├── file2
├── README.md
└── file1


/file2:
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 1 | import pandas as pd
 2 | import plotly.express as px
 3 | from datetime import timedelta
 4 | 
 5 | # Read Excel file (example structure: Task, Start, Duration (days), Assigned To)
 6 | df_excel = pd.read_excel("tasks.xlsx")
 7 | 
 8 | # Convert Start to datetime and compute Finish
 9 | df_excel["Start"] = pd.to_datetime(df_excel["Start"])
10 | df_excel["Finish"] = df_excel["Start"] + df_excel["Duration (days)"].apply(lambda x: timedelta(days=int(x)))
11 | 
12 | # Gantt Chart
13 | fig = px.timeline(df_excel, x_start="Start", x_end="Finish", y="Task", color="Assigned To", title="Gantt Chart - From Excel")
14 | fig.update_yaxes(categoryorder="total ascending")
15 | fig.show()
16 | 


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/README.md:
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 1 | # 📅 Gantt Chart Auto-Generation from Task Descriptions
 2 | 
 3 | A Streamlit-powered web app that automatically generates interactive Gantt charts from either natural language task descriptions or structured Excel sheets. Ideal for project managers, data teams, and researchers.
 4 | 
 5 | ---
 6 | 
 7 | ## 🚀 Features
 8 | 
 9 | - ✅ Parse tasks from Excel or structured descriptions
10 | - ✅ Support for natural language inputs (e.g. “Alice will collect data from April 1 for 5 days”)
11 | - ✅ Gantt chart generation using Plotly
12 | - ✅ Task dependencies & critical path visualization
13 | - ✅ Track task progress with completion percentages
14 | - ✅ Export charts as HTML or PDF
15 | - ✅ Clean UI built with Streamlit
16 | 
17 | ---
18 | 
19 | ## 🛠️ Installation
20 | 
21 | Clone this repo and install dependencies:
22 | 
23 | ```bash
24 | git clone https://github.com/Akajiaku1/gantt-chart-generator.git
25 | cd gantt-chart-generator
26 | pip install -r requirements.txt
27 | 


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/file1:
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 1 | import pandas as pd
 2 | import plotly.express as px
 3 | import re
 4 | from datetime import datetime, timedelta
 5 | 
 6 | # Step 1: Synthetic Task Descriptions
 7 | task_descriptions = [
 8 |     "Task: Data Collection, Start: 2025-04-01, Duration: 5 days, Assigned to: Alice",
 9 |     "Task: Data Cleaning, Start: 2025-04-06, Duration: 3 days, Assigned to: Bob",
10 |     "Task: Feature Engineering, Start: 2025-04-09, Duration: 4 days, Assigned to: Alice",
11 |     "Task: Model Training, Start: 2025-04-13, Duration: 7 days, Assigned to: Carol",
12 |     "Task: Evaluation & Testing, Start: 2025-04-20, Duration: 3 days, Assigned to: Bob",
13 |     "Task: Report Generation, Start: 2025-04-23, Duration: 2 days, Assigned to: Alice"
14 | ]
15 | 
16 | # Step 2: Parse Descriptions into Structured Data
17 | def parse_description(desc):
18 |     task_match = re.search(r"Task:\s*(.*?),", desc)
19 |     start_match = re.search(r"Start:\s*([\d\-]+),", desc)
20 |     duration_match = re.search(r"Duration:\s*(\d+)\s*days", desc)
21 |     person_match = re.search(r"Assigned to:\s*(\w+)", desc)
22 | 
23 |     task = task_match.group(1).strip()
24 |     start = datetime.strptime(start_match.group(1), "%Y-%m-%d")
25 |     duration = int(duration_match.group(1))
26 |     end = start + timedelta(days=duration)
27 |     person = person_match.group(1)
28 | 
29 |     return {
30 |         "Task": task,
31 |         "Start": start,
32 |         "Finish": end,
33 |         "Assigned To": person
34 |     }
35 | 
36 | task_data = [parse_description(desc) for desc in task_descriptions]
37 | df_tasks = pd.DataFrame(task_data)
38 | 
39 | # Step 3: Generate Gantt Chart
40 | fig = px.timeline(df_tasks, x_start="Start", x_end="Finish", y="Task", color="Assigned To", title="Gantt Chart - Auto Generated from Descriptions")
41 | fig.update_yaxes(categoryorder="total ascending")
42 | fig.show()
43 | 


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