将文本格式的电子邮件合并为一个用于机器学习的 csv 文件

Question

我正在使用 Enron 数据集解决机器学习问题。我想将所有垃圾邮件文件合并到一个 csv 文件中，并将所有 ham 文件合并到另一个 csv 文件中以供进一步分析。我正在使用此处列出的数据集：https://github.com/crossedbanana/Enron-Email-Classification

我使用下面的代码合并了电子邮件，并且能够合并它们。但是，当我尝试读取 csv 文件并将其加载到 pandas 时，由于 ParserError: Error tokenizing data. C error: Expected 1 fields in line 8, saw 2

而出现错误

将 txt 格式的电子邮件文件合并到 csv 中的代码

import os
for f in glob.glob("./dataset_temp/spam/*.txt"):
    os.system("cat "+f+" >> OutFile1.csv")

Code to load into pandas:

```# reading the csv into pandas

emails = pd.read_csv('OutFile1.csv')
print(emails.shape)```

1. How can I get rid of the parser error? this is occuring due to commas present in the email messages I think.
2. How can I just load each email message into pandas with just the email body?

This is how the email format looks like(an example of a text file in the spam folder)
The commas in line 3 are causing a problem while loading into pandas


*Subject: your prescription is ready . . oxwq s f e
low cost prescription medications
soma , ultram , adipex , vicodin many more
prescribed online and shipped
overnight to your door ! !
one of our us licensed physicians will write an
fda approved prescription for you and ship your
order overnight via a us licensed pharmacy direct
to your doorstep . . . . fast and secure ! !
click here !
no thanks , please take me off your list
ogrg z
lqlokeolnq
lnu* 


Thanks for any help.

Answer 1

您可以使用 excel 文件来代替读取和写入 CSV 文件中的数据。所以你不会因为','（逗号）而得到任何错误。只需将 csv 替换为 excel.

这是一个例子：

    import os
    import pandas as pd
    import codecs

    # Function to create list of emails.
    def create_email_list(folder_path):
        email_list = []
        folder = os.listdir(folder_path)#provide folder path, if the folder is in same directory provide only the folder name
        for txt in folder:
            file_name = fr'{folder_path}/{txt}'
            #read emails
            with codecs.open(file_name, 'r', encoding='utf-8',errors='ignore') as f:
                email = f.read()
                email_list.append(email)
        return email_list

    spam_list = create_email_list('spam')#calling the function for reading spam 
    spam_df = pd.DataFrame(spam_list)#creating a dataframe of spam
    spam_df.to_excel('spam.xlsx')#creating excel file of spam

    ham_list = create_email_list('ham')#calling the function for reading ham
    ham_df = pd.DataFrame(ham_list)#creating a dataframe of spam
    ham_df.to_excel('ham.xlsx')#creating excel file of ham

您只需要在函数中传递文件夹路径即可（文件夹名称是文件夹在同一目录下）。此代码将创建 excel 个文件。

Answer 2

为避免 , 出现问题，您可以使用不同的分隔符（例如 |）或在字段周围加上引号：

"soma , ultram , adipex , vicodin many more"

如果字段中有引号，您必须用另一个引号将其转义：

"soma , ultram , ""adipex"" , vicodin many more"

但是，您的示例将对每封邮件中的每一行都有一个 csv 记录。每封电子邮件有一条记录可能更合乎逻辑：

subject,body
your prescription is ready . . oxwq s f e,"low cost prescription medications
soma , ultram , adipex , vicodin many more
prescribed online and shipped
overnight to your door ! !
one of our us licensed physicians will write an
fda approved prescription for you and ship your
order overnight via a us licensed pharmacy direct
to your doorstep . . . . fast and secure ! !
click here !
no thanks , please take me off your list
ogrg z
lqlokeolnq
lnu"
test subject2,"test
body 2"

以上示例为您提供了一个包含 2 列的 table：subject 和 body，其中 body 是一个用双引号括起来的多行字段。

Answer 3

我这样解决了我的问题。先阅读所有的txt文件

```
BASE_DIR = './'
SPAM_DIR = './spam'
 def load_text_file(filenames):
        text_list = []
        for filename in filenames:
             with codecs.open(filename, "r", "utf-8", errors = 'ignore') as f:
                 text = f.read().replace('\r\n', ' ')
                 text_list.append(text)
    return text_list

# add it to a list with filenames 
ham_filenames = glob.glob( BASE_DIR + HAM_DIR + '*.txt')
ham_list = load_text_file(ham_filenames)

# load the list into a dataframe
df = DataFrame (train_list,columns=['emails'])
```

一旦我将它放入数据框中，我就将电子邮件解析为主题和正文。感谢大家的帮助。

将文本格式的电子邮件合并为一个用于机器学习的 csv 文件

Merge emails in text format into one csv file for machine learning

csv

merging-data

python-3.x

pandas