Timeline for How to apply .replace() inside a column in a pandas data frame to clean data
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| May 20, 2021 at 14:16 | vote | accept | The Dan | ||
| Apr 15, 2020 at 0:21 | history | edited | nwaldo | CC BY-SA 4.0 |
added 64 characters in body
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| Apr 15, 2020 at 0:13 | history | edited | nwaldo | CC BY-SA 4.0 |
Improved answer to included code
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| Apr 14, 2020 at 18:27 | comment | added | nwaldo | See if this might do the trick. import re; df_clean2['product_ranking'].map(lambda x: float(re.sub('[,\s]*' , '', x))) | |
| Apr 14, 2020 at 18:25 | comment | added | The Dan | There shouldn't be other types of variables. Actually those values are supposed to be only integers | |
| Apr 14, 2020 at 18:13 | comment | added | The Dan | Some of them are in the correct format, the errors I have found come form commas and dots | |
| Apr 14, 2020 at 18:06 | comment | added | The Dan | Sure! there you have some code, there is the line that gives the error | |
| Apr 14, 2020 at 17:19 | history | answered | nwaldo | CC BY-SA 4.0 |