this is the app.py file "import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from dataset_import import load_data
from data_cleaning import clean_data

st.title("AnalyzeYT Dataset Analysis")

Load and clean dataset

data = load_data()

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

# Clean data
data = clean_data(data)

st.write("Cleaned 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)

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()

" also write a requirements.txt file