Pandas to D3. Serializing dataframes to JSON

Question

I have a DataFrame with the following columns and no duplicates:

['region', 'type', 'name', 'value']

that can be seen as a hierarchy as follows

grouped = df.groupby(['region','type', 'name'])

I would like to serialize this hierarchy as a JSON object.

If anyone is interested, the motivation behind this is to eventually put together a visualization like this one which requires a JSON file.

To do so, I need to convert grouped into the following:

new_data['children'][i]['name'] = region
new_data['children'][i]['children'][j]['name'] = type
new_data['children'][i]['children'][j]'children'][k]['name'] = name
new_data['children'][i]['children'][j]'children'][k]['size'] = value
...

where region, type, name correspond to different levels of the hierarchy (indexed by i, j and k)

Is there an easy way in Pandas/Python to do this?

score 3 · Accepted Answer · edited May 23 '17 at 12:01

Something along these lines might get you there.

from collections import defaultdict

tree = lambda: defaultdict(tree)  # a recursive defaultdict
d = tree()
for _, (region, type, name, value) in df.iterrows():
    d['children'][region]['name'] = region
    ...

json.dumps(d)

A vectorized solution would be better, and maybe something that takes advantage of the speed of groupby, but I can't think of such a solution.

Also take a look at df.groupby(...).groups, which return a dict.

Pandas to D3. Serializing dataframes to JSON

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