["python","python-2.7","dictionary","mapping","nested"]
How do you create nested dict in Python?

I have 2 CSV files: 'Data' and 'Mapping': 'Mapping' file has 4 columns: Device_Name, GDN, Device_Type, and Device_OS. All four columns are populated. 'Data' file has these same columns, with Device_Name column populated and the other three columns blank. I want my Python code to open both files and for each Device_Name in the Data file, map its GDN, Device_Type, and Device_OS value from the Mapping file. I know how to use dict when only 2 columns are present (1 is needed to be mapped) but I don't know how to accomplish this when 3 columns need to be mapped. Following is the code using which I tried to accomplish mapping of Device_Type: x = dict([]) with open("Pricing Mapping_2013-04-22.csv", "rb") as in_file1: file_map = csv.reader(in_file1, delimiter=',') for row in file_map: typemap = [row[0],row[2]] x.append(typemap) with open("Pricing_Updated_Cleaned.csv", "rb") as in_file2, open("Data Scraper_GDN.csv", "wb") as out_file: writer = csv.writer(out_file, delimiter=',') for row in csv.reader(in_file2, delimiter=','): try: row[27] = x[row[11]] except KeyError: row[27] = "" writer.writerow(row) It returns Attribute Error. After some researching, I think I need to create a nested dict, but I don't have any idea how to do this.
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 type defaultdict(<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) instead for 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: I have 2 files a.csv b.csv, a.csv has 4 columns i j k l, b.csv also has these columns. i is kind of key columns for these csvs'. j k l column is empty in a.csv but populated in b.csv. I want to map values of j k l 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.csv with 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.csv with 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.