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preprocess.py
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preprocess.py
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import streamlit as st
import numpy as np
import seaborn as sn
import pandas as pd
import re
def gettimeanddate(string):
string = string.split(',')
date, time = string[0], string[1]
time = time.split('-')
time = time[0].strip()
return date+" "+time
def getstring(text):
return text.split('\n')[0]
def preprocess(data):
pattern = '\d{1,2}/\d{1,2}/\d{2,4},\s\d{1,2}:\d{2}\s-\s'
messages = re.split(pattern, data)[1:]
dates = re.findall(pattern, data)
df = pd.DataFrame({'user_messages': messages,
'message_date': dates})
df['message_date'] = df['message_date'].apply(
lambda text: gettimeanddate(text))
df.rename(columns={'message_date': 'date'}, inplace=True)
users = []
messages = []
for message in df['user_messages']:
entry = re.split('([\w\W]+?):\s', message)
if entry[1:]:
users.append(entry[1])
messages.append(entry[2])
else:
users.append('Group Notification')
messages.append(entry[0])
df['User'] = users
df['message'] = messages
df['message'] = df['message'].apply(lambda text: getstring(text))
df = df.drop(['user_messages'], axis=1)
df = df[['message', 'date', 'User']]
df = df.rename(columns={'message': 'Message',
'date': 'Date'})
df['Only date'] = pd.to_datetime(df['Date']).dt.date
df['Year'] = pd.to_datetime(df['Date']).dt.year
df['Month_num'] = pd.to_datetime(df['Date']).dt.month
df['Month'] = pd.to_datetime(df['Date']).dt.month_name()
df['Day'] = pd.to_datetime(df['Date']).dt.day
df['Day_name'] = pd.to_datetime(df['Date']).dt.day_name()
df['Hour'] = pd.to_datetime(df['Date']).dt.hour
df['Minute'] = pd.to_datetime(df['Date']).dt.minute
return df