How To Calculate The Steepness Of A Trend In Python

I am using the regression slope as follows to calculate the steepness (slope) of the trend. Scenario 1: For example, consider I am using sales figures (x-axis: 1, 4, 6, 8, 10, 15)

Solution 1:

I believe the problem is your variables are switched. If you want to track sales performance over time, you should perform the regression the other way around. You can invert the slopes you've calculated to get the correct values, which will show higher sales performance in case 1.

1 / 0.377 = 2.65

Here is a visualization of your data:

import matplotlib.pyplot as plt

days = [1,2,3,4,5,6]
sales1 = [1,4,6,8,10,15]
sales2 = [1,2,3,4,5,6]

df = pd.DataFrame({'days': days, 'sales1': sales1, 'sales2': sales2})
df = df.set_index('days')
df.plot(marker='o', linestyle='--')