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Connecting to a C3 Cluster
TBDInstall Jupyter Notebook & Connect to the C3 Container
Getting
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the Documentation of the
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Internal Data Model
TODO:
Step 1: Connecting to the C3 Cluster
Step 2:
Fetching Instances of Types
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- Using Browser Developing Tools: https://developer.c3.ai/docs/7.12.0/guide/guide-c3aisuite-basic/di-monitoring-and-troubleshooting
- using Python Jupyter Notebook: https://developer.c3.ai/docs/7.12.0/topic/ds-jupyter-notebooks
A Code Example in Jupyter Notebook:
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import pandas as pd 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' }) df = pd.DataFrame(raw_df.objs.toJson()) df.head()## fetching all "BlockInfo" c3 type entries with field "prop_urban" >= 0.8 and field "med10_age" > 1990. c3Grid(BlockInfo.fetch({filter: "prop_urban >=0.8 && med10_age > 1990"})) |
Converting Fetch results to usable forms in Jupyter Notebook
TODO:
Executing Metrics on Time series data
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