From the course: Introduction to Data Science
Join today to access over 24,900 courses taught by industry experts.
Visualizing your quantitative data
From the course: Introduction to Data Science
Visualizing your quantitative data
Two types of charts that are commonly used to visualize quantitative data are histograms and scatter plots. Note that quantitative data is another term for numerical data, which means data that consists of amounts or quantities. In this lesson, I'll show you how to create these charts in Python. For example, say that you have a data set on Airbnb listings in New York City for 2019, last updated on August 12th of that year. First, I'll import the Python libraries that I'll need, so I'll start with import pandas as pd, import matplotlib.pyplot as plt, import numpy as np and I'll run the cell. Note that going forward, when I code in this notebook, I need to use pd to refer to pandas, plt to refer to matplotlib.pyplot and np to refer to Numpy. Now, Matplotlib.pyplot is a collection of functions that allow you to create figures and plots and make changes to them in Python. Numpy is a useful library for scientific computing in Python and contains functions that allow you to create data…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.