Question

I am making a Python script that parses an Excel file using the xlrd library.
What I would like is to do calculations on different columns if the cells contain a certain value. Otherwise, skip those values. Then store the output in a dictionary.
Here’s what I tried to do :

import xlrd


workbook = xlrd.open_workbook('filter_data.xlsx')
worksheet = workbook.sheet_by_name('filter_data')

num_rows = worksheet.nrows -1
num_cells = worksheet.ncols - 1

first_col = 0
scnd_col = 1
third_col = 2

# Read Data into double level dictionary
celldict = dict()
for curr_row in range(num_rows)  :

    cell0_val = int(worksheet.cell_value(curr_row+1,first_col))
    cell1_val = worksheet.cell_value(curr_row,scnd_col)
    cell2_val = worksheet.cell_value(curr_row,third_col)

    if cell1_val[:3] == 'BL1' :
        if cell2_val=='toSkip' :
        continue
    elif cell1_val[:3] == 'OUT' :
        if cell2_val == 'toSkip' :
        continue
    if not cell0_val in celldict :
        celldict[cell0_val] = dict()
# if the entry isn't in the second level dictionary then add it, with count 1
    if not cell1_val in celldict[cell0_val] :
        celldict[cell0_val][cell1_val] = 1
        # Otherwise increase the count
    else :
        celldict[cell0_val][cell1_val] += 1

So here as you can see, I count the number of “cell1_val” values for each “cell0_val”. But I would like to skip those values which have “toSkip” in the adjacent column’s cell before doing the sum and storing it in the dict.
I am doing something wrong here, and I feel like the solution is much more simple.
Any help would be appreciated. Thanks.

Here’s an example of my sheet :

cell0 cell1  cell2
12    BL1    toSkip
12    BL1    doNotSkip
12    OUT3   doNotSkip
12    OUT3   toSkip
13    BL1    doNotSkip
13    BL1    toSkip
13    OUT3   doNotSkip

Answer 1

Use collections.defaultdict with collections.Counter for your nested dictionary.

Here it is in action:

>>> from collections import defaultdict, Counter
>>> d = defaultdict(Counter)
>>> d['red']['blue'] += 1
>>> d['green']['brown'] += 1
>>> d['red']['blue'] += 1
>>> pprint.pprint(d)
{'green': Counter({'brown': 1}),
 'red': Counter({'blue': 2})}

Here it is integrated into your code:

from collections import defaultdict, Counter
import xlrd

workbook = xlrd.open_workbook('filter_data.xlsx')
worksheet = workbook.sheet_by_name('filter_data')

first_col = 0
scnd_col = 1
third_col = 2

celldict = defaultdict(Counter)
for curr_row in range(1, worksheet.nrows): # start at 1 skips header row

    cell0_val = int(worksheet.cell_value(curr_row, first_col))
    cell1_val = worksheet.cell_value(curr_row, scnd_col)
    cell2_val = worksheet.cell_value(curr_row, third_col)

    if cell2_val == 'toSkip' and cell1_val[:3] in ('BL1', 'OUT'):
        continue

    celldict[cell0_val][cell1_val] += 1

I also combined your if-statments and changed the calculation of curr_row to be simpler.