50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
# 企业微信客户群聊分析
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from os import stat_result
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import pandas as pd
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import re
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def parser_chat_text(content: str):
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result = []
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temp = ["", "", "", ""]
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message = ""
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pattern = "(.*?@{0,1}.*?@{0,1}.*?) (.{1,2}/.{1,2}) (.{2}:.{2}:.{2})"
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for i in content.split("\n"):
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a = re.findall(pattern, i)
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if a:
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if message:
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temp[3] = message
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message = ""
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result.append(temp.copy())
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user, date, time = a[0]
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temp[0] = user
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temp[1] = date
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temp[2] = time
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else:
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message += i
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stat_result = {}
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for user, date, time, content in result:
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if user in stat_result:
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times, word_count = stat_result[user]
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stat_result[user] = (times + 1, word_count + len(content))
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else:
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stat_result[user] = (1, len(content))
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return result, [[t, stat_result[t][0], stat_result[t][1]] for t in stat_result]
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if __name__ == '__main__':
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df = pd.read_excel("聊天记录.xlsx")
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for group_name,group_messages in df.values:
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if group_messages == " ":
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continue
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writer = pd.ExcelWriter(f"{group_name}-聊天记录分析.xlsx", engine="xlsxwriter")
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chat_messages ,chat_analyzer = parser_chat_text(group_messages)
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df1 = pd.DataFrame(chat_messages,columns=["user","date","time","content"])
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df1 = df1.sort_values("date",ascending=False)
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df2 = pd.DataFrame(chat_analyzer,columns=["user","frequence","word_count"])
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df2 = df2.sort_values("frequence",ascending=False)
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df2.to_excel(writer, sheet_name="记录分析",index=False)
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df1.to_excel(writer, sheet_name="记录详情",index=False)
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writer.close()
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