Thank you, I now have
defaultdict(<class 'int'>, {736697: 10, 736677: 14, 736980: 9, 737109:
50, 736919: 15, 736652: 19, 736502: 14, 736710: 2, 736674: 6, 736672: 5,
736933: 2, 736932: 6, 736658: 7, 736671: 5, 736499: 6, 736707: 4,
737181: 4, 736686: 2, ...
where the first number is the proleptic Gregorian ordinal of the date
8-) ( I had to look up what proleptic meant)
This means I can access the elements by the ordinal of the date, for
later processing, and extraction to a spreadsheet
Dave
On 09/05/2019 04:08, Cameron Simpson wrote:
On 08May2019 21:04, Dave Hill <d...@the-hills.org.uk> wrote:
I have a csv file which details the results of equipment tests, I
carry out PAT testing as a volunteer at a heriatge railway in N.
Wales. I want to extract how many items were tested on each test day.
So far I have generated a List of test dates, but I am now stalled at
how to efficiently count numbers tested on each date.
Can I have a list of tuples, where one item is the date and the
second the count?
Not as such, because you can't modify a tuple (so you can't update the
count part). But you could use a 2 element list.
or is there a better construct?
Oh definitely. The easiest thing would be a defaultdict(int). Example:
from collections import defaultdict
...
by_date = defaultdict(int)
for row in csvdata:
timestamp = row[1] # based on your example data
# get the date from the timestamp
date = ...
by_date[date] += 1
A defaultdict is a dict which magicly makes missing elements when they
get access, using a factory function you supply. Here we're using
"int" as that factory, as int() returns zero.
I presume you've got the timestamp => date conversion sorted?
Cheers,
Cameron Simpson <c...@cskk.id.au>
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