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| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| country_mapping = { | |
| 'United States': 'USA', | |
| 'United Kingdom': 'GBR', | |
| 'France': 'FRA', | |
| 'Canada': 'CAN', | |
| 'Germany': 'DEU', | |
| 'Japan': 'JPN', | |
| 'India': 'IND', | |
| 'Australia': 'AUS', | |
| 'China': 'CHN', | |
| 'Italy': 'ITA', | |
| 'Spain': 'ESP', | |
| 'Mexico': 'MEX', | |
| 'Hong Kong': 'HKG', | |
| 'Sweden': 'SWE', | |
| 'Denmark': 'DNK', | |
| 'New Zealand': 'NZL', | |
| 'Belgium': 'BEL', | |
| 'South Korea': 'KOR', | |
| 'Ireland': 'IRL', | |
| 'Czech Republic': 'CZE', | |
| 'Switzerland': 'CHE', | |
| 'Hungary': 'HUN', | |
| 'Norway': 'NOR', | |
| 'United Arab Emirates': 'ARE', | |
| 'Netherlands': 'NLD', | |
| 'South Africa': 'ZAF', | |
| 'Poland': 'POL', | |
| 'Austria': 'AUT', | |
| 'Turkey': 'TUR' | |
| } | |
| # Load your dataframes | |
| df_tv_series= pd.read_csv('series_after_cleaning.csv') | |
| df_movies= pd.read_csv('movie_after_cleaning.csv') | |
| df_movies['genre'] = df_movies['genre'].str.split(',') | |
| df_tv_series['genre'] = df_tv_series['genre'].str.split(',') | |
| df_movies['country'] = df_movies['country'].str.split(',') | |
| df_tv_series['country'] = df_tv_series['country'].str.split(',') | |
| # Function to generate treemap | |
| def create_treemap(df, title): | |
| fig = px.treemap(df, path=['parentalguide'], title=title) | |
| return fig | |
| def create_genre_bar_chart(df, title): | |
| # Explode the genre column to count each genre separately | |
| df_exploded = df.explode('genre') | |
| genre_counts = df_exploded['genre'].value_counts().reset_index() | |
| genre_counts.columns = ['genre', 'count'] | |
| genre_counts = genre_counts.head(10) # Get top 10 genres | |
| fig = px.bar(genre_counts, x='count', y='genre', orientation='h', title=title) | |
| return fig | |
| def create_country_map(df, title): | |
| # Explode the country column to count each country separately | |
| df_exploded = df.explode('country') | |
| country_counts = df_exploded['country'].value_counts().reset_index() | |
| country_counts.columns = ['country', 'count'] | |
| # Map country names to ISO codes | |
| country_counts['country'] = country_counts['country'].map(country_mapping) | |
| fig = px.choropleth(country_counts, | |
| locations="country", | |
| color="count", | |
| hover_name="country", | |
| title=title, | |
| projection="natural earth", | |
| color_continuous_scale='Viridis') | |
| fig.update_layout(template='plotly_dark', font=dict(color='yellow')) | |
| return fig | |
| # Streamlit app | |
| st.title('Parental Guide Treemaps') | |
| # Split into two columns | |
| col1, col2 = st.columns(2) | |
| # Initialize variable for selection | |
| selection = 'Movies' | |
| # Add buttons in each column | |
| with col1: | |
| if st.button('Movies'): | |
| selection = 'Movies' | |
| with col2: | |
| if st.button('TV Series'): | |
| selection = 'TV Series' | |
| # Display the corresponding treemap in the center | |
| if selection == 'Movies': | |
| 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.plotly_chart(create_country_map(df_movies, 'Global Distribution of Movies'), use_container_width=True) | |
| elif selection == 'TV Series': | |
| 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.plotly_chart(create_country_map(df_tv_series, 'Global Distribution of TV Series'), use_container_width=True) | |