I have reviewed all the posts that refer to this problem, even the explanation that DQ has in relation to this problem I have read it coming to a point of zero ideas.
autos["date_crawled"] = autos["date_crawled"].str[:10].copy()
What I expected to happen:
2016-03-26 17:47:46 data and re-asign again into
autos["date_crawled"] in this format
What actually happened:
I get solution BUT still the warning so this is not aver nice practice
/dataquest/system/env/python3/lib/python3.4/site-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy if __name__ == '__main__':
What I did?
`autos.loc["date_crawled"] = autos.loc["date_crawled"].str[:10]`
`autos.iloc[:,0] = autos.iloc[:,0].str[:10]`
`A = autos["date_crawled"].str[:10]`
`autos.loc["date_crawled"] = A.copy()`
The idea, as the dq document says, is to recognize chained indexing and avoid it at all costs, but so far I don’t see it.
Again thousan times thx
autos a dataframe you get by reading in the .csv file as it is? Or have you done some transformation like
autos = autos[boolean_mask]?
I’ve done something but I’m not sure to answer you in a precise way
I want to send you the file so I don’t make you dizzy.
I would say that all the time I am with the original csv but as I say I prefer that you take a look at the document and so we just confirm it, I am not 100% sure.
Challengue.ipynb (275.3 KB)
Click here to view the jupyter notebook file in a new tab
Ok, I´ve got two pieces of news: a good and a bad one
The good one - I found where you have to set a copy in order to avoid further SettingWithCopyWarning. The cell
In  :
autos = autos[autos["price_Dollars"].between(2,3890000)]
If you set copy (
.copy()) here, then it won’t raise warning later on.
The bad one - I´m really confused why it causes SettingWithCopyWarning in your project and it doesn´t in mine, although I used the same technique to deal with price outliers. I even tried a piece of my code which creates a new column in your project and it raised the Warning while it works perfectly fine in my project
Two days later good news is good news, the truth is that I would never have gotten there.
The one that is not so good is indeed more strange because I downloaded the work of a girl who did that movement of copying the dataframe on itself and did not give any alert.(!)
While I am writing these words I will export the csv online from the platform (hope works) and work locally on mine anaconda that I have here to see how it behaves.
Another thing in case it doesn’t work will be to compare with the girl’s work what steps she took and I didn’t, basically to rule out.
I thank you for the work you have done, if I could do more than give you a I would invite you for a
Thanks again for the analysis, you have helped me a lot,
You are welcome!
I understand you what a relief to get the solution after 2 days of struggling
Yes, you got it right.
The sun is shining again.
I hope I can help you next time, it will be a good sign.