在csv文件中創建一個重複的行以分隔列中的多個值（python）

Question

我想在Python中構建一些代碼以將列中的多個值分隔爲單獨的行，並基於同一天聚合Active-Ticket列對於時間戳，是否有任何內部庫可以使用，或者我需要安裝外部庫嗎？

我的樣本文件（就目前來看，主動式門票欄爲空）：

Input.csv

Timestamp,CaseID,Active-Tickets 
14FEB2017:10:55:23,K456 G578 T213,   
13FEB2017:10:56:12,F891 A63, 
14FEB2017:11:59:14,T427 T31212 F900000, 
15FEB2017:03:55:23,K456 G578 T213,   
14FEB2017:05:56:12,F891 A63, 

我想實現：

輸出.csv

Timestamp,CaseID,Active-Tickets 
14FEB2017:10:55:23,K456,8 (because there are 8 cases happened on the same day) 
14FEB2017:10:55:23,G578,8 
14FEB2017:10:55:23,T213,8   
13FEB2017:10:56:12,F891,2 (because there are 2 cases happened on the same day) 
13FEB2017:10:56:12,A63,2 
14FEB2017:11:59:14,T427,8 
14FEB2017:11:59:14,T31212,8 
14FEB2017:11:59:14,F900000,8 
15FEB2017:03:55:23,K456,3 (because there are 3 cases happened on the same day) 
15FEB2017:03:55:23,G578,3 
15FEB2017:03:55:23,T213,3   
14FEB2017:05:56:12,F891,8 
14FEB2017:05:56:12,A63,8 

我的想法是：

1. Take the values for the column Timestamp

2. Check if the date is the same,

3. Store all of the CaseID separated by space into a list based on the date,

4. Count the number of element in the list for each date then

5. Return the values for the counted elements into Active-Tickets .

但這裏的問題是，數據量也不小，假設有50案件最小的一天，那麼我不認爲我的方式是可能的。

Answer 1

這是使用itertools.chain.from_iterable()來做到這一點的一種方法。它只保留內存中的計數，所以可能適用於你的情況。它讀取兩次csv文件。一旦獲得計數，並且一次寫入輸出，但是隻使用迭代器進行讀取，那麼應該保持內存需求不變。

代碼：

import csv 
import itertools as it 
from collections import Counter 

# read through file and get counts per date 
with open('test.csv', 'rU') as f: 
    reader = csv.reader(f) 
    header = next(reader) 
    dates = it.chain.from_iterable(
     [date for _ in ids.split()] 
     for date, ids in ((x[0].split(':')[0], x[1]) for x in reader)) 
    counts = Counter(dates) 

# read through file again, and output as individual records with counts 
with open('test.csv', 'rU') as f: 
    reader = csv.reader(f) 
    header = next(reader) 
    records = it.chain.from_iterable(
     [(l[0], d) for d in l[1].split()] for l in reader) 
    new_lines = (l + (str(counts[l[0].split(':')[0]]),) for l in records) 

    with open('test2.csv', 'wb') as f_out: 
     writer = csv.writer(f_out) 
     writer.writerow(header) 
     writer.writerows(new_lines) 

結果：

Timestamp,CaseID,Active-Tickets 
14FEB2017:10:55:23,K456,8 
14FEB2017:10:55:23,G578,8 
14FEB2017:10:55:23,T213,8 
13FEB2017:10:56:12,F891,2 
13FEB2017:10:56:12,A63,2 
14FEB2017:11:59:14,T427,8 
14FEB2017:11:59:14,T31212,8 
14FEB2017:11:59:14,F900000,8 
15FEB2017:03:55:23,K456,3 
15FEB2017:03:55:23,G578,3 
15FEB2017:03:55:23,T213,3 
14FEB2017:05:56:12,F891,8 
14FEB2017:05:56:12,A63,8 

計數器在2.6

collections.Counter一直蟒蛇向後移植2.5+（Here）