Thanks for sharing your project with Dataquest community. The whole project look well organized with every workings nicely presented. The code lines are well worked and has thus rendered the required outputs, the comments and most of the explanations given are very informing . I love your visualization walkthrough, those graphs are very admiring , keep it mate for the good work.!
Have got few humble suggestions to make;
You haven’t provided the title and the/objectives of your project ,kindly check onto that.
It’s always advisable to provide the inks of the dataset you are working with for easy access by the reader, and also giving some information background about this dataset.
Providing the findings in summary way in the conclusion is always a good practice, and hope you will check onto it as well.
Otherwise , congratulations for the good presentation !
Thanks a lot for your recommendations and feedback.
I realized that I have not uploaded my final ipython notebook , but the last saving point before.
Meanwhile I addded the URL to the data set as recommended.
I just downloaded your work and you have given me an error!
/tmp/ipykernel_37129/1339988604.py:22: FutureWarning: Indexing a DataFrame with a datetimelike index using a single string to slice the rows, like frame[string], is deprecated and will be removed in a future version. Use frame.loc[string] instead.
grouped = euro_to_dollar[yr].groupby(pd.PeriodIndex(euro_to_dollar[yr].index, freq=“M”))[‘rolling_mean’]
Take a look at it, as it is a pity that the effort you have put in we cannot be seen. I would also recommend that you can do it in the following way:
So that if you want to see the result you do not have to download the ipynb and open anaconda in the first instance.
Thanks for the feedback, thanks to you I recognized that the automatic link to view the IPython Notebook was removed after I updated the post a first time.
Further I took care of the warning that you got on your loacal install, due to string-based-slicing of a dataframe that shoulde depricate soon. I hope this works now, as I was not able to reproduce the warning within the DataQuest platform environment…
Have a look and let me know if your issue was solved: