01-22,Product3,296.0,West
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2023-01-23,Product2,737.0,West
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2023-01-24,Product3,531.0,East
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2023-01-25,Product2,834.0,North

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