Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Comparing Dynamics | Visualizing Data
Analyzing and Visualizing Real-World Data
course content

Conteúdo do 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

bookComparing 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.

Tarefa

  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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 4. Capítulo 2
toggle bottom row

bookComparing 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.

Tarefa

  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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 4. Capítulo 2
toggle bottom row

bookComparing 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.

Tarefa

  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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

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.

Tarefa

  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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 4. Capítulo 2
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
some-alt