data/examples_database/txt_docs/Advanced - Smoothing.txt

--- Cell 1 ---
Advanced - Smoothing.ipynb

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from pangaeapy import PanDataSet
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d

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ds=PanDataSet(894182)

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ds.data.head()

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### Smoothing with Scipy's interp1d quadratic spline function

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#Bet
x=ds.data['Age']
y=ds.data['Bet']

f = interp1d(x, y, kind='quadratic')

#setting the number of x values for oversampling
xnew = np.linspace(min(x),max(x) ,2000)

plt.figure(figsize = (12,5))
plt.plot(x, y, 'o', xnew, f(xnew), '-')
plt.xlabel('xlabel')
#plt.plot(x_smooth, y_spline, 'red', linewidth=1)

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### Smooting with Scipy's UnivariateSpline

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from scipy.interpolate import UnivariateSpline

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f2 = UnivariateSpline(x, y)
plt.figure(figsize = (12,5))
plt.plot(x, y, 'o',xnew, f2(xnew), '-')

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### Making the line very smooth by setting the smoothness factor

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f2.set_smoothing_factor(20000)
plt.figure(figsize = (12,5))
plt.plot(x, y, 'o',xnew, f2(xnew), '-')

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