Understanding and Implementing Data Frame Splitting based on Slope of Data

In this article, we will explore how to split a data frame into groups based on the slope of the data. We will use Python and the Pandas library for data manipulation.

Introduction to Slope Calculation

The slope of a data point is calculated by taking the difference between two consecutive points in the dataset. For example, if we have a dataset with values [5, 7, 5, 5, 5, 6, 3, 2, 0, 5], the slopes would be:

(7 - 5) / (1 - 0) = 2
(5 - 7) / (2 - 1) = -2
(5 - 5) / (3 - 2) = 0
(5 - 5) / (4 - 3) = 0
(5 - 5) / (5 - 4) = 0
(6 - 5) / (6 - 5) = 1

Implementing Slope Calculation using Pandas

We will start by creating a sample data frame with the entity column.

x = pd.DataFrame({'entity':[5,7,5,5,5,6,3,2,0,5]})

Next, we calculate the difference between consecutive points in the dataset and fill any missing values at the beginning with 0.

df['diff'] = df.entity.diff().bfill()

Then, we change all negative slopes to positive to make them easier to work with.

df.loc[df['diff'] < 0, 'diff'] = -1

Finding Groups Based on Slope

We create an empty list init and start a loop that checks each point in the dataset to see if it has the same slope as the previous point. If they do, we append the index of the previous point to init. If they don’t, we append the index of the current point plus 1 to init.

init = [0]
for x in df['diff'] == df['diff'].shift(1):
    if x:
        init.append(init[-1])
    else:
        init.append(init[-1]+1)

Finally, we create a new column g that contains the length of each group.

df['g'] = init[1:]

Understanding Group Lengths

Now that we have our data frame split into groups based on slope, let’s understand how to check the lengths of these groups. We can do this by simply looking at the values in the g column.

For example, if we look at the output below:

   entity  diff  g
0       5   2.0  1
1       7   2.0  1
2       5  -1.0  2
3       5   0.0  3
4       5   0.0  3
5       6   1.0  4
6       3  -1.0  5
7       2  -1.0  5
8       0  -1.0  5
9       5   5.0  6

We can see that the group lengths are: 1, 1, 2, 3, 3, 4, 5, 5, 5.

Conclusion

In this article, we have learned how to split a data frame into groups based on the slope of the data. We used Python and the Pandas library for data manipulation and implemented the necessary steps to achieve this task.

Last modified on 2025-03-26