There comes a time when you want to extract every other row from your DataFrame. What I mean is: get the first row, skip the second, get the third, skip the fourth, and so on.
Say you have the dataframe below:
shape: (10, 3)
| str |
date |
str |
| "Pilot" |
2011-06-23 |
"Kevin Bray" |
| "Errors and Omissions" |
2011-06-30 |
"John Scott" |
| "Inside Track" |
2011-07-07 |
"Kevin Bray" |
| "Dirty Little Secrets" |
2011-07-14 |
"Dennie Gordon" |
| "Bail Out" |
2011-07-21 |
"Kate Woods" |
| "Tricks of the Trade" |
2011-07-28 |
"Terry McDonough" |
| "Play the Man" |
2011-08-04 |
"Tim Matheson" |
| "Identity Crisis" |
2011-08-11 |
"Norberto Barba" |
| "Undefeated" |
2011-08-18 |
"Felix Alcala" |
| "Shelf Life" |
2011-08-25 |
"Jennifer Getzinger" |
And you want to select every odd-numbered row—like the first, third, fifth, etc.
I remember writing overly complex code with lambda functions just to achieve this.
Getting every other row with polars
With Polars, you don’t have to torture yourself writing convoluted Python code. The gather_every function does exactly that.
shape: (5, 3)
| str |
date |
str |
| "Pilot" |
2011-06-23 |
"Kevin Bray" |
| "Inside Track" |
2011-07-07 |
"Kevin Bray" |
| "Bail Out" |
2011-07-21 |
"Kate Woods" |
| "Play the Man" |
2011-08-04 |
"Tim Matheson" |
| "Undefeated" |
2011-08-18 |
"Felix Alcala" |
Isn’t that cool?
Even cooler ways to use Polars in my Polars course!