Comparing Shops | Visualizing Data

Course Content

# Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

## Comparing Shops

As you can see, all of these points are related to the 'pre-Christmas' periods, as we noticed before. Now, let's use visualizing tools to compare the revenue for shops. We already know the top 5 selling stores, but are other shops significantly worse? We'll find out using a bar chart.

1. Prepare the data: group the values of the `df` DataFrame based on the `'Store'` column, then select the `'Weekly_Sales'` column, calculate sum values across groups, and reset the indexes. Save the result within the `data` variable.
2. Initialize a bar plot. Use the `'Store'` column values of `data` for the x-axis, `'Weekly_Sales'` for the y-axis, and make bars `'blue'`.
3. Display the plot.

Everything was clear?

Section 4. Chapter 6

Course Content

# Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

## Comparing Shops

As you can see, all of these points are related to the 'pre-Christmas' periods, as we noticed before. Now, let's use visualizing tools to compare the revenue for shops. We already know the top 5 selling stores, but are other shops significantly worse? We'll find out using a bar chart.

1. Prepare the data: group the values of the `df` DataFrame based on the `'Store'` column, then select the `'Weekly_Sales'` column, calculate sum values across groups, and reset the indexes. Save the result within the `data` variable.
2. Initialize a bar plot. Use the `'Store'` column values of `data` for the x-axis, `'Weekly_Sales'` for the y-axis, and make bars `'blue'`.