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.
Swipe to show code editor
- Prepare the data for visualization: filter the values in the
df
so that only data for stores with the numbers present in thetop_stores
list remain. Save the resulting data in thedata
variable. - 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.
Obrigado pelo seu feedback!
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 show code editor
- Prepare the data for visualization: filter the values in the
df
so that only data for stores with the numbers present in thetop_stores
list remain. Save the resulting data in thedata
variable. - 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.
Obrigado pelo seu feedback!
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 show code editor
- Prepare the data for visualization: filter the values in the
df
so that only data for stores with the numbers present in thetop_stores
list remain. Save the resulting data in thedata
variable. - 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.
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.
Swipe to show code editor
- Prepare the data for visualization: filter the values in the
df
so that only data for stores with the numbers present in thetop_stores
list remain. Save the resulting data in thedata
variable. - 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.