Histograms_automation

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Histograms_automation

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This project automates histogram construction and frequency distribution table generation from numerical datasets using pure Python implementation. Developed as part of CIS 240 Statistical Analysis course at the Faculty of Computer and Information Sciences, Ain Shams University.

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# Histogram Automation for Statistical Analysis
A Python tool that automates the creation of histograms and frequency distribution tables from datasets, following theoretical statistical analysis methodology.
## Live Coding Session
Watch the full development process: [[Video](https://youtu.be/q8hvJiqmIGY?si=vNVU0SRqgL_fPXx_)]
## Academic Context
**Institution:** Faculty of Computer and Information Sciences, Ain Shams University  
**Course:** CIS 240 - Statistical Analysis  
**Special Thanks:** Dr. Ghada Hamed, Dr. Fatma Naguib, Dr. Diaa and all TAs for the excellent teaching and guidance throughout this course
## Features
- Automatically calculates statistical measures (min, max, range, sample size)
- Determines optimal number of subintervals using √n method
- Computes frequency and relative frequency distributions
- Generates side-by-side frequency table and histogram visualization
- Handles decimal precision automatically based on dataset
## Technologies
- **Python 3.13**
- **Matplotlib** (visualization only)
- No pandas, no numpy - pure Python implementation
## Methodology
The project follows standard statistical histogram construction steps:
1. Find minimum and maximum data points
2. Calculate range (max - min)
3. Determine subintervals using √n (rounded up)
4. Calculate interval width: Range / Number of subintervals
5. Create interval boundaries with consistent decimal precision
6. Count frequencies for each interval
7. Generate frequency table and histogram
## Usage
1. Prepare your dataset as a CSV file (comma-separated values)
2. Update the filename in the code:
```py
file = open("dataset_1.csv", "rt")
```
3. Run the script:
```bash
python histogram_generator.py
```
## Input Format
The dataset should be a CSV file with comma-separated numerical values:
```csv
2.0,3.0,0.3,3.3,1.3,0.4,0.2,6.0,5.5,6.5,0.2,2.3,1.5,4.0,5.9,1.8,4.7,0.7,4.5,0.3,1.5,0.5,2.5,5.0,1.0,6.0,5.6,6.0,1.2,0.2
```
## Output
- Console output with all statistical measures
- Interactive matplotlib window displaying:
- Frequency distribution table (left):

![table_pic](https://raw.githubusercontent.com/Abdrrrahman/Histograms_automation/main/attachments/table.png)

- Histogram visualization (right):

![histogram_pic](https://raw.githubusercontent.com/Abdrrrahman/Histograms_automation/main/attachments/histogram.png)

## Example Output
The tool generates a comprehensive view with:
- Intervals column showing data ranges
- Frequency counts for each interval
- Relative frequencies (as decimals)
- Visual histogram with proper binning
## Educational Context
This project was developed as part of a theoretical statistical analysis course, demonstrating the practical implementation of histogram construction principles taught in statistics classes.
## License
MIT License - Feel free to use for educational purposes
## Contributing
This is an educational project, but suggestions and improvements are welcome!

---

_Developed as part of Statistical Analysis coursework - demonstrating core concepts without relying on high-level data science libraries._

Histograms_automation

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