Metadata-Version: 2.1
Name: fifids
Version: 0.1.1
Summary: data science for swiss cheese brains
Author: fibleep
Author-email: filipn924@gmail.com
Requires-Python: >=3.9,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: polars (>=0.20.18,<0.21.0)
Requires-Dist: pyarrow (>=15.0.2,<16.0.0)
Requires-Dist: scikit-learn (>=1.4.1.post1,<2.0.0)
Requires-Dist: seaborn (>=0.13.2,<0.14.0)
Requires-Dist: shap (>=0.45.0,<0.46.0)
Requires-Dist: statsmodels (>=0.14.1,<0.15.0)
Requires-Dist: xgboost (>=2.0.3,<3.0.0)
Description-Content-Type: text/markdown

# Fifi
## data science for swiss cheese brains

Fifi is a pypi package for quick eda and modelling made specifically for use with Jupyter Notebooks.
Use `??` as much as possible to see the code and adapt it for your needs. The package will guide you through the usual EDA process.

The package is meant be a source of cool plots or workflows and be able to use them within Jupyter without having to look at documentation every time.

## Installation

```bash
pip install fifids
```

## Usage

```python
from fifids import Fifi
import pandas as pd
import polars as pl

df = pd.read_csv("data.csv")
# OR POLARS
df = pl.read_csv("data.csv")
# Note from author: eventually, right now it breaks with polars, but I'm working on it

# Specify the target column and if the data is time series or not
# Time series enables a branch with more plots and a different train/test split
fifi = Fifi(df, target="target_column", time_series=True)

fifi.describe()
# OR
fifi.plots()
# OR
fifi.outliers()
# OR
fifi.pipeline()
```

Once you call a function, it will usually print something to guide you through the process. You can also use the `??` to see the code.

