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Course Content

Analyzing and Visualizing Real-Life Data

1. Preprocessing Data: Part I

Loading the DataData TypesAnalyzing Columns [1/4]Removing Characters: Method 1Removing Characters: Method 2Analyzing Columns [2/4]Replacing Characters

2. Preprocessing Data: Part II

Analyzing Columns [3/4]Removing and ReplacingAnalyzing Columns [4/4]Wrong Convertation?Proper ConvertingThat's All?

3. Analyzing Data

Superficial AnalysisThe Most Profitable StoreDate RangeHow Periodic the Data is?The Most Profitable PeriodsThe Best CombinationHolidays EffectWhat Holidays are we Considering?The Most Profitable Holiday

4. Visualizing Data

First Look at the DataComparing DynamicsFinding RelationDoes Temperature Affect?Or is it Holiday Effect?Comparing ShopsAdding Holidays to Comparison

Analyzing and Visualizing Real-Life Data

Comparing DynamicsComparing Dynamics

Returning to the previous section, you solved the problem of finding the most profitable stores. According to the data, these stores are numbered 20, 4, 14, 13, and 2 (the numbers are saved in the top_stores variable). Let's examine the sales dynamics of these stores.

Task

  1. Prepare the data for visualization: filter the values in the df so that only data for stores with the numbers present in the top_stores list remain. Save the resulting data in the data variable.
  2. Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the data dataframe. Display a separate line for each store.

Everything was clear?

Section 4. Chapter 2
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