Takes Aeon reader in/out data and caculcates the maximum number of readers

maxReaders.py

import json
import csv
import os

#function that takes a series of data formatted date, start time, end time and returns max simultaneous calls
def maximumOverlap(calls):
    times = []
    for call in calls:
        
        date, startTime, endTime = call
        times.append((startTime, 'start'))
        times.append((endTime, 'end'))
    times = sorted(times)

    count = 0
    maxCount = 0
    for time in times:
        if time[1] == 'start':
            count += 1    # increment on arrival/start
        else:
            count -= 1    # decrement on departure/end
        maxCount = max(count, maxCount)  # maintain maximum
    return date, maxCount


# calls a directory of text files 
# files should be csvs formatted as date, start time, end time
# loop through each file, and pull data into an array

directory = 'C:\Users\Kevin\Desktop\maxReaders\source'

for filename in os.listdir(directory):
    if filename.endswith(".txt"):
        f = open(filename)
        calls = []
        with open(filename) as csvfile:
            reader = csv.reader(csvfile, quoting=csv.QUOTE_NONNUMERIC) # change contents to floats
            for row in reader: # each row is a list
                calls.append(row)
#call function
        print(maximumOverlap(calls))
        continue
    else:
    	continue

readerCount.txt

NB: Very manual, file names and paths hardcoded, etc.  

1) Start with a spreadsheet like this of reader in/out times:

Date	Time In	Date	Time Out
10/31/2017	1:22 PM	10/31/2017	1:28:00 PM
10/31/2017	1:23 PM	10/31/2017	1:29:00 PM
10/31/2017	1:28 PM	10/31/2017	8:45:00 PM
10/31/2017	1:29 PM	10/31/2017	8:45:00 PM
10/31/2017	1:43 PM	10/31/2017	6:08:00 PM

2) Converted to numbers and removed third column, save as .csv file

Date		Time In		Time Out
43039	,	0.556944444	,	0.561111111
43039	,	0.557638889	,	0.561805556
43039	,	0.561111111	,	0.864583333
43039	,	0.561805556	,	0.864583333

3) Run splitter.py (below) across the csv, resulting in one .txt file for each date formatted like this:
43039	,	0.556944444	,	0.561111111

4) Run maxReaders.py (below)

5) Copy output, paste into Excel, and convert back to human-readable date:
Date	Max readers
Monday, November 06, 2017	24
Thursday, August 09, 2018	23
Friday, April 20, 2018	22
Friday, April 13, 2018	21
Tuesday, June 26, 2018	21

splitter.py

import csv
from itertools import groupby

for key, rows in groupby(csv.reader(open("foo.csv")),
                         lambda row: row[0]):
    with open("%s.txt" % key, "w") as output:
        for row in rows:
            output.write(",".join(row) + "\n")