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Analyzing and Visualizing Real-World Data
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Contenido del Curso

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

bookThe Most Profitable Store

Since we want to find the most profitable stores based on the given data, we need to group the observations in the df dataframe by the 'Store' column values and calculate the total (sum) of the 'Weekly_Sales' column for each group. Finally, we need to sort the resulting values in descending order.

Tarea

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

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 3. Capítulo 2
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bookThe Most Profitable Store

Since we want to find the most profitable stores based on the given data, we need to group the observations in the df dataframe by the 'Store' column values and calculate the total (sum) of the 'Weekly_Sales' column for each group. Finally, we need to sort the resulting values in descending order.

Tarea

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

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 3. Capítulo 2
toggle bottom row

bookThe Most Profitable Store

Since we want to find the most profitable stores based on the given data, we need to group the observations in the df dataframe by the 'Store' column values and calculate the total (sum) of the 'Weekly_Sales' column for each group. Finally, we need to sort the resulting values in descending order.

Tarea

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

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Since we want to find the most profitable stores based on the given data, we need to group the observations in the df dataframe by the 'Store' column values and calculate the total (sum) of the 'Weekly_Sales' column for each group. Finally, we need to sort the resulting values in descending order.

Tarea

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

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 3. Capítulo 2
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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