pandasIO for Google BigQuery

Reading data from BigQuery with user account credentials

In [1]: import pandas as pd

In order to run a query in BigQuery you need to have your own BigQuery project. We can request some public sample data:

In [2]: data = pd.read_gbq('''SELECT title, id, num_characters
   ...:                       FROM [publicdata:samples.wikipedia]
   ...:                       LIMIT 5'''
   ...:                    , project_id='<your-project-id>')

This will print out:

Your browser has been opened to visit:

    https://accounts.google.com/o/oauth2/v2/auth...[looong url cutted]

If your browser is on a different machine then exit and re-run this
application with the command-line parameter

  --noauth_local_webserver

If your are operating from local machine than browser will pop-up. After granting privileges pandas will continue with output:

Authentication successful.
Requesting query... ok.
Query running...
Query done.
Processed: 13.8 Gb

Retrieving results...
Got 5 rows.

Total time taken 1.5 s.
Finished at 2016-08-23 11:26:03.

Result:

In [3]: data
Out[3]: 
               title       id  num_characters
0       Fusidic acid   935328            1112
1     Clark Air Base   426241            8257
2  Watergate scandal    52382           25790
3               2005    35984           75813
4               .BLP  2664340            1659

As a side effect pandas will create json file bigquery_credentials.dat which will allow you to run further queries without need to grant privileges any more:

In [9]: pd.read_gbq('SELECT count(1) cnt FROM [publicdata:samples.wikipedia]'
                   , project_id='<your-project-id>')
Requesting query... ok.
[rest of output cutted]

Out[9]: 
         cnt
0  313797035

Reading data from BigQuery with service account credentials

If you have created service account and have private key json file for it, you can use this file to authenticate with pandas

In [5]: pd.read_gbq('''SELECT corpus, sum(word_count) words
                       FROM [bigquery-public-data:samples.shakespeare]       
                       GROUP BY corpus                                
                       ORDER BY words desc
                       LIMIT 5'''
                   , project_id='<your-project-id>'
                   , private_key='<private key json contents or file path>')
Requesting query... ok.
[rest of output cutted]

Out[5]: 
           corpus  words
0          hamlet  32446
1  kingrichardiii  31868
2      coriolanus  29535
3       cymbeline  29231
4    2kinghenryiv  28241