Update app.py

app.py

@@ -2,21 +2,6 @@ import streamlit as st
 import pandas as pd
 import plotly.express as px
 
-# Function to assign color based on count
-def assign_color(count):
-    if count <= 10:
-        return '1-10'
-    elif count <= 50:
-        return '10-50'
-    elif count <= 100:
-        return '50-100'
-    elif count <= 500:
-        return '100-500'
-    elif count <= 1000:
-        return '500-1000'
-    else:
-        return '>1000'
-
 # Country mapping dictionary
 country_mapping = {
     'United States': 'USA',
@@ -124,7 +109,7 @@ country_mapping = {
     'Maldives': 'MDV'
 }
 
-# Load your dataframes (replace with actual CSV filenames)
+# Load your dataframes
 df_movies = pd.read_csv('movie_after_cleaning.csv')
 df_tv_series = pd.read_csv('series_after_cleaning.csv')
 
@@ -145,11 +130,7 @@ def create_genre_bar_chart(df, title):
     genre_counts = df_exploded['genre'].value_counts().reset_index()
     genre_counts.columns = ['genre', 'count']
     genre_counts = genre_counts.head(10)  # Top 10 genres
-    fig = px.bar(genre_counts, x='count', y='genre', orientation='h', title=title, 
-                 labels={'count': 'Count', 'genre': 'Genre'},
-                 color_discrete_sequence=['#FFA07A'])
-    fig.update_traces(marker_line_color='rgb(8,48,107)', marker_line_width=1.5, opacity=0.6)
-    fig.update_layout(title_font_size=20, title_font_family='Arial', title_font_color='#00308F')
+    fig = px.bar(genre_counts, x='count', y='genre', orientation='h', title=title)
     return fig
 
 # Function to create choropleth map
@@ -161,61 +142,51 @@ def create_country_map(df, title):
     # Map country names to ISO codes
     country_counts['country'] = country_counts['country'].map(country_mapping)
     
-    # Assign color based on count
-    country_counts['color'] = country_counts['count'].apply(assign_color)
-    
     fig = px.choropleth(country_counts, 
                         locations="country",
-                        color="color",
+                        color="count",
                         hover_name="country",
                         title=title,
-                        projection="natural earth",
-                        color_discrete_sequence=['#7FFF00', '#FFD700', '#FFA500', '#FF4500', '#DC143C', '#8B0000'],
-                        category_orders={"color": ['1-10', '10-50', '50-100', '100-500', '500-1000', '>1000']})
+                        projection="natural earth")
     
-    fig.update_geos(showcoastlines=True, coastlinecolor="LightBlue", showland=True, landcolor="LightGreen",
-                    showocean=True, oceancolor="LightBlue", showlakes=True, lakecolor="LightBlue", 
-                    showrivers=True, rivercolor="LightBlue")
-    
-    fig.update_layout(title_font_size=20, title_font_family='Arial', title_font_color='#00308F')
     return fig
 
 # Function to create rating distribution box chart
 def create_rating_box_chart(df, title):
-    fig = px.box(df, x="rating", points="all", title=title, 
-                 labels={'rating': 'Rating'},
-                 orientation='h',
-                 color_discrete_sequence=['#FF6347'])
-    fig.update_traces(marker_line_color='rgb(8,48,107)', marker_line_width=1.5, opacity=0.6)
-    fig.update_layout(title_font_size=20, title_font_family='Arial', title_font_color='#00308F')
+    fig = px.box(df, x="rating", points="all", title=title)
     return fig
 
 # Streamlit app
-st.title('MOVIE Analysis')
+st.title('Parental Guide Analysis')
 
-# Split into two columns for buttons
+# Display two charts per row
 col1, col2 = st.columns(2)
+selection = col1.button('Movies')
+col2.button('TV Series')
 
-# Default selection
-selection = 'Movies'
-
-# Buttons for Movies and TV Series
-with col1:
-    if st.button('Movies'):
-        selection = 'Movies'
-
-with col2:
-    if st.button('TV Series'):
-        selection = 'TV Series'
-
-# Display treemap, genre bar chart, rating distribution, and choropleth map based on selection
-if selection == 'Movies':
+# Displaying charts in a customized layout based on selection
+if selection:
+    st.subheader('Movies')
+    st.write('<div style="display: flex; flex-direction: row; flex-wrap: wrap;">', unsafe_allow_html=True)
+    st.write('<div style="flex: 50%; padding: 10px;">')
     st.plotly_chart(create_treemap(df_movies, 'Parental Guide - Movies'), use_container_width=True)
     st.plotly_chart(create_genre_bar_chart(df_movies, 'Top 10 Genres - Movies'), use_container_width=True)
+    st.write('</div>')
+    st.write('<div style="flex: 50%; padding: 10px;">')
     st.plotly_chart(create_rating_box_chart(df_movies, 'Rating Distribution - Movies'), use_container_width=True)
     st.plotly_chart(create_country_map(df_movies, 'Global Distribution of Movies'), use_container_width=True)
-elif selection == 'TV Series':
+    st.write('</div>')
+    st.write('</div>', unsafe_allow_html=True)
+
+else:
+    st.subheader('TV Series')
+    st.write('<div style="display: flex; flex-direction: row; flex-wrap: wrap;">', unsafe_allow_html=True)
+    st.write('<div style="flex: 50%; padding: 10px;">')
     st.plotly_chart(create_treemap(df_tv_series, 'Parental Guide - TV Series'), use_container_width=True)
     st.plotly_chart(create_genre_bar_chart(df_tv_series, 'Top 10 Genres - TV Series'), use_container_width=True)
+    st.write('</div>')
+    st.write('<div style="flex: 50%; padding: 10px;">')
     st.plotly_chart(create_rating_box_chart(df_tv_series, 'Rating Distribution - TV Series'), use_container_width=True)
     st.plotly_chart(create_country_map(df_tv_series, 'Global Distribution of TV Series'), use_container_width=True)
+    st.write('</div>')
+    st.write('</div>', unsafe_allow_html=True)