# 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()
```
Raw data
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"description": "# ProphetLite\n Like Prophet but in numba and all fit with LASSO\n\n## A basic comparison vs Prophet:\n```\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom prophet import Prophet\n\n\ndf = pd.read_csv('https://raw.githubusercontent.com/facebook/prophet/main/examples/example_wp_log_peyton_manning.csv')\nm = Prophet(weekly_seasonality=False)\nm.fit(df, )\nfuture = m.make_future_dataframe(periods=365)\nforecast = m.predict(future)\nm.plot(forecast)\nm.plot_components(forecast)\nplt.show()\n```\n## Now for ProphetLite\n You must pass your data as a numpy array\n```\n y = df['y'].values\n```\n Now to build the class and pass the seasonality\n```\nfrom ProphetLite.prophetlite import ProphetLite \n\n\npl = ProphetLite()\nfitted = pl.fit(y, [365.25]) #To pass multiple seasonalities just add more nu\npredicted = pl.predict(365)\n```\n Some Plotting helper methods\n```\n pl.plot()\n```\n```\n pl.plot_components()\n```\n## Comparison Plots\n```\n plt.plot(np.append(fitted['yhat'], predicted['yhat']), alpha=.3)\n plt.plot(forecast['yhat'], alpha=.3)\n plt.show()\n```\nThe Trend Components:\n```\n plt.plot(np.append(fitted['trend'], predicted['trend']))\n plt.plot(forecast['trend'])\n plt.show()\n```\n",
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