功能：从邮件中提取关键字并判断是否超出阈值，并将关键字记录在excel中。邮件内容类似于：

Dear Mr. Smith,

I am writing to follow up on our previous conversation regarding the project. As per your request, I have attached the latest progress report and budget sheet for your review.

Please note that there have been some unexpected expenses incurred in the past month, particularly in the area of travel and accommodation for the team members. I have highlighted these items in the budget sheet for your attention.

I would appreciate it if you could review these documents and let me know if you have any questions or concerns. Thank you for your time and attention.

Best regards,

John Doe

在以上邮件中，可能需要提取的关键字有：项目、进展、预算、费用、旅行、住宿、团队等。如果某个关键字出现的次数超过了预设的阈值，例如3次，那么就需要将该关键字记录在excel表格中。

相关问题

请用代码实现功能：从邮件中提取关键字并判断是否超出阈值，并将关键字记录在excel中。邮件内容参考你发送的

I am sorry, but as an AI language model, I am not able to send emails or access email content. However, I can provide you with a sample code to extract keywords from a text document and record them in an Excel file.

import pandas as pd
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize

# Set threshold for keyword frequency
threshold = 2

# Load stop words
stop_words = set(stopwords.words('english'))

# Load text document
with open('text.txt', 'r') as f:
text = f.read()

# Tokenize text
tokens = word_tokenize(text)

# Remove stop words and punctuation
keywords = [word.lower() for word in tokens if word.isalpha() and word.lower() not in stop_words]

# Count keyword frequency
freq = nltk.FreqDist(keywords)

# Filter keywords that exceed threshold
keywords = [word for word, count in freq.items() if count >= threshold]

# Record keywords in Excel file
df = pd.DataFrame(keywords, columns=['Keywords'])
df.to_excel('keywords.xlsx', index=False)

This code reads a text document named "text.txt", tokenizes it, removes stop words and punctuation, counts the frequency of each keyword, filters the keywords that exceed the threshold, and records the remaining keywords in an Excel file named "keywords.xlsx". You can adjust the threshold value to your desired limit.

依次读取excel文件中的数据判断哪个值超出了阈值并输出

好的，这个问题属于技术问题，可以回答。你可以使用 pandas 库中的 read_excel() 方法读取 excel 文件，再使用条件判断语句来判断哪些值超出了阈值，最后输出超出阈值的值。以下是一个示例代码：

import pandas as pd

# 读取 excel 文件
df = pd.read_excel('your_file.xlsx')

# 设置阈值
threshold = 100

# 判断哪些值超出了阈值
outliers = df[df > threshold]

# 输出超出阈值的值
print(outliers)