A quick script to parse the (now deprecated) member counts data (memberCounts.csv) into "memberCountsHistorical.csv" that will be used to populate the chart in the site, and updated to include the current count data. The input file has a record of every date, while the output has month/year dates paired with running total for each.

generate_counts.py

import pandas

# This script will parse the historical data,
# and return a lookup of monthly dates with counts.

df = pandas.read_csv('memberCounts.csv')
counts = dict()

# Put dates and counts for each into lookup
for date in df['date'].tolist():
    date = date.split('/')
    date = "%s/%s" %(date[0], date[-1])  # month / year
    if date not in counts:
        counts[date] = 0
    counts[date]+=1

# Update to be a running total    
total = 0
for date, count in counts.items():
    total = total + count
    counts[date] = total

# Save to csv
with open('memberCountsHistorical.csv', 'w') as filey: 
    filey.write('date,total\n') 
    for date, count in counts.items(): 
        filey.write('%s,%s\n' %(date, count)) 

memberCounts.csv