Add a sample notebook. Refactor regression out.

build/

dist/

xlap.egg-info/

.ipynb_checkpoints/

 No newline at end of file

import math

import numpy as np

import matplotlib.pyplot as plt

from sklearn import linear_model

plt.rcParams["figure.figsize"] = (16, 9)

plt.rcParams.update({'figure.autolayout': True})

# TODO: Refactor.

def regress(df, column):

    x = df.index.values.reshape(-1, 1)

    y = df[column].values

    model = linear_model.LinearRegression()

    model.fit(x, y)

    print("R-Score:", model.score(x, y))

    plt.scatter(x, y)

    plt.grid()

    plt.plot(x, model.predict(x), color="red", linewidth=3)

def trace(df, title, export=False):

from sklearn import linear_model

import matplotlib.pyplot as plt

def linear(data_frame, column):

    """

    Execute a simple linear regression on the given column for the passed data_frame.

    :param data_frame:

    :param column:

    :return:

    """

    x = data_frame.index.values.reshape(-1, 1)

    y = data_frame[column].values

    model = linear_model.LinearRegression()

    model.fit(x, y)

    print("R-Score:", model.score(x, y))

    plt.scatter(x, y)

    plt.grid()

    plt.plot(x, model.predict(x), color="red", linewidth=3)

    plt.show()