Timeline for What makes Python better suited to quant finance than Matlab / Octave, Julia, R and others?
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| S Oct 1 at 15:24 | history | suggested | uhoh | CC BY-SA 4.0 |
OMG Ernie's name is Ernest, not Ernst!
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| Oct 1 at 15:17 | review | Suggested edits | |||
| S Oct 1 at 15:24 | |||||
| Oct 1 at 15:15 | history | edited | Sane | CC BY-SA 4.0 |
added 12 characters in body
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| S Jul 8 at 9:47 | history | suggested | uhoh | CC BY-SA 4.0 |
add a link to the publication itself and adjust formatting
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| Jul 8 at 9:29 | review | Suggested edits | |||
| S Jul 8 at 9:47 | |||||
| Jul 8 at 7:46 | comment | added | Sane | I have added citation, please check above. | |
| Jul 8 at 7:45 | history | edited | Sane | CC BY-SA 4.0 |
added 87 characters in body
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| Jul 5 at 9:07 | comment | added | ojdo | Exactly this. The "not an island" factor + that it nearly is as user-friendly and feature-rich as purpose-built languages just makes it an outright win. Then add some years and you end up where we're now. | |
| Jul 4 at 16:45 | comment | added | lehalle | I fully agree, I would just add that one of the strength of python is that it interacts very naturally with software environment, that is crucial for MLops or devOps. It is probably one of the reasons of is success. | |
| Jul 4 at 14:26 | comment | added | Frido | Exactly my thoughts (re Matlab). Octave is its open source clone and has less support obviously, but a great set of packages and the same functionality. I'm still a bit perplexed why it's under-utilized. | |
| Jul 4 at 14:21 | history | answered | Sane | CC BY-SA 4.0 |