-
Notifications
You must be signed in to change notification settings - Fork 112
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
prep.py Error #30
Comments
Same, any one can fix this problem? |
Clearly the data source is no longer supported. Does anyone know an alternate source to use for the data? Or equivalent data to download? |
I don't personally know of a good place to download this data, but I wouldn't be surprised if one exists. The dask repository now includes a |
I also wanted to try this tutorial, but couldn't get the data:
How big is the data that was downloaded by Would be great to have this tutorial working.... |
I agree that putting the data into the repository is possible. Unfortunately I no longer know how to obtain the data. My recommendation that someone rework the examples to use the |
@minrk - maybe you still have a copy of the files around?
I could try tomorrow. But to me, bundling example data in the tutorial repo seems like the better solution if it's small, to increase chances of it working in the future. |
dask.datasets.timeseries produces random data using the numpy.random module. It's definitely as robust as packaging data, and has the benefit of working over conference wifi. I think it's ok to have a few megabytes of data here, but we need to expect this tutorial to be run over very poor internet connections. Anything over a few tens of megabytes is unpleasant. |
In order to even get to the google error I've set dask=0.20.2 and pandas =0.22 in the environment.yml file. Dask ran into the same issue as @cdeil reported, and pandas reported the following exception:
|
It seems that google have updated their API, so when running prep.py it raises a remote error:
raise RemoteDataError('Unable to read URL: {0}'.format(url)) pandas_datareader._utils.RemoteDataError: Unable to read URL: http://www.google. com/finance/historical?q=usb&startdate=Jan+27%2C+2017&enddate=Jan+27%2C+2018&out put=csv
Is there a way the offline versions of JSON files could be made available?
The text was updated successfully, but these errors were encountered: