semvec/pypi-packages huggingface dataset:
ProphetLite 0.0.2
Like Prophet but using Numba and LASSO.
Keywords: forecasting,time series,seasonality,trend

# ProphetLite
 Like Prophet but in numba and all fit with LASSO

## A basic comparison vs Prophet:
```
import pandas as pd
import matplotlib.pyplot as plt
from prophet import Prophet


df = pd.read_csv('https://raw.githubusercontent.com/facebook/prophet/main/examples/example_wp_log_peyton_manning.csv')
m = Prophet(weekly_seasonality=False)
m.fit(df, )
future = m.make_future_dataframe(periods=365)
forecast = m.predict(future)
m.plot(forecast)
m.plot_components(forecast)
plt.show()
```
## Now for ProphetLite
 You must pass your data as a numpy array
```
    y = df['y'].values
```
 Now to build the class and pass the seasonality
```
from ProphetLite.prophetlite import ProphetLite 


pl = ProphetLite()
fitted = pl.fit(y, [365.25]) #To pass multiple seasonalities just add more nu
predicted = pl.predict(365)
```
 Some Plotting helper methods
```
    pl.plot()
```
```
    pl.plot_components()
```
## Comparison Plots
```
    plt.plot(np.append(fitted['yhat'], predicted['yhat']), alpha=.3)
    plt.plot(forecast['yhat'], alpha=.3)
    plt.show()
```
The Trend Components:
```
    plt.plot(np.append(fitted['trend'], predicted['trend']))
    plt.plot(forecast['trend'])
    plt.show()
```
streamlit-ketchersa 0.0.2
This library is a streamlit app for chemical or medical use that open and draw small molecules
Requires Python: >=3.6
Keywords: chemistry,molecule,streamlit

[![Open in Huggingface](https://huggingface.co/datasets/huggingface/badges/raw/refs%2Fpr%2F11/open-in-hf-spaces-md-dark.svg)](https://huggingface.co/spaces/z-uo/DrawMaleculeKetcher)

# Streamlit Ketcher Standalone
A Streamlit library for create and open small molecule based on [Ketcher](https://github.com/epam/ketcher/tree/master/packages/ketcher-standalone).

|White theme|
|-----------|
|![streamlit app screenshot](https://gitlab.com/nicolalandro/streamlit-ketchersa/-/raw/main/imgs/white.png)|

Install from pipy:

```
pip install streamlit_ketchersa
```

Example of usage:

```
import streamlit as st
from streamlit_ketchersa import streamlit_ketchersa

result = streamlit_ketchersa()
st.markdown(result)
```