我有两个与Twitter数据相关的.csv
个文件。一个包含推文文本,另一个包含这些推文的ID。具有ID的文件是从中抽取另一个文件中的推文的总体。我正在尝试编写一个脚本来读取文本,在另一个文件中搜索相应的ID,然后在较小的样本中编写一个新的.csv
文件,其中包含推文的ID和文本。 / p>
这是我到目前为止所拥有的:
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)
填充文件(gg_originals.csv)的数据如下所示:
tweet_id_str,text
534974890168700930,abcd
534267820071084033,abce
539572102441877504,abcf
539973576108294145,abcg
529278820876943361,abch
529583601244176384,abci
535172191743397888,abcj
532195210059874304,abck
537812033895669760,abcl
,
,
作为人口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是,它似乎获得了正确的ID,甚至将它们写入新.csv
文件中的新列。但是,新文件中的ID不在正确的行中 - 它们显示在实际上不对应的文本行中,这很糟糕!
新文件应该看起来像这样:
ID,text
537812033895669760,abcl
529583601244176384,abci
534974890168700930,abcd
相反,它最终会像这样:
ID,text
529583601244176384,abcl
537812033895669760,abci
534974890168700930,abcd
找到了正确的ID,但它们已被写入错误的行。
答案 0 :(得分:1)
好的,这段代码确实(我认为)你想做什么。我问你的操作系统的原因是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。一切都很有趣:)
我最终没时间跟踪你的错误并仍然给出了答案,所以我写了答案,如果我有机会并且突出你的工作不同步的地方我会回去(我是从来没有遇到过Excel中的SYLK错误,所以分心!)。
我交换了你的字典。推文本身成为了这个词的关键。不再迭代字典了。这也意味着您只需要打开first20.csv
一次。你原来的方法有点复杂。
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)