semvec/pypi-packages huggingface dataset:
tabotools 0.1.6
A data tools library for loading, preprocessing, exploratory analysis, and visualization.
License: MIT
Requires Python: >=3.6

# TaboTools

TaboTools is a Python library designed to streamline data processing workflows, including file loading, data preprocessing, exploratory analysis, and visualization. This package provides a set of tools to simplify the tasks of cleaning, analyzing, and visualizing your data.

## Features

- **File Loading:** Automatically loads data from various file formats.
- **Data Preprocessing:** Checks data types, detects full and implicit duplicates, and processes date columns.
- **Exploratory Data Analysis:** Provides quick statistical insights and analysis of different feature types.
- **Data Visualization:** Generates customizable visualizations to aid in data understanding.

## Installation

You can install TaboTools directly from PyPI:

```bash
pip install tabotools
```

## Usage

Below is an example of how to use the DataProcessor class provided by TaboTools. In this example, we initialize the processor with an abstract file path and specify which columns should be parsed as dates.

```python
from tabotools import DataProcessor

# Initialize the DataProcessor with a generic data file and a list of date columns.
data_processor = DataProcessor(
    file_path='data/sample_data.csv',
    parse_dates=['created_at', 'updated_at', 'published_at']
)

# Run data preprocessing: this method checks data types and identifies duplicate records.
data_processor.data_preprocessor()

# Perform exploratory data analysis by specifying the target feature.
data_processor.eda(target_value='sale_price')

# Display dataset information including:
# - File path and source
# - DataFrame name or identifier
# - Lists of categorical, numerical, and time columns
# - The designated target feature
data_processor.info()
```
## Dependencies

TaboTools requires the following libraries:

- Python
- pandas
- matplotlib
- seaborn
- IPython

## Contributing

Contributions to TaboTools are welcome! If you have any suggestions, bug fixes, or improvements, please open an issue or submit a pull request.

## License

This project is licensed under the MIT License – see the [LICENSE](LICENSE) file for details.
int-encoder 1.0.1
A library for encoding and decoding integers using modular arithmetic
License: MIT
Keywords: integer, encoding, modular arithmetic, decoding, encryption

# int_encoder

`int_encoder` is a Python library for encoding and decoding integers using modular arithmetic.

## Installation

To install the library from PyPI, simply run:

```bash
pip3 install int-encoder
```

## Configuration

The library uses two configuration constants, defined in `config.py`:

- `INT_ENCODE_KEY`: The key used for encoding and decoding integers.
- `INT_ENCODED_MAX`: The maximum value for the encoded integer.

These values can be modified in `config.py` to suit your needs.


## Usage

```python
import int_encoder

# Modify configuration constants (optional)
int_encoder.config.INT_ENCODE_KEY = 987654321  # New key for encoding
int_encoder.config.INT_ENCODED_MAX = 2 ** 16   # New maximum value for encoded integers

# Example usage
int_to_encode = 123456
encoded_value = int_encoder.encode(int_to_encode)
print(f"Encoded value: {encoded_value}")

decoded_value = int_encoder.decode(encoded_value)
print(f"Decoded value: {decoded_value}")
```