如何从 Excel 文件中提取电子邮件列并使用 Pandas 找出邮件类型？

在本文中，让我们看看如何从 Excel 文件中提取电子邮件列，并使用 Pandas 找出邮件的类型。假设我们的 Excel 文件如下图所示，然后我们必须在 Dataframe 的不同列中存储不同类型的电子邮件。

要查看 Excel 文件，请单击此处

方法：

• Import required module.
• Import data from Excel file.
• Make an extra column for each different Email.
• Set Each required Index for searching.
• Define the Pattern of the Email.
• Search the Email and assigning to the respective column in Dataframe.

让我们看看分步实施：

步骤 1：导入所需模块并从 Excel 文件中读取数据。

Python3

# import required module
import pandas as pd;
import re;
  
# Read excel file and store in to DataFrame
data = pd.read_excel("Email_sample.xlsx");
  
# show the dataframe
data

输出：

第 2 步：为每个不同的电子邮件创建一个额外的列。

Python3

data['Google-mail'] = None
  
data

输出：

Python3

data['Yahoo-mail'] = None
data

输出 ：

第 3 步：设置搜索所需的每个索引。

Python3

# set required index 
index_set = data.columns.get_loc('E-mail')
index_gmail = data.columns.get_loc('Google-mail')
index_yahoo = data.columns.get_loc('Yahoo-mail')
  
print(index_set, index_gmail, 
      index_yahoo)

输出：

1 2 3

第 4 步：定义电子邮件的模式。

Python3

# define pattern of Email
google_pattern = r'gmail.com'
yahoo_pattern = r'yahoo.com'

第 5 步：搜索电子邮件并分配到 Dataframe 中的相应列。

Python3

# Search the Email in DataFrame and store  
for row in range(0, len(data)):
    
    if re.search(google_pattern,
                 data.iat[row, index_set]) == None :
        data.iat[row,index_gmail] = 'Account not belongs to Google'
          
    else:
        gmail = re.search(google_pattern,
                          data.iat[row, index_set]).group()
        data.iat[row,index_gmail] = "Google-Mail"
  
    if re.search(yahoo_pattern,
                 data.iat[row, index_set]) == None :
        data.iat[row,index_yahoo] = 'Account not belongs to Yahoo'
          
    else:
        yahoo = re.search(yahoo_pattern,
                          data.iat[row, index_set]).group()
        data.iat[row,index_yahoo] = "Yahoo-Mail"
          
data

输出：

完整代码：

Python3

# importing required module
import pandas as pd
import re
  
# Creating df
# Reading data from Excel
data = pd.read_excel("Email_sample.xlsx")
print("Original DataFrame")
print(data)
  
# Create column for
# each type of Email
data['Google-mail'] = None
data['Yahoo-mail'] = None
  
# set index
index_set = data.columns.get_loc('E-mail')
index_gmail = data.columns.get_loc('Google-mail')
index_yahoo = data.columns.get_loc('Yahoo-mail')
  
# define Email pattern
google_pattern = r'gmail.com'
yahoo_pattern = r'yahoo.com'
  
# Searching the email
# Store into DataFrame
for row in range(0, len(data)):
    if re.search(google_pattern,
                 data.iat[row, index_set]) == None:
        data.iat[row, index_gmail] = 'Account not belongs to Google'
    else:
        gmail = re.search(google_pattern,
                          data.iat[row, index_set]).group()
        data.iat[row, index_gmail] = "Google-Mail"
  
    if re.search(yahoo_pattern,
                 data.iat[row, index_set]) == None:
        data.iat[row, index_yahoo] = 'Account not belongs to Yahoo'
    else:
        yahoo = re.search(yahoo_pattern,
                          data.iat[row, index_set]).group()
        data.iat[row, index_yahoo] = "Yahoo-Mail"
  
data

输出 ：

注意：在运行此程序之前，请确保您已经在Python环境中安装了xlrd库。