app.py

import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from dataset_import import load_data

st.title("AnalyzeYT Dataset Analysis")

# Load dataset
data = load_data()

if data is not None:
    st.write("Loaded Data Preview:")
    st.write(data.head())

    # Show data description
    st.write("Data Description:")
    st.write(data.describe())

    # Add correlation matrix
    st.write("Correlation Matrix:")
    corr = data.corr()
    st.write(corr)
    st.write(sns.heatmap(corr, annot=True, cmap='coolwarm'))
    st.pyplot()

    # Data visualization options
    st.write("Data Visualization:")
    chart_type = st.selectbox("Select Chart Type", ['Line Chart', 'Bar Chart', 'Histogram'])

    if chart_type == 'Line Chart':
        x_axis = st.selectbox("Select X-axis Column", data.columns)
        y_axis = st.selectbox("Select Y-axis Column", data.columns)
        title = st.text_input("Enter Chart Title", "Line Chart")
        st.line_chart(data[[x_axis, y_axis]])
        st.write(f"Line Chart: {title}")

    elif chart_type == 'Bar Chart':
        x_axis = st.selectbox("Select X-axis Column", data.columns)
        y_axis = st.selectbox("Select Y-axis Column", data.columns)
        title = st.text_input("Enter Chart Title", "Bar Chart")
        st.bar_chart(data[[x_axis, y_axis]])
        st.write(f"Bar Chart: {title}")

    elif chart_type == 'Histogram':
        selected_column = st.selectbox("Select Column for Histogram", data.columns)
        bins = st.slider("Number of Bins", min_value=10, max_value=100, value=30)
        title = st.text_input("Enter Chart Title", "Histogram")
        plt.hist(data[selected_column], bins=bins)
        plt.title(title)
        plt.xlabel(selected_column)
        plt.ylabel('Frequency')
        st.pyplot()