semvec/pypi-packages huggingface dataset:
lightkde 1.0.4
Lightning fast, lightweight, and reliable kernel density estimation.
Requires Python: >=3.7

# lightkde

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A lightning fast, lightweight, and reliable kernel density estimation.

* Easy to use, e.g. ``density_vec, x_vec = kde_1d(sample_vec=sample)``\.
* Works with 1d and 2d samples.
* Works with weighted samples as well.
* Based on the MATLAB implementations of Botev:
  [kde](https://www.mathworks.com/matlabcentral/fileexchange/14034-kernel-density-estimator),
  [kde2d](https://www.mathworks.com/matlabcentral/fileexchange/17204-kernel-density-estimation).

![alt text](https://gist.githubusercontent.com/rozsasarpi/022fa396c919fbedabcd78fde9d1801a/raw/9822c2d457fcd5a7ef9b06350f14c9f16ae80b71/illustrative_image.svg)


## Install

```bash
pip install lightkde
```

## Usage

```python
import numpy as np
from lightkde import kde_1d

sample = np.random.randn(1000)

density_vec, x_vec = kde_1d(sample_vec=sample)
```

For further examples see the [documentation](https://lightkde.readthedocs.io/en/latest).

## Other kde packages

Other python packages for kernel density estimation:

* [scipy.stats.gaussian_kde](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.gaussian_kde.html)
* [KDEpy](https://github.com/tommyod/KDEpy)
rock-pre-h 0.1.5
rock-for-easy-preprocessing
Requires Python: >=3.9.13

# Package for easy data preprocessing

- corr
  - make_pvalue_df
  - make_ttest_df
  - make_ANOVA_df
  - make_crosstab_df
- plots
  - make_corr_heatmap
  - make_distplots
  - make_boxplots
  - make_barplots
- useful
  - createFolder
  - checkNAN
  - handle_NAN
  - NAN_preview
  - check_features
  - check_unique
  - how_to_use_handle_NAN