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a4b813b | 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 58 59 60 61 62 63 64 65 | import gradio as gr
import seaborn as sns
import matplotlib.pyplot as plt
# Load Titanic dataset
df = sns.load_dataset("titanic")
# --- Visualization functions ---
def show_data(rows: int = 5):
"""Show top N rows of dataset."""
return df.head(rows)
def plot_survival_by_class():
"""Bar plot: survival count by passenger class."""
fig, ax = plt.subplots()
sns.countplot(data=df, x="pclass", hue="survived", ax=ax)
ax.set_title("Survival Count by Passenger Class")
ax.set_xlabel("Passenger Class")
ax.set_ylabel("Count")
return fig
def plot_gender_distribution():
"""Pie chart: gender distribution."""
fig, ax = plt.subplots()
df["sex"].value_counts().plot.pie(
autopct="%1.1f%%", startangle=90, colors=["#66b3ff", "#ff9999"], ax=ax
)
ax.set_ylabel("")
ax.set_title("Gender Distribution")
return fig
def plot_age_distribution():
"""Histogram: age distribution."""
fig, ax = plt.subplots()
df["age"].dropna().plot.hist(bins=20, edgecolor="black", ax=ax)
ax.set_title("Age Distribution")
ax.set_xlabel("Age")
ax.set_ylabel("Frequency")
return fig
# --- Gradio Interface ---
with gr.Blocks(title="Titanic Data Dashboard") as demo:
gr.Markdown("# 🚢 Titanic Data Dashboard")
gr.Markdown("Explore the Titanic dataset — view data and visualize key statistics.")
with gr.Tab("📋 Dataset"):
gr.Interface(
fn=show_data,
inputs=gr.Slider(1, 50, value=5, step=1, label="Number of rows"),
outputs=gr.Dataframe(label="Titanic Data"),
)
with gr.Tab("📊 Survival by Class"):
gr.Plot(plot_survival_by_class)
with gr.Tab("👫 Gender Distribution"):
gr.Plot(plot_gender_distribution)
with gr.Tab("🎂 Age Distribution"):
gr.Plot(plot_age_distribution)
demo.launch()
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