CSV到Python中的嵌套词典（无熊猫）

Question

I have a CSV that I'd like to process into a nested dictionary, by grouping based upon values in the columns. It is formatted as follows:

sample, date, depth, analyte, result
'ABC', '01/01/2018', '3', 'LEAD', 0.22
'ABC', '02/01/2018', '3', 'LEAD', 0.25
'ABC', '01/01/2018', '5', 'LEAD', 0.19
'ABC', '02/01/2018', '5', 'LEAD', 0.18
'ABC', '01/01/2018', '3', 'MERCURY', 0.97
'ABC', '02/01/2018', '3', 'MERCURY', 0.95
'ABC', '01/01/2018', '5', 'MERCURY', 0.34
'ABC', '02/01/2018', '5', 'MERCURY', 0.11
'DEF', '01/01/2018', '3', 'LEAD', 0.07
'DEF', '02/01/2018', '3', 'LEAD', 0.04
'DEF', '01/01/2018', '5', 'LEAD', 0.16
'DEF', '02/01/2018', '5', 'LEAD', 0.65
'DEF', '01/01/2018', '3', 'MERCURY', 0.03
'DEF', '02/01/2018', '3', 'MERCURY', 0.01
'DEF', '01/01/2018', '5', 'MERCURY', 0.11
'DEF', '02/01/2018', '5', 'MERCURY', 0.13

I'd like my final dictionary to look like:
dictionary = {sample: {date: {depth: [analyte, result], [analyte, result] ... }}}

I'm hoping I could then iterate through the dictionary to access each block of unique results, by entering something like:
dictionary[sample][date][depth]

For example:
dictionary['ABC']['01/01/2018']['5'] = [['LEAD', 0.19], ['MERCURY', 0.34]]

I'd like to avoid using Pandas, although I know it may be well suited to accomplish the task - I'm looking for a Pythonic solution. It's difficult - because I have to accommodate multiple samples, multiple dates, multiple depths, and multiple analytes. I'm a beginner, and the nested loops that I've tried have fried my brain.

Any help is appreciated..

Answer 1

This is one solution using csv.DictReader and collections.defaultdict . You can define a specific nested dictionary structure. Then iterate once over your input file, adding items for each dictionary resulting from DictReader .

Using a similar method you can also opt for a dictionary with tuple keys. This will be more efficient for lookups but make iteration more cumbersome.

from collections import defaultdict
import csv

d = defaultdict(lambda: defaultdict(lambda: defaultdict(list)))

with open('file.csv', 'r') as fin:

    reader = csv.DictReader(fin, quotechar="'", skipinitialspace=True)

    for i in reader:
        d[i['sample']][i['date']][i['depth']].append([i['analyte'], float(i['result'])])

Result

print(d)

defaultdict({'ABC': defaultdict({'01/01/2018': defaultdict(list,
                                      {'3': [['LEAD', 0.22], ['MERCURY', 0.97]],
                                       '5': [['LEAD', 0.19], ['MERCURY', 0.34]]}),
                                 '02/01/2018': defaultdict(list,
                                      {'3': [['LEAD', 0.25], ['MERCURY', 0.95]],
                                       '5': [['LEAD', 0.18], ['MERCURY', 0.11]]})}),
             'DEF': defaultdict({'01/01/2018': defaultdict(list,
                                      {'3': [['LEAD', 0.07],
                                ....