Timeline for Generating a PANDAS DataFrame of simulated coin tosses
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jun 10, 2020 at 13:24 | history | edited | CommunityBot | Commonmark migration | |
| Oct 6, 2015 at 20:46 | answer | added | holroy | timeline score: 2 | |
| Oct 6, 2015 at 9:25 | answer | added | SuperBiasedMan | timeline score: 1 | |
| Oct 6, 2015 at 8:46 | history | edited | 200_success | CC BY-SA 3.0 | title according to site norms |
| Oct 6, 2015 at 8:11 | history | edited | SuperBiasedMan | edited tags | |
| Oct 5, 2015 at 20:15 | history | migrated | from stackoverflow.com (revisions) | ||
| Oct 5, 2015 at 3:52 | comment | added | jfs | to improve performance, use vectorized operations | |
| Oct 5, 2015 at 2:31 | comment | added | subhacom | Moving the local variable choices = [coin.HEADS, coin.TAILS to global scope gives slight performance improvement. However, since your loop counts are constants, I suspect operating on a single large array may be faster than an object oriented solution. | |
| Oct 5, 2015 at 1:35 | history | asked | compguy24 | CC BY-SA 3.0 |