Update eda.py

eda.py

@@ -1,9 +1,45 @@
 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')
+    st.title('Exploration Data Analysis Section')
+
+# ============================= Simple Analysis ========================
+
+    eda=pd.read_csv('eda.csv')
+    # 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)