import streamlit as st
import pandas as pd
from PIL import Image
import plotly.express as px

def run():
    '''
    Function for EDA page
    '''
    st.title('Exploration Data Analysis Section')

# ============================= Simple Analysis ========================

    eda=pd.read_csv('eda.csv')
    # basic summary analysis
    emotion_counts = eda['Emotion'].value_counts()
    
    eda['Comment Length'] = eda['Comment'].apply(len)
    eda['Word Count'] = eda['Comment'].apply(lambda x: len(x.split()))
    # emotion distribution
    fig_emotions = px.bar(emotion_counts,
                          x=emotion_counts.index,
                          y=emotion_counts.values,
                          labels={'x': 'Emotion', 'y': 'Count'},
                          title='Distribution of Emotions')
    fig_emotions.update_traces(marker_line_width=1, marker_line_color='black')
    fig_emotions.update_layout(xaxis_title='Emotions', yaxis_title='Count', width=1000)
    
    # comment distribution
    fig_comment_length = px.histogram(eda,
                                      x='Comment Length',
                                      nbins=30,
                                      marginal='box',
                                      title='Distribution of Comment Length')
    fig_comment_length.update_traces(marker_line_width=1, marker_line_color='black')
    fig_comment_length.update_layout(xaxis_title='Length of Comment', yaxis_title='Count', width=1000, bargap=0)
    
    # word count distribution
    fig_word_count = px.histogram(eda,
                                  x='Word Count',
                                  nbins=30,
                                  marginal='box',
                                  title='Distribution of Word Count')
    fig_word_count.update_traces(marker_line_width=1, marker_line_color='black')
    fig_word_count.update_layout(xaxis_title='Word Count', yaxis_title='Count', width=1000)
    
    # Display the figures in Streamlit
    st.plotly_chart(fig_emotions)
    st.plotly_chart(fig_comment_length)
    st.plotly_chart(fig_word_count)