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将制表符分隔的 txt 文件转换为逗号分隔的 csv 文件

[英]Convert tab delimited txt file into csv file comma separated

I have this text file and I want to convert it into comma separated file我有这个文本文件,我想把它转换成逗号分隔的文件

antecedents    consequents    support    confidence    lift
-------------  -------------  ---------  ------------  ------
  398  frozenset(['LM = 25', 'DIAB = n', 'SMOK = y'])     frozenset(['AL = 1'])       0.25             1  1.33333
  461  frozenset(['Age = 80', 'LM = 15', 'CHOL = 200'])   frozenset(['AL = 1'])       0.25             1  1.33333
  837  frozenset(['RCA = 80', 'Age = 80', 'SMOK = y'])    frozenset(['AL = 1'])       0.25             1  1.33333

I applied pandas and csv but it doesn't separate columns, it only separates raws like this我应用了 pandas 和 csv 但它没有分隔列,它只分隔这样的原始数据

antecedents    consequents    support    confidence    lift
-------------  -------------  ---------  ------------  ------
"  398  frozenset(['LM = 25', 'DIAB = n', 'SMOK = y'])     frozenset(['AL = 1'])       0.25             1  1.33333"
"  461  frozenset(['Age = 80', 'LM = 15', 'CHOL = 200'])   frozenset(['AL = 1'])       0.25             1  1.33333"
"  837  frozenset(['RCA = 80', 'Age = 80', 'SMOK = y'])    frozenset(['AL = 1'])       0.25             1  1.33333"

This is the code I used 1-这是我使用的代码 1-

dataframe = pd.read_csv("/Users/user/PycharmProjects/Apriori /Rules.txt",delimiter="\t")
dataframe.to_csv("newDoc.csv", encoding='utf-8', index=False)

2- 2-

txt_file = r"/Users/user/PycharmProjects/Apriori /Rules.txt"
csv_file = r"mycsv.csv"

in_txt = csv.reader(open(txt_file, "rb"), delimiter = '\t')
out_csv = csv.writer(open(csv_file, 'wb'))

out_csv.writerows(in_txt)

Any help please?请问有什么帮助吗?

Given the lines it looks as if you could use a regular expression to grab the five fields.鉴于这些行,您似乎可以使用正则表达式来获取五个字段。 Something along the lines of:类似于以下内容:

import csv
import re

# looks like a consistent format given the example text:
line_re = re.compile('^\s*(\d+)\s+(frozenset.*?\))\s*(frozenset.*?\))\s*(\S+)\s+(\S+)\s+(\S+)$')
txt = '''antecedents    consequents    support    confidence    lift
-------------  -------------  ---------  ------------  ------
  398  frozenset(['LM = 25', 'DIAB = n', 'SMOK = y'])     frozenset(['AL = 1'])       0.25             1  1.33333
  461  frozenset(['Age = 80', 'LM = 15', 'CHOL = 200'])   frozenset(['AL = 1'])       0.25             1  1.33333
  837  frozenset(['RCA = 80', 'Age = 80', 'SMOK = y'])    frozenset(['AL = 1'])       0.25             1  1.33333'''

with open('mycsv.csv', 'w') as f:
    writer = csv.writer(f)
    for line in txt.splitlines():
        mo = line_re.match(line)
        if mo:
            writer.writerow(mo.groups())


cat mycsv.csv
398,"frozenset(['LM = 25', 'DIAB = n', 'SMOK = y'])",frozenset(['AL = 1']),0.25,1,1.33333
461,"frozenset(['Age = 80', 'LM = 15', 'CHOL = 200'])",frozenset(['AL = 1']),0.25,1,1.33333
837,"frozenset(['RCA = 80', 'Age = 80', 'SMOK = y'])",frozenset(['AL = 1']),0.25,1,1.33333

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