Reading in a file with Google datalab

问题:

I am trying to use Google Datalab to read in a file in ipython notebook, the basic pd.read_csv() as I can't find the path of the file. I have it locally and also uploaded it to google cloud storage in a bucket.

I ran the following commands to understand where I am

os.getcwd()

gives '/content/[e-mail]'

os.listdir('/content/[e-mail]')

gives ['.git', '.gitignore', 'datalab', 'Hello World.ipynb', '.ipynb_checkpoints']

回答1:

The following reads the contents of the object into a string variable called text:

%%storage read --object "gs://path/to/data.csv" --variable text

Then

from cStringIO import StringIO
mydata = pd.read_csv(StringIO(text)) 
mydata.head()

Hopefully Pandas will support "gs://" URLs (as it does for s3:// currently to allow reading directly from Google Cloud storage.

I have found the following docs really helpful:

https://github.com/GoogleCloudPlatform/datalab/tree/master/content/datalab/tutorials

Hope that helps (just getting started with Datalab too, so maybe someone will have a cleaner method soon).

回答2:

You can also run BigQuery queries directly against CSV files in Cloud Storage by creating a FederatedTable wrapper object. That is described here:

https://github.com/GoogleCloudPlatform/datalab/blob/master/content/datalab/tutorials/BigQuery/Using%20External%20Tables%20from%20BigQuery.ipynb