Cumulative sum vs .diff()
In the video, you have learned about expanding windows that allow you to run cumulative calculations.
The cumulative sum method has in fact the opposite effect of the .diff()
method that you came across in chapter 1.
To illustrate this, let's use the Google stock price time series, create the differences between prices, and reconstruct the series using the cumulative sum.
This is a part of the course
“Manipulating Time Series Data in Python”
Exercise instructions
We have already imported pandas
as pd
and matplotlib.pyplot
as plt
. We have also loaded google stock prices into the variable data
- Apply
.diff()
todata
, drop missing values, and assign the result todifferences
. - Use
.first('D')
to select the first price fromdata
, and assign it tostart_price
. - Use
.append()
to combinestart_price
anddifferences
, apply.cumsum()
and assign this tocumulative_sum
. - Use
.equals()
to comparedata
andcumulative_sum
, and print the result.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate differences
differences = ____
# Select start price
start_price = ____
# Calculate cumulative sum
cumulative_sum = ____
# Validate cumulative sum equals data
print(____)