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Project Whatsapp Message analysis

Write some introduction about your project here: describe the dataset, where you got it from, what you're trying to do with it, and which tools & techniques you're using. You can also mention about the course, and what you've learned from it.

As a first step, let's upload our Jupyter notebook to

In [12]:
!pip install jovian --upgrade --quiet
!pip install numpy --upgrade --quiet
!pip install pandas --upgrade --quiet
!pip install matplotlib --upgrade --quiet
!pip install seaborn --upgrade --quiet
In [5]:
project_name = "whatsapp-chat-analysis-course-project-try"
In [3]:
import jovian
In [7]:
[jovian] Attempting to save notebook.. [jovian] Please enter your API key ( from ): API KEY: ········ [jovian] Updating notebook "edsenmichaelcy/whatsapp-chat-analysis-course-project-try" on [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully!

Data Preparation and Cleaning

In [16]:
import os
import pandas as pd
import re
import datetime as time
import jovian
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
In [19]:
from urllib.request import urlretrieve

In [20]:
whatsapp_df = pd.read_fwf('WhatsApp_Chat_group.txt', header = None)

In [21]:
<class 'pandas.core.frame.DataFrame'> RangeIndex: 23330 entries, 0 to 23329 Data columns (total 3 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 0 23177 non-null object 1 1 23087 non-null object 2 2 788 non-null object dtypes: object(3) memory usage: 546.9+ KB

After that we will use the info() that provided by the pandas to understand the datatype in the dataframe. As you can see we need to do some clearning such as the date and the Media omitted.

In [22]:
(23330, 3)
In [23]:
def txtTodf(txt_file):
    '''Convert WhatsApp chat log text file to a Pandas dataframe.'''
    # some regex to account for messages taking up multiple lines
    pat = re.compile(r'^(\d\d\/\d\d\/\d\d\d\d.*?)(?=^^\d\d\/\d\d\/\d\d\d\d|\Z)', re.S | re.M)
    with open(txt_file) as file:
        data = ['\n', ' ') for m in pat.finditer(]

    user     = []; 
    message  = []; 
    datetime = []
    for row in data:

        # timestamp is before the first dash
        datetime.append(row.split(' - ')[0])

        # sender is between am/pm, dash and colon
            s ='m - (.*?):', row).group(1)

        # message content is after the first colon
            message.append(row.split(': ', 1)[1])

    df = pd.DataFrame(zip(datetime, user, message), columns=['datetime', 'user', 'message'])
    df['datetime'] = pd.to_datetime(df.datetime, format='%d/%m/%Y, %I:%M %p')

    # remove events not associated with a sender
    df = df[df.user != ''].reset_index(drop=True)
    return df

whatsapp_df = txtTodf('WhatsApp_Chat_group.txt')