[FIXED] Converting table directly to tree structure with pandas

Issue

I want to convert this csv file Format:

into a hdf5 file with this structure:

I am using Pandas. Is there a simple way to do that?

Solution

You can use nested dictionaries via collections.defaultdict for this:

from collections import defaultdict
import pandas as pd

# read csv file
# df = pd.read_csv('input.csv', header=None)

df = pd.DataFrame([['A', 'a', 'a1'],
                   ['A', 'a', 'a2'],
                   ['A', 'b', 'b1'],
                   ['A', 'b', 'b2'],
                   ['A', 'c', 'c1'],
                   ['A', 'c', 'c2']],
                  columns=['col1', 'col2', 'col3'])

d = defaultdict(lambda: defaultdict(list))

for row in df.itertuples():
    d[row[1]][row[2]].append(row[3])

Result

defaultdict(<function __main__.<lambda>>,
            {'A': defaultdict(list,
                         {'a': ['a1', 'a2'],
                          'b': ['b1', 'b2'],
                          'c': ['c1', 'c2']})})

Answered By - jpp