使用CSV：在正确的ord中读写数据

Question

我有两个.csv文件与来自Twitter的数据相关。一个有tweets的文本，另一个有tweets的id。具有id的文件是从中对另一个文件中的tweet进行采样的总体。我试图编写一个脚本来读取文本，在另一个文件中搜索相应的ID，然后编写一个新的.csv文件，该文件在较小的示例中包含tweets的ID和文本。你知道吗

以下是我目前掌握的情况：

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（gg）的数据_原件.csv)看起来像这样：

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

作为总体子集的纯文本文件如下所示：

text
abcl
abci
abcd

到目前为止，我运行的程序似乎得到了正确的id，它甚至将它们写入新.csv文件中的一个新列。但是，新文件中的ID不在正确的行中—它们显示在与它们实际上不对应的文本行中，这很糟糕！你知道吗

新文件应如下所示：

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

结果是这样的：

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

找到了正确的ID，但它们被写入了错误的行。你知道吗

Answer 1

好吧，这个代码（我想）就是你想要做的。我之所以要你的操作系统是因为wt会在Windows中提供双倍行距的csv，所以我不得不使用wb。此外，在单元格A1中插入大写“ID”会导致使用Excel打开时出现类型问题。所有乐趣：）

最后我没有时间追踪你的错误，仍然给出答案，所以我已经写了答案，如果有机会，我会回去强调你的工作不同步的地方（在分心之前，我从来没有在Excel中遇到SYLK错误！）。你知道吗

我把你的字典换了。tweet本身就成了dict的关键，不再重复字典了。这也意味着你只需要打开first20.csv一次。你原来的方法有点复杂。你知道吗

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)