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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
2. Preprocessing Data: Part II
3. Analyzing Data
4. Visualizing Data

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
test

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  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
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Seção 4. Capítulo 2
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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
test

Swipe to show code editor

  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
test

Swipe to show code editor

  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
test

Swipe to show code editor

  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
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