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Create 4.Simple EDA.py
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pages/4.Simple EDA.py
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import streamlit as st
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import pandas as pd
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st.markdown("""
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<style>
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/* Set a soft background color */
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body {
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background-color: #eef2f7;
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}
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/* Style for main title */
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h1 {
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color: black;
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font-family: 'Roboto', sans-serif;
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font-weight: 700;
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text-align: center;
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margin-bottom: 25px;
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}
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/* Style for headers */
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h2 {
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color: black;
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font-family: 'Roboto', sans-serif;
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font-weight: 600;
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margin-top: 30px;
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}
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/* Style for subheaders */
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h3 {
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color: red;
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font-family: 'Roboto', sans-serif;
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font-weight: 500;
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margin-top: 20px;
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}
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.custom-subheader {
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color: black;
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font-family: 'Roboto', sans-serif;
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font-weight: 600;
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margin-bottom: 15px;
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}
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/* Paragraph styling */
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p {
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font-family: 'Georgia', serif;
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line-height: 1.8;
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color: black;
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margin-bottom: 20px;
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}
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/* List styling with checkmark bullets */
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.icon-bullet {
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list-style-type: none;
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padding-left: 20px;
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}
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.icon-bullet li {
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font-family: 'Georgia', serif;
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font-size: 1.1em;
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margin-bottom: 10px;
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color: black;
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}
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.icon-bullet li::before {
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content: "β";
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padding-right: 10px;
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color: black;
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}
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/* Sidebar styling */
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.sidebar .sidebar-content {
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background-color: #ffffff;
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border-radius: 10px;
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padding: 15px;
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}
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.sidebar h2 {
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color: #495057;
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}
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/* Custom button style */
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.streamlit-button {
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background-color: #00FFFF;
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color: #000000;
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font-weight: bold;
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}
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</style>
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""", unsafe_allow_html=True)
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st.header(":red[π Simple EDA π¬]")
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# Introduction to Simple EDA
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st.markdown("<div class='section'>", unsafe_allow_html=True)
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st.markdown("<h2 class='title'>π Understanding Simple EDA</h2>", unsafe_allow_html=True)
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st.markdown("<p class='subtitle'>Evaluating raw text data quality before processing</p>", unsafe_allow_html=True)
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st.info("π **Simple EDA is a crucial step in the NLP lifecycle:**\n\nβ
Ensures raw data quality\n\nβ
Not dependent on problem statement\n\nβ
Helps in better data exploration")
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st.markdown("</div>", unsafe_allow_html=True)
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st.subheader(":violet[π Major Simple EDA Steps]")
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st.markdown("β
**Check Text Case** β Identify if text is in **lowercase, uppercase, or mixed case**.")
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st.markdown("β
**Detect HTML & URL Tags** β Analyze if text contains unwanted elements.")
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st.markdown("β
**Identify URLs** β Ensure URLs are either preserved or removed based on problem statement.")
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st.markdown("β
**Detect Mentions & Hashtags** β Find occurrences of `@mentions` or `#hashtags`.")
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st.markdown("β
**Identify Numeric Data** β Detect if text includes **digits or numerical data**.")
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st.markdown("β
**Analyze Punctuation Usage** β Check whether punctuation marks affect text clarity.")
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st.markdown("β
**Detect Emojis** β Ensure **emoji-based sentiments** are not lost.")
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st.markdown("β
**Analyze Date/Time Formats** β Identify the presence of date/time-related text.")
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st.success("π Performing **Simple EDA** ensures structured and high-quality text data, leading to better NLP model performance!")
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st.code('''
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import pandas as pd
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import numpy as np
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import re
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import emoji
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def simple_eda(data,column):
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lower_upper = data[column].apply(lambda x:True if (x.lower()) or (x.upper()) else False).sum()
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tags = data[column].apply(lambda x:True if re.search("<.*?>",x) else False).sum()
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urls = data[column].apply(lambda x:True if re.search("https://\S+",x) else False).sum()
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mails = data[column].apply(lambda x:True if re.search("\S+@\S+",x) else False).sum()
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mentions = data[column].apply(lambda x:True if re.search("\B[@#]\S+",x) else False).sum()
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emojis = data[column].apply(lambda x:True if emoji.emoji_count(x) else False).sum()
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digit = data[column].apply(lambda x:True if re.search("\d",x) else False).sum()
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punc = data[column].apply(lambda x:True if re.search('[!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~]',x) else False).sum()
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dates = data[column].apply(lambda x:True if re.search(r"^[0-9]{1,2}\/[0-9]{1,2}\/[0-9]{4}$",x) else False).sum()
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if lower_upper >0:
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print("text have combination")
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if tags > 0:
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print("text have tags")
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if urls >0:
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print("text have urls")
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if mails > 0:
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print("text have mails")
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if mentions >0:
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print("text have mentions")
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if emojis > 0:
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print("text have emojis")
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if digit >0:
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print("text have digit")
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if punc > 0:
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print("text have punctuations")
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if dates >0:
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print("text have dates")
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''')
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st.markdown('''
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- By the following code we will check the exploration of the data
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| 145 |
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- Basically it gives the quality of collected text data
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| 146 |
+
- After the simple eda we will perform pre-processing on text based on problem statement after knowing quality of the data
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| 147 |
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''')
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