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.
Swipe to start coding
- 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.
Oplossing
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Completion rate improved to 3.45Comparing Dynamics
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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.
Swipe to start coding
- 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.
Oplossing
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Awesome!
Completion rate improved to 3.45single
