# simplebins
**simplebins** is a lightweight Python utility that makes it easy to bin numeric values into equal-width intervals.
It supports individual numbers, lists and `pandas.Series`.
## Features
- Works with numbers, lists and `pandas.Series`
- Returns either the bin index, floor, ceiling, midpoint, or a human-readable label
- Clean and intuitive API
- Handles missing values gracefully
- Zero dependencies outside of `pandas` and `numpy`
## Why not `pandas.cut()`?
`pandas.cut()` is powerful but sometimes overkill.
**simplebins** simplifies the common use case: fixed-width bins with predictable, numeric output – perfect for quick transformations.
## Installation
```bash
pip install simplebins
```
## Usage
```python
from simplebins import cut
```
### Bin a single number
```python
cut(12, binwidth=5)
# Output: 10
```
### Bin a list of numbers
```python
cut([3, 7, 12], binwidth=5)
# Output: [0, 5, 10]
```
### Bin a pandas Series
```python
import pandas as pd
import numpy as np
cut(pd.Series([3, 7, np.nan]), binwidth=5)
# Output:
# 0 0
# 1 5
# 2 nan
# dtype: object
```
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"description": "# simplebins\n\n**simplebins** is a lightweight Python utility that makes it easy to bin numeric values into equal-width intervals. \nIt supports individual numbers, lists and `pandas.Series`.\n\n\n## Features\n\n- Works with numbers, lists and `pandas.Series` \n- Returns either the bin index, floor, ceiling, midpoint, or a human-readable label \n- Clean and intuitive API \n- Handles missing values gracefully \n- Zero dependencies outside of `pandas` and `numpy`\n\n\n## Why not `pandas.cut()`?\n\n`pandas.cut()` is powerful but sometimes overkill. \n**simplebins** simplifies the common use case: fixed-width bins with predictable, numeric output \u2013 perfect for quick transformations.\n\n\n## Installation\n\n```bash\npip install simplebins\n```\n\n\n## Usage\n\n```python\nfrom simplebins import cut\n```\n\n### Bin a single number\n```python\ncut(12, binwidth=5)\n# Output: 10\n```\n\n### Bin a list of numbers\n```python\ncut([3, 7, 12], binwidth=5)\n# Output: [0, 5, 10]\n```\n\n### Bin a pandas Series\n```python\nimport pandas as pd\nimport numpy as np\ncut(pd.Series([3, 7, np.nan]), binwidth=5)\n# Output: \n# 0 0\n# 1 5\n# 2 nan\n# dtype: object\n```\n",
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