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A Code Example in Jupyter Notebook:

from c3python import pandas as pdget_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'
})

Converting Fetch results to usable forms in Jupyter Notebook

A Code Example in Jupyter Notebook:

## inherited from previous section ##
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()

Converting Fetch results to usable forms in Jupyter Notebook

Image Added

Users can operations like after you convert the c3 Dataset into the pandas dataframe.TODO:

Executing Metrics on Time series data

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