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2d37ca0 253bb1b 2d37ca0 253bb1b 2d37ca0 | 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 51 52 53 54 55 56 57 | import gradio as gr
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Load dataset
url = "https://raw.githubusercontent.com/laxmimerit/All-CSV-ML-Data-Files-Download/master/IMDB-Movie-Data.csv"
df = pd.read_csv(url)
# --- Visualization Functions ---
def show_data(n):
"""Show top n rows of the dataset."""
return df.head(n)
def plot_visualizations(choice):
"""Generate different plots based on user choice."""
plt.figure(figsize=(8, 5))
if choice == "Rating Distribution":
sns.histplot(df["Rating"], bins=15, kde=True)
plt.title("Distribution of Movie Ratings")
elif choice == "Top 10 Directors":
top_directors = df["Director"].value_counts().head(10)
sns.barplot(x=top_directors.values, y=top_directors.index)
plt.title("Top 10 Directors by Movie Count")
elif choice == "Genre Frequency":
all_genres = df["Genre"].str.split(",").explode().str.strip()
top_genres = all_genres.value_counts().head(10)
sns.barplot(x=top_genres.values, y=top_genres.index)
plt.title("Top 10 Movie Genres")
elif choice == "Revenue vs Rating":
sns.scatterplot(x="Rating", y="Revenue (Millions)", data=df)
plt.title("Revenue vs Rating")
plt.tight_layout()
return plt.gcf()
# --- Gradio Interface ---
with gr.Blocks() as demo:
gr.Markdown("# 🎬 IMDB Movie Data Explorer")
gr.Markdown("Explore insights from the IMDB Movie Dataset with visualizations.")
with gr.Tab("📊 View Data"):
n_slider = gr.Slider(5, 50, value=10, step=5, label="Select number of rows")
data_output = gr.Dataframe(label="Dataset Preview")
n_slider.change(show_data, inputs=n_slider, outputs=data_output)
with gr.Tab("📈 Visualize"):
choice = gr.Radio(
["Rating Distribution", "Top 10 Directors", "Genre Frequency", "Revenue vs Rating"],
label="Select Visualization",
)
plot_output = gr.Plot(label="Visualization")
choice.change(plot_visualizations, inputs=choice, outputs=plot_output)
gr.Markdown("Made with ❤️ using Gradio + Seaborn")
demo.launch()
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