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The Best Combination | Analyzing Data
Analyzing and Visualizing Real-World Data
course content

Contenido del 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

The Best Combination

Interesting! The most profitable weeks are the second to last weeks of December and November. Now, let's answer the question: What was the best selling week and store? Since our data is already weekly, we won't need to group observations this time.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 3. Capítulo 6
toggle bottom row

The Best Combination

Interesting! The most profitable weeks are the second to last weeks of December and November. Now, let's answer the question: What was the best selling week and store? Since our data is already weekly, we won't need to group observations this time.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 3. Capítulo 6
toggle bottom row

The Best Combination

Interesting! The most profitable weeks are the second to last weeks of December and November. Now, let's answer the question: What was the best selling week and store? Since our data is already weekly, we won't need to group observations this time.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Interesting! The most profitable weeks are the second to last weeks of December and November. Now, let's answer the question: What was the best selling week and store? Since our data is already weekly, we won't need to group observations this time.

Tarea

  1. Select the 'Store', 'Date', and 'Weekly_Sales' columns.
  2. Sort the values of the 'Weekly_Sales' column in descending order (not ascending).
  3. Display the first 10 rows of the obtained dataframe.

Do not worry about syntax, pandas allows splitting methods by lines.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 3. Capítulo 6
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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