How do you create nested dict in Python?

A nested dict is a dictionary within a dictionary. A very simple thing.

>>> d = {}>>> d['dict1'] = {}>>> d['dict1']['innerkey'] = 'value'>>> d['dict1']['innerkey2'] = 'value2'>>> d{'dict1': {'innerkey': 'value', 'innerkey2': 'value2'}}

You can also use a defaultdict from the collections package to facilitate creating nested dictionaries.

>>> import collections>>> d = collections.defaultdict(dict)>>> d['dict1']['innerkey'] = 'value'>>> d  # currently a defaultdict typedefaultdict(<type 'dict'>, {'dict1': {'innerkey': 'value'}})>>> dict(d)  # but is exactly like a normal dictionary.{'dict1': {'innerkey': 'value'}}

You can populate that however you want.

I would recommend in your code something like the following:

d = {}  # can use defaultdict(dict) insteadfor row in file_map:    # derive row key from something     # when using defaultdict, we can skip the next step creating a dictionary on row_key    d[row_key] = {}     for idx, col in enumerate(row):        d[row_key][idx] = col

According to your comment:

may be above code is confusing the question. My problem in nutshell: Ihave 2 files a.csv b.csv, a.csv has 4 columns i j k l, b.csv also hasthese columns. i is kind of key columns for these csvs'. j k l columnis empty in a.csv but populated in b.csv. I want to map values of j kl columns using 'i` as key column from b.csv to a.csv file

My suggestion would be something like this (without using defaultdict):

a_file = "path/to/a.csv"b_file = "path/to/b.csv"# read from file a.csvwith open(a_file) as f:    # skip headers    f.next()    # get first colum as keys    keys = (line.split(',')[0] for line in f) # create empty dictionary:d = {}# read from file b.csvwith open(b_file) as f:    # gather headers except first key header    headers = f.next().split(',')[1:]    # iterate lines    for line in f:        # gather the colums        cols = line.strip().split(',')        # check to make sure this key should be mapped.        if cols[0] not in keys:            continue        # add key to dict        d[cols[0]] = dict(            # inner keys are the header names, values are columns            (headers[idx], v) for idx, v in enumerate(cols[1:]))

Please note though, that for parsing csv files there is a csv module.

UPDATE: For an arbitrary length of a nested dictionary, go to this answer.

Use the defaultdict function from the collections.

High performance: "if key not in dict" is very expensive when the data set is large.

Low maintenance: make the code more readable and can be easily extended.

from collections import defaultdicttarget_dict = defaultdict(dict)target_dict[key1][key2] = val

For arbitrary levels of nestedness:

In [2]: def nested_dict():   ...:     return collections.defaultdict(nested_dict)   ...:In [3]: a = nested_dict()In [4]: aOut[4]: defaultdict(<function __main__.nested_dict>, {})In [5]: a['a']['b']['c'] = 1In [6]: aOut[6]:defaultdict(<function __main__.nested_dict>,            {'a': defaultdict(<function __main__.nested_dict>,                         {'b': defaultdict(<function __main__.nested_dict>,                                      {'c': 1})})})