Total 15 Posts

How to Set Axis Range (xlim, ylim) in Matplotlib

Introduction

Matplotlib is one of the most widely used data visualization libraries in Python. Much of Matplotlib's popularity comes from its customization options - you can tweak just about any element from its hierarchy of objects.

In this tutorial, we'll take a look at how to set the axis range

Seaborn Scatter Plot - Tutorial and Examples

Introduction

Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. It offers a simple, intuitive, yet highly customizable API for data visualization.

In this tutorial, we'll take a look at how to plot a scatter plot in Seaborn. We'll cover simple

Matplotlib Scatter Plot - Tutorial and Examples

Introduction

Matplotlib is one of the most widely used data visualization libraries in Python. From simple to complex visualizations, it's the go-to library for most.

In this tutorial, we'll take a look at how to plot a scatter plot in Matplotlib.

Import Data

We'll be using the Ames Housing dataset

Change Figure Size in Matplotlib

Introduction

Matplotlib is one of the most widely used data visualization libraries in Python. Much of Matplotlib's popularity comes from its customization options - you can tweak just about any element from its hierarchy of objects.

In this tutorial, we'll take a look at how to change a figure size

Kernel Density Estimation in Python Using Scikit-Learn

Introduction

This article is an introduction to kernel density estimation using Python's machine learning library scikit-learn.

Kernel density estimation (KDE) is a non-parametric method for estimating the probability density function of a given random variable. It is also referred to by its traditional name, the Parzen-Rosenblatt Window method, after its

Deep Learning in Keras - Data Preprocessing

Introduction

Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.

In many of these applications, deep learning

Statistical Hypothesis Analysis in Python with ANOVAs, Chi-Square, and Pearson Correlation

Introduction

Python is an incredibly versatile language, useful for a wide variety of tasks in a wide range of disciplines. One such discipline is statistical analysis on datasets, and along with SPSS, Python is one of the most common tools for statistics.

Python’s user-friendly and intuitive nature makes running

Calculating Mean, Median, and Mode in Python

Introduction

When we're trying to describe and summarize a sample of data, we probably start by finding the mean (or average), the median, and the mode of the data. These are central tendency measures and are often our first look at a dataset.

In this tutorial, we'll learn how to