使用CSVs：以正確的順序讀取和寫入數據

Question

我有兩個.csv與Twitter數據相關的文件。一個有推文文本，另一個有這些推文的ID。帶有ID的文件是其他文件中的推文被採樣的總體。我正在嘗試編寫一個腳本來讀取文本，在另一個文件中搜索相應的ID，然後編寫一個新的.csv文件，該文件同時包含較小示例中推文的ID和文本。

這是我到目前爲止有：

import csv 

# creates empty dictionary in which to store tweetIDs and tweet text 
originals_data = {} 

# declares an empty list to hold tweet text from coded datafile 
# will be used to compare against the dictionary created earlier 
coded_data = [] 
coded_all = [] # for all, not just text 

# list to hold the IDs belonging to coded tweets for the round 
tweet_IDs_for_coded = [] 

with open('first20.csv', 'rt') as round_in, open('gg_originals.csv', 'rt') as original_in: 

    # reader object for gg_originals 
    readOrigin = csv.reader(original_in, delimiter=',') 
    # adds values from .csv file into the dictionary 
    for row in readOrigin: 
     originals_data[row[0]] = row[1] 

    # reader object for round_x data 
    readRound = csv.reader(round_in, delimiter=",") 
    # appends the tweet text to a list 
    for row in readRound: 
     coded_data.append(row[0]) 

    # iterates over id:text dictionary 
    for tweet_id in originals_data: 
     # iterates over coded_data 
     for tweet in coded_data: 
      # When tweet in list matches text in dict, sends key to list 
      if tweet == originals_data[tweet_id]: 
       tweet_IDs_for_coded.append(tweet_id) 

with open('first20.csv', 'rt') as round_in, open('test2.csv', 'wt') as output: 
    # reader object for round_x data 
    readRound = csv.reader(round_in, delimiter=",") 
    # creates writer object to write new csv file with IDs 
    writeNew = csv.writer(output, delimiter=",") 
    # list that holds everything that's going into the csv file 
    everything = [] 
    # sets row to equal a single row from round data 
    row = next(readRound) 
    row.insert(0, 'ID') 
    # appends ID and then all existing data to list of rows 
    everything.append(row) 
    for i, row in enumerate(readRound): 
     everything.append([str(tweet_IDs_for_coded[i])] + row) 
    writeNew.writerows(everything) 

人口文件中的數據（gg_originals.csv）看起來是這樣的：

tweet_id_str,text 
534974890168700930,abcd 
534267820071084033,abce 
539572102441877504,abcf 
539973576108294145,abcg 
529278820876943361,abch 
529583601244176384,abci 
535172191743397888,abcj 
532195210059874304,abck 
537812033895669760,abcl 
, 
, 

的純文本文件，該文件是一個子集的人口看起來像這樣：

text 
abcl 
abci 
abcd 

我到目前爲止運行，似乎得到了公司正確的ID，甚至會將它們寫入新的.csv文件中的新列。但是，新文件中的ID不在正確的行中 - 它們顯示在文本的行中，它們實際上並不對應，這很糟糕！

新的文件應該是這個樣子：

ID,text 
537812033895669760,abcl 
529583601244176384,abci 
534974890168700930,abcd 

相反，它最終是這樣的：

ID,text 
529583601244176384,abcl 
537812033895669760,abci 
534974890168700930,abcd 

正確的ID已經找到，但他們已經被寫入到錯誤的行。

Answer 1

好的，這段代碼確實（我認爲）你正在做的是什麼。我問你的操作系統的原因是，wt將在Windows中提供雙倍間隔的csvs，因此我必須使用wb。此外，在單元格A1中插入大寫「ID」時，會在使用Excel打開時導致類型問題。所有的樂趣:)

我最終沒有足夠的時間跟蹤你的錯誤，仍然給出答案，所以我寫了答案，我會回去，如果我有機會，並強調你的工作出去的地方，同步（我不會在Excel中遇到SYLK錯誤，所以分心！）。

我換了你的字典。推特本身成爲字典的關鍵。沒有更多的迭代通過字典。這也意味着你只需要打開first20.csv一次。你的原創方法有點複雜。

import csv 

with open('gg_originals.csv', 'rt') as original_in: 
    readOrigin = csv.reader(original_in, delimiter = ',') 
    originals_data = {row[1]: row[0] for row in readOrigin} 

with open('first20.csv', 'rt') as round_in: 
    input_data = csv.reader(round_in) 
    data_to_match = [row[0] for row in input_data] 

compiled_list = [] 
for item in data_to_match: 
    compiled_list.append([item, originals_data[item]]) 

with open('testoutput.csv', 'wt') as outfile: 
    writer = csv.writer(outfile) 
    writer.writerows(compiled_list)