Conteúdo do Curso
Analyzing and Visualizing Real-World Data
Analyzing and Visualizing Real-World Data
Comparing 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
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tarefa
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tudo estava claro?
Comparing 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
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tarefa
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tudo estava claro?
Comparing 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
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tarefa
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
Tudo estava claro?
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
- Prepare the data for visualization: filter the values in the
dfso that only data for stores with the numbers present in thetop_storeslist remain. Save the resulting data in thedatavariable. - Initialize a line plot with dates on the x-axis, weekly sales on the y-axis, using the
datadataframe. Display a separate line for each store.
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