Spaces:
Sleeping
Sleeping
File size: 1,649 Bytes
90a6c5f 5a0a701 90a6c5f 5a0a701 4d9b242 50f339f 53d94e8 90a6c5f 5a0a701 0488555 50f339f 0488555 90a6c5f 5a0a701 90a6c5f 4d9b242 90a6c5f dcbc569 4d9b242 dcbc569 4d9b242 dcbc569 0488555 dcbc569 50f339f 0488555 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 |
import streamlit as st
import pandas as pd
import plotly.express as px
# 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(',')
# 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']
fig = px.bar(genre_counts, x='genre', y='count', title=title)
return fig
# Streamlit app
st.title('Parental Guide Treemaps')
# Split into two columns
col1, col2 = st.columns(2)
# Initialize variable for selection
selection = None
# 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 Genres - Movies'), use_container_width=True)
elif selection == 'TV Series':
st.plotly_chart(create_treemap(df, 'Parental Guide - TV Series'), use_container_width=True)
st.plotly_chart(create_genre_bar_chart(df_tv_series, 'Top Genres - TV Series'), use_container_width=True)
|