Update pages/3.Simple EDA.py

pages/3.Simple EDA.py

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