Spaces:
Sleeping
Sleeping
File size: 6,177 Bytes
be1bbc0 23a0c99 0b4a8f9 ba87418 be1bbc0 23a0c99 ba87418 be1bbc0 23a0c99 be1bbc0 0b4a8f9 1967c28 ba87418 1967c28 0b4a8f9 1967c28 0b4a8f9 1967c28 94d74f3 a4dcfdb 94d74f3 23a0c99 0b4a8f9 23a0c99 0b4a8f9 1967c28 0b4a8f9 23a0c99 0b4a8f9 be1bbc0 0b4a8f9 23a0c99 0b4a8f9 1967c28 0b4a8f9 1967c28 0b4a8f9 1967c28 0b4a8f9 1967c28 0b4a8f9 23a0c99 0b4a8f9 be1bbc0 0228322 1967c28 a4dcfdb 1967c28 a4dcfdb 1967c28 0228322 1967c28 0228322 1967c28 a4dcfdb 1967c28 a4dcfdb 1967c28 a4dcfdb 1967c28 23a0c99 1967c28 0b4a8f9 1967c28 be1bbc0 0b4a8f9 1967c28 0b4a8f9 1967c28 0b4a8f9 23a0c99 0b4a8f9 1967c28 0b4a8f9 23a0c99 1967c28 a4dcfdb be1bbc0 0b4a8f9 a4dcfdb 1967c28 23a0c99 1967c28 be1bbc0 23a0c99 1967c28 |
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 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 |
import gradio as gr
import pandas as pd
import io
import plotly.express as px
import plotly.graph_objects as go
import os
# Define admin credentials
ADMIN_EMAIL = os.environ["ACCOUNT"]
ADMIN_PASSWORD = os.environ["PASSWORD"]
# Variable to store uploaded grades file in memory
grades_df = None
# Admin login function
def admin_login_function(email, password):
if (email == ADMIN_EMAIL and password == ADMIN_PASSWORD):
return gr.update(visible=False), gr.update(visible=True),
else:
raise gr.Error("wrong password 💥!", duration=5)
# Intern login function
def intern_login(email):
results = intern_view(email)
return gr.update(visible=False), gr.update(visible=True), results[0], results[1]
# Admin upload function
def admin_upload(file):
global grades_df
if file is not None:
grades_df = pd.read_excel(file.name)
return "File uploaded and processed successfully."
else:
return "Please upload a valid Excel file."
# Function to generate performance analysis charts
def performance_analysis():
if grades_df is not None:
# Ensure 'Created At' is datetime
grades_df['Created At'] = pd.to_datetime(grades_df['Created At'])
grades_df['Date'] = grades_df['Created At'].dt.date
# Group by date and calculate sum of grades
daily_performance = grades_df.groupby('Date')['Grade'].sum().reset_index()
# Line chart for daily performance
line_chart = px.line(daily_performance, x='Date', y='Grade', title='Daily Performance (Total Grades)')
email_performance = grades_df.groupby('Email')['Grade'].sum().reset_index()
# Histogram of grades
histogram = px.histogram(email_performance, x='Grade', nbins=20, title='Grade Distribution')
# Box plot for grade statistics
box_plot = px.box(email_performance, y='Grade', title='Grade Statistics')
# Create a summary table
summary_stats = email_performance['Grade'].describe().reset_index()
summary_table = go.Figure(data=[go.Table(
header=dict(values=['Statistic', 'Value']),
cells=dict(values=[summary_stats['index'], summary_stats['Grade']])
)])
return line_chart, histogram, box_plot, summary_table
else:
return None, None, None, None
MAX_SCORE = 25*2 # Assuming the maximum possible score is 100
def intern_view(email):
if grades_df is not None:
intern_grades = grades_df[grades_df['Email'] == email]
daily_performance = intern_grades.groupby('Date')['Grade'].sum().reset_index()
line_chart = px.line(daily_performance, x='Date', y='Grade', title='Daily Performance (Total Grades)')
if not intern_grades.empty:
total_grade = intern_grades['Grade'].sum()
average_grade = intern_grades['Grade'].mean()
num_records = intern_grades.shape[0]
# Normalize the score to MAX_SCORE
normalized_score = min(total_grade / MAX_SCORE, 1)
# Determine the color level
if normalized_score <= 0.8:
color = "red"
else:
color = "green"
# <div style="background-color:{color}; padding:10px; border-radius:5px;">
# **Performance Level**: {color.capitalize()}
# </div>
# - Quá 3 assignment đạt level đỏ sẽ phải liên hệ manager để giải trình
# Return as a Markdown formatted string
return f"""
### Grade Analysis for {email}
- **Tổng điểm**: {normalized_score}
- **số lần upload**: {num_records}
""", line_chart
else:
return gr.Error("No records found for this email. 💥!", duration=5)
else:
return gr.Error("No grades file uploaded. Please contact the admin.", duration=5)
# Create the Gradio interface
with gr.Blocks() as demo:
with gr.Tab("Admin Login"):
with gr.Column(visible=True) as admin_login_section:
admin_email = gr.Textbox(label="Admin Email")
admin_password = gr.Textbox(label="Admin Password", type="password")
admin_login_button = gr.Button("Login")
admin_login_output = gr.Textbox(label="Admin Output")
with gr.Column(visible=False) as admin_upload_section:
with gr.Column() as update_file_section:
admin_file = gr.File(label="Upload Grades Excel File")
admin_submit = gr.Button("Submit")
admin_file_output = gr.Textbox(label="File Upload Output")
admin_analyze = gr.Button("Analyze")
admin_charts = gr.Plot()
admin_histogram = gr.Plot()
admin_box_plot = gr.Plot()
admin_summary_table = gr.Plot()
admin_login_button.click(
admin_login_function,
inputs=[admin_email, admin_password],
outputs=[admin_login_section, admin_upload_section],
show_progress=True,
)
admin_submit.click(
admin_upload,
inputs=[admin_file],
outputs=admin_file_output,
)
admin_analyze.click(
performance_analysis,
outputs=[admin_charts, admin_histogram, admin_box_plot, admin_summary_table],
)
with gr.Tab("Intern Login"):
with gr.Column(visible=True) as intern_login_section:
intern_email = gr.Textbox(label="Intern Email")
intern_login_button = gr.Button("Find")
intern_login_output = gr.Textbox(label="Intern Output")
with gr.Column(visible=False) as intern_info_section:
intern_output = gr.Markdown(label="Grade Analysis")
intern_charts = gr.Plot()
intern_login_button.click(
intern_login,
inputs=[intern_email],
outputs=[intern_login_section, intern_info_section, intern_output, intern_charts],
show_progress=True,
)
# intern_submit.click(
# intern_view,
# inputs=[intern_email],
# outputs=intern_output,
# )
# Launch the app
demo.launch(debug=True)
|