shape: (7, 2)
| Day | Sales |
|---|---|
| str | i64 |
| "Mon" | 182 |
| "Tue" | 247 |
| "Wed" | 547 |
| "Thur" | 481 |
| "Fri" | 319 |
| "Sat" | 208 |
| "Sun" | 67 |
Calculating cumulative sum in polars
pl.cum_sum
100DaysOfPolars
Say you have a target you want to hit for your weekly sales total, and you also want to know how close you are to hitting that target with each passing day. It turns out there’s a way to perform that calculation in Polars. Below is a dataframe containing daily sales.
Calculate cumulative sum
In Polars, you use the expression pl.cum_sum to add the next number to the sum of the previous numbers. Here’s how to do it:
(df
.with_columns(Cum_Sales=pl.col('Sales').cum_sum())
)
shape: (7, 3)
| Day | Sales | Cum_Sales |
|---|---|---|
| str | i64 | i64 |
| "Mon" | 182 | 182 |
| "Tue" | 247 | 429 |
| "Wed" | 547 | 976 |
| "Thur" | 481 | 1457 |
| "Fri" | 319 | 1776 |
| "Sat" | 208 | 1984 |
| "Sun" | 67 | 2051 |
So, if you had a target of $2,000 by the end of the week, you’d know by Friday that you’re not too far from hitting that target.
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