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Analyzing and Visualizing Real-World Data
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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.

Tarefa

  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).

Tarefa

  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).

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 5
toggle bottom row

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.

Tarefa

  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).

Tarefa

  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).

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 5
toggle bottom row

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.

Tarefa

  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).

Tarefa

  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).

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

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.

Tarefa

  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).

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 5
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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