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import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import gradio as gr
def analyze(file):
df = pd.read_csv(file)
# Clean percentage column (remove % and convert to int)
df["Percentage"] = df["Percentage"].str.replace("%", "").astype(float)
subjects = df["Subjects"]
percentages = df["Percentage"]
best = subjects[percentages.idxmax()]
weak = subjects[percentages.idxmin()]
avg = np.mean(percentages)
remarks = []
for subj, perc in zip(subjects, percentages):
if perc <= 33:
remarks.append(f"❌ {subj}: {perc}% → Fail. Needs to reappear.")
elif 34 <= perc <= 70:
remarks.append(f"⚠️ {subj}: {perc}% → Average. Needs improvement.")
elif 71 <= perc <= 89:
remarks.append(f"✅ {subj}: {perc}% → Good. Did great!")
else: # 90-100
remarks.append(f"🌟 {subj}: {perc}% → Amazing performance!")
# Plot
colors = []
for subj, perc in zip(subjects, percentages):
if perc <= 33:
colors.append("red")
elif perc <= 70:
colors.append("orange")
elif perc <= 89:
colors.append("skyblue")
else:
colors.append("green")
plt.figure(figsize=(6,4))
plt.bar(subjects, percentages, color=colors, edgecolor="black")
plt.axhline(avg, color="purple", linestyle="--", label=f"Numerical Average of Subjects: {avg:.2f}%")
plt.legend()
plt.title("Student Performance Analysis")
plt.xlabel("Subjects")
plt.ylabel("Percentage (%)")
plt.ylim(0, 110)
return "\n".join(remarks), plt.gcf()
app = gr.Interface(
fn=analyze,
inputs=gr.File(label="Upload CSV", type="filepath"),
outputs=["text", "plot"]
)
app.launch()
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