StatAssist 1.0.6

Math tools for private or personal use.

StatAssist

StatAssist is a python library that provides statistical and mathematical functions as well as built-in algorithms such as integration and linear regression.

Installation

You can install StatAssist using pip:

pip install StatAssist==1.0.6

Usage

Example 1:

from StatAssist import statistics_ as stats
import matplotlib.pyplot as plt

# Define data
x_data = [0, 1, 2, 3, 4, 5]
y_data = [0, 2, 4, 6, 8, 10]

# Get statistical information
averages = stats.get_means(x_data, y_data)
variances = stats.get_variance([x_data, y_data], averages)

covariance_xy = stats.get_covariance([x_data, y_data], averages)
correlation = stats.get_correlation_coefficient(covariance_xy, variances[0], variances[1])

# Get linear regression parameters
m = stats.get_linreg_slope(correlation, variances[0], variances[1])
b = stats.ml_linreg_1([x_data, y_data], slope=m)

y_reg = [m*x + b for x in x_data]

# Display plot
plt.scatter(x_data, y_data, color='b')
plt.plot(x_data, y_reg, color='r')

plt.show()

Example 2:

from StatAssist import algorithms_
import matplotlib.pyplot as plt

lin_reg = algorithms_.linear_regression

# Define data
x_data = [0, 1, 2, 3, 4, 5]
y_data = [0, 2, 4, 6, 8, 10]

# Linear regression of data
m, b = lin_reg([x_data, y_data])

y_reg = [m*x + b for x in x_data]

# Display plot
plt.scatter(x_data, y_data, color='b')
plt.plot(x_data, y_reg, color='r')

plt.show()

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Licencse

MIT