- matplotlib
- numpy
- pandas
- scikit-learn
print("Now you can write python in HTML with py-script tag!")
import matplotlib.pyplot as plt
import numpy as np
from sklearn.linear_model import LinearRegression
x = [5,7,8,7,2,17,2,9,4,11,12,9,6]
y = [99,86,87,88,111,86,103,87,94,78,77,85,86]
print("Plotting specific points")
fig, ax = plt.subplots()
ax.scatter(x, y)
fig # if we put fig as the last line, it will execute - pyscript.write('scatterplot', fig)
import matplotlib.pyplot as plt
import numpy as np
x = np.random.randn(1000)
y = np.random.randn(1000)
print("Plotting 1000 random points")
fig, ax = plt.subplots()
ax.scatter(x, y)
fig
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
x = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
y = np.dot(x, np.array([1, 2])) + 3
reg = LinearRegression().fit(x, y)
z = reg.predict(np.array([[3, 5]]))
print("Linear predictive model")
print(z)