Timeline for Faster way of replacing strings in large pandas dataframe with regex
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| Nov 24, 2017 at 12:54 | comment | added | Zulfiqaar | well isnt that neat, another 20% faster. fantastic :) | |
| Nov 24, 2017 at 12:51 | comment | added | Ludisposed |
I I have changed it slightly to x.lower() doing str.lower(x) is not the correct format
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| Nov 24, 2017 at 12:49 | history | edited | Ludisposed | CC BY-SA 3.0 |
deleted 2 characters in body
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| Nov 24, 2017 at 12:47 | comment | added | Zulfiqaar |
thank you very much, this has sped it up by ~6 times. for posterity, i had to change it to str.lower(x), but otherwise its perfect. there are a few edge cases where i will have to use the other methods, but this should work for the vast bulk of the data. have a good day!
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| Nov 24, 2017 at 12:47 | vote | accept | Zulfiqaar | ||
| Nov 24, 2017 at 12:29 | history | edited | Ludisposed | CC BY-SA 3.0 |
added 82 characters in body
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| Nov 24, 2017 at 12:13 | history | answered | Ludisposed | CC BY-SA 3.0 |