Timeline for Insert a row to pandas dataframe
Current License: CC BY-SA 4.0
29 events
| when toggle format | what | by | license | comment | |
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| May 14 at 13:28 | answer | added | mins | timeline score: 1 | |
| Apr 28, 2023 at 14:46 | history | protected | cs95 | ||
| Sep 8, 2022 at 15:06 | comment | added | Yakov Galka | @ciaranhaines I find pandas and numpy being just bandaids for the fact that python being a (very slow) interpreted language. There's only a handful of 'optimized' building blocks that they provide, versus the infinite scope of potential problems I regularly face. I spend countless time finding the right combination of those primitives that would do what I need, and more often than not I figure out that there isn't one. I can write an unvectorized loop to do the same in a fraction of my time, but it will run slow. Python is good only as a prototyping language. | |
| Aug 2, 2022 at 10:25 | comment | added | ciaran haines | @MattCochrane - Almost every time that I have found Pandas to be slow, I have found a different pandas method that is much faster later on or realised I was doing things weirdly backward. I find a lot of database functions like how you describe -I think that's due to the way database theory works, not down to Pandas specifically. I'm aware that there are other more specialised libraries that are faster for specific purposes, but few that do as much as broadly well as Pandas. If you / anyone has an alternate suggestion, I'd love to hear it! | |
| Jul 31, 2022 at 7:42 | answer | added | Muhammad Yasirroni | timeline score: 2 | |
| Jun 8, 2022 at 14:56 | answer | added | ZTang | timeline score: 1 | |
| Apr 21, 2022 at 14:35 | answer | added | Xin Niu | timeline score: 0 | |
| Apr 5, 2022 at 11:26 | answer | added | Alessio Pan | timeline score: 4 | |
| Sep 9, 2021 at 13:18 | answer | added | Ehsan Akbaritabar | timeline score: 1 | |
| May 24, 2021 at 21:06 | answer | added | kovashikawa | timeline score: 88 | |
| Feb 15, 2021 at 8:10 | answer | added | Steven | timeline score: 3 | |
| May 18, 2020 at 13:42 | answer | added | M. Viaz | timeline score: 3 | |
| Apr 28, 2020 at 9:21 | answer | added | Pepe | timeline score: -3 | |
| Apr 28, 2020 at 8:11 | answer | added | Pepe | timeline score: 13 | |
| Apr 15, 2020 at 3:16 | answer | added | Xinyi Li | timeline score: 1 | |
| Dec 11, 2019 at 3:54 | history | edited | smci | CC BY-SA 4.0 |
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| Jul 10, 2019 at 19:14 | answer | added | Aaron Melgar | timeline score: 8 | |
| Apr 8, 2019 at 4:16 | answer | added | Sagar Rathod | timeline score: 7 | |
| Jan 15, 2018 at 23:09 | answer | added | Tai | timeline score: 15 | |
| Sep 21, 2017 at 22:34 | answer | added | elPastor | timeline score: 22 | |
| Aug 2, 2017 at 9:27 | comment | added | MattCochrane | I don't understand why everyone loves pandas so much when something that should be so simple is such a pain in the ass and so slow. | |
| Sep 9, 2014 at 22:00 | history | edited | BenMorel | CC BY-SA 3.0 |
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| Jun 23, 2014 at 0:56 | audit | Suggested edits | |||
| Jun 23, 2014 at 0:56 | |||||
| Jun 18, 2014 at 13:56 | comment | added | acushner |
note that it's better to use s1.values as opposed to list(s1) as you will be creating an entirely new list using list(s1).
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| Jun 18, 2014 at 13:42 | answer | added | mgilbert | timeline score: 75 | |
| Jun 18, 2014 at 11:44 | answer | added | Piotr Migdal | timeline score: 272 | |
| Jun 18, 2014 at 11:38 | history | edited | Meloun | CC BY-SA 3.0 |
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| Jun 18, 2014 at 11:36 | answer | added | FooBar | timeline score: 32 | |
| Jun 18, 2014 at 11:27 | history | asked | Meloun | CC BY-SA 3.0 |