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Analyzing and Visualizing Real-World Data

The Most Profitable Periods

Good, now we know that the given data are weekly. Let's find out what weeks were the most profitable by comparing the total for each week.

Task

  1. Group the observations in the df dataframe by the 'Date' column values.
  2. Select the 'Weekly_Sales' column.
  3. Calculate the total (sum) for each group.
  4. Sort values in descending order (not ascending).

Everything was clear?

Section 3. Chapter 5
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course content

Course Content

Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

1. Preprocessing Data: Part I

Loading the DataData TypesColumns OverviewRemoving Characters: Method 1Removing Characters: Method 2Checking ColumnsReplacing Characters

2. Preprocessing Data: Part II

Analyzing ColumnsRemoving and ReplacingProcessing DatesWrong 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

The Most Profitable Periods

Good, now we know that the given data are weekly. Let's find out what weeks were the most profitable by comparing the total for each week.

Task

  1. Group the observations in the df dataframe by the 'Date' column values.
  2. Select the 'Weekly_Sales' column.
  3. Calculate the total (sum) for each group.
  4. Sort values in descending order (not ascending).

Everything was clear?

Section 3. Chapter 5
toggle bottom row
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