https://github.com/danyal-faheem/project-logs-analyzer
This repo contains scripts to analyze project logs and display some charts related to the data
https://github.com/danyal-faheem/project-logs-analyzer
data data-visualization matplotlib pandas python streamlit
Last synced: about 2 months ago
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This repo contains scripts to analyze project logs and display some charts related to the data
- Host: GitHub
- URL: https://github.com/danyal-faheem/project-logs-analyzer
- Owner: Danyal-Faheem
- Created: 2025-04-10T13:18:36.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-10T15:54:51.000Z (about 1 year ago)
- Last Synced: 2025-04-11T05:39:44.839Z (about 1 year ago)
- Topics: data, data-visualization, matplotlib, pandas, python, streamlit
- Language: Python
- Homepage:
- Size: 277 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Project Logs Analyzer
A simple Streamlit app to analyze and visualize your work logs from CSV files. This tool gives you insights into how your time is spent across days, tasks, and subteams.
---
## 🚀 Features
The app provides multiple visualizations based on your uploaded project logs files:
### 📅 1. Average Hours per Day of the Week
A bar chart showing how many hours you typically work on each weekday.

### 📘 2. Percentage of Time Spent on Each Task Type
A pie chart showing how your overall time is divided among different task types.

### 📈 3. Task Type Breakdown by Weekday
A stacked bar chart showing what percentage of your time each weekday goes into which task.

### 👥 4. Percentage of Time Spent Each Day on Each SubTeam
A stacked bar chart showing which subteams you worked on each weekday.

### 🔍 5. Task Breakdown for Each SubTeam
Multiple pie charts displayed side-by-side showing how time is distributed across tasks for each subteam.

---
## 📝 Input Format
Upload one or more CSV files with the following columns:
- `Person`
- `Team`
- `SubTeam`
- `Date`
- `Hours`
- `Description` (Tasks should be written in square brackets, like `[Coding] - Fixed issue...`)
---
## ⚙️ How to Run
### 1. Clone the repo (or download the script)
```bash
git clone https://github.com/your-username/time-log-analyzer.git
cd time-log-analyzer
```
### 2. Install dependencies
```bash
pip install -r requirements.txt
```
### 3. Run the Streamlit app
```bash
streamlit run analyzer.py
```
---
## 📂 Example Usage
- Drag and drop one or more CSV log files into the app.
- The charts will be rendered based on the data in those files.
- If a required column is missing, the app will display a helpful error message.