Ugly To Pretty for CSVS

Run on linux. Set an import path and an export path to folders. Will take every file in import directory that is a mathematica generated CSV and turn it into a nicely fomatted CSV in Output directory.

Paths



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importpath = "/home/jwb/repos/github-research/csvs/Companies/Ugly/Stack/"
exportpath = "/home/jwb/repos/github-research/csvs/Companies/Pretty/Stack/"

Function



In [8]:

    
import csv
import pandas as pd
import os

def arrayer(path):
    with open(path, "rt") as f: 
        reader = csv.reader(f)
        names = set()
        times = {}
        windows = []
        rownum = 0
        for row in reader:
                newrow = [(i[1:-1],j[:-2]) for i,j in zip(row[1::2], row[2::2])] #Drops the timewindow, and groups the rest of the row into [name, tally]
                rowdict = dict(newrow) 
                names.update([x[0] for x in newrow]) #adds each name to a name set
                l=row[0].replace("DateObject[{","").strip("{}]}").replace(",","").replace("}]","").split() #Strips DateObject string
                timestamp=':'.join(l[:3])+'-'+':'.join(l[3:]) #Formats date string
                windows.append(timestamp) #add timestamp to list
                times[timestamp] = rowdict #link results as value in timestamp dict
                rownum += 1

    cols = [[times[k][name] if name in times[k] else ' 0' for name in names ] for k in windows] #put the tally for each name across each timestamp in a nested list of Columns
    data = pd.DataFrame(cols,columns=list(names),index=windows) #Put into dataframe with labels
    return data.transpose()

Run



In [9]:

    
for filename in os.listdir(importpath):
    arrayer(importpath+filename).to_csv(exportpath+filename, encoding='utf-8')



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