File size: 1,714 Bytes
597120e 5fefb8a 597120e 5fefb8a 597120e 5fefb8a 597120e 5fefb8a 597120e 5fefb8a 597120e 5fefb8a |
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 matplotlib.pyplot as plt
import os
# Function to visualize student progress
def visualize_progress(file):
# Check if the file is a valid CSV file
if file is None:
return "No file uploaded!"
try:
# Read the CSV file using pandas
df = pd.read_csv(file.name)
# Check if required columns exist in the CSV
required_columns = {'student_name', 'date', 'score'}
if not required_columns.issubset(df.columns):
return "CSV should contain 'student_name', 'date', and 'score' columns."
# Create a progress plot for each student
plt.figure(figsize=(10, 6))
for student in df['student_name'].unique():
student_data = df[df['student_name'] == student]
plt.plot(student_data['date'], student_data['score'], label=student)
# Customize the chart
plt.xlabel('Date')
plt.ylabel('Score')
plt.title('Student Progress Over Time')
plt.legend()
plt.grid(True)
# Save the plot to a file
plot_filename = "progress.png"
plt.savefig(plot_filename)
plt.close()
return plot_filename
except Exception as e:
return f"Error: {e}"
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("# Student Progress Analysis Tool")
# File input for CSV and display output
file_input = gr.File(label="Upload Student Data (CSV)")
output_image = gr.Image(label="Progress Chart")
# Call the visualize_progress function when the file changes
file_input.change(visualize_progress, inputs=file_input, outputs=output_image)
# Launch the Gradio app
demo.launch()
|