This guide details how to connect to a C3 cluster, search for data you want to use,
fetch that data, and convert it into a form that you can easily analyze.
Install Jupyter Notebook & Connect to the C3 Container
Using Browser to Connect to the C3 Suite
Step 1: Connecting to the C3 Cluster
Step 2:
Data Fetching Documentations if you are:
A Code Example in Jupyter Notebook:
from c3python import get_c3 raw_df = c3.BlockInfo.fetch(spec={ 'limit': -1, 'filter': 'exists(prp_bf_lr)', 'order': 'descending(id)', 'include': 'pct_i_l,pct_t_l,prp_res_lr,pop10_ha_lr,hu10_ha_lr,eroom_ha_lr,med10_age,prp_bf_lr' }) |
A Code Example in Jupyter Notebook:
## continue from above ## import pandas as pd df = pd.DataFrame(raw_df.objs.toJson()) df.head() df.drop('meta', axis=1, inplace=True) df.drop('type', axis=1, inplace=True) df.drop('version', axis=1, inplace=True) df.drop('id', axis=1, inplace=True) df.head() |
Users can operations like after you convert the c3 Dataset into the pandas dataframe.
TODO:
Code example using both Python and JS: https://developer.c3.ai/docs/7.12.0/topic/mlpipe-code-examples#construct-tensorflowpipe