Data Visualizations in Python

The statsmodels module in Python offers a variety of functions and classes that allow you to fit various statistical models. The following…

One way to visualize the performance of classification models in machine learning is by creating a ROC curve, which stands for “receiver…

You can use the regplot() function from the seaborn data visualization library to plot a logistic regression curve in Python: import seaborn…

A Pareto chart is a type of chart that displays the ordered frequencies of categories along with the cumulative frequencies of categories.…

Principal components analysis (PCA) is an unsupervised machine learning technique that finds principal components (linear combinations of the predictor variables) that explain…

When using classification models in machine learning, two metrics we often use to assess the quality of the model are precision and…

You can use the following basic syntax to calculate the cumulative distribution function (CDF) in Python: #sort data x = np.sort(data) #calculate…

A log-log plot is a plot that uses logarithmic scales on both the x-axis and the y-axis. This type of plot is…

Often you may want to fit a curve to some dataset in Python. The following step-by-step example explains how to fit curves…

Logistic Regression is a statistical method that we use to fit a regression model when the response variable is binary. To assess how well…