• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
Finance Train

Finance Train

High Quality tutorials for finance, risk, data science

  • Home
  • Data Science
  • CFA® Exam
  • PRM Exam
  • Tutorials
  • Careers
  • Products
  • Login

When to Use Bar Chart, Column Chart, and Area Chart

Data Science

This lesson is part 2 of 29 in the course Data Visualization with R

Bar Chart and Column Chart

A Bar Chart or Bar Graph can be only used to compare values. It presents grouped data using rectangular bars whose lengths are proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a Column Chart. Bar charts are usually scaled so that all the data can fit on the chart. Bars on the chart can be arranged in any order. The point values can be compared between themselves (single-series chart) or values inside the category (multi-series chart). In case of several series points are grouped by categories.

While talking about charts, we will generally refer to different axis as dimensions and measures.

The same chart can be presented as a column chart as shown below:

Area Chart

An area chart or area graph is used to display quantitative data in a graphical manner. Common uses are the comparison of two or more quantities. They can be used to represent cumulated totals using numbers or percentages over time. Use the area chart to show trends over time among related attributes. When multiple attributes are included, the first attribute is plotted as a line with color fill followed by the second attribute, and so on. Technically this chart type is based on Line Chart and represents filled area between zeroline and the line that connects data points. The same as for Line Chart, timeline scale is the most common case for the X-axis of the Area Chart, but sometimes ordinal scale can be also used.

The following area chart shows venture capital investment by stage.

100% Stack Area Chart

100 Percent Stacked Area Charts display the data that can be put in a table on a worksheet (the items should have two coordinates or parameters). A stacked chart means that all values of one category form a whole; when we’ve got a 100% stacked chart, it means that this chart displays the comparison of the percentage value each part of the category brings to the category. Real values are not displayed, chart shows only the percentage.

This 100% stacked area chart shows the venture capital investment by stage.

Previous Lesson

‹ Overview of Data Visualization

Next Lesson

What is Line Chart and When to Use It ›

Join Our Facebook Group - Finance, Risk and Data Science

Posts You May Like

How to Improve your Financial Health

CFA® Exam Overview and Guidelines (Updated for 2021)

Changing Themes (Look and Feel) in ggplot2 in R

Coordinates in ggplot2 in R

Facets for ggplot2 Charts in R (Faceting Layer)

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Primary Sidebar

In this Course

  • Overview of Data Visualization
  • When to Use Bar Chart, Column Chart, and Area Chart
  • What is Line Chart and When to Use It
  • What are Pie Chart and Donut Chart and When to Use Them
  • How to Read Scatter Chart and Bubble Chart
  • What is a Box Plot and How to Read It
  • Understanding Japanese Candlestick Charts and OHLC Charts
  • Understanding Treemap, Heatmap and Other Map Charts
  • Visualization in Data Science
  • Graphic Systems in R
  • Accessing Built-in Datasets in R
  • How to Create a Scatter Plot in R
  • Create a Scatter Plot in R with Multiple Groups
  • Creating a Bar Chart in R
  • Creating a Line Chart in R
  • Plotting Multiple Datasets on One Chart in R
  • Adding Details and Features to R Plots
  • Introduction to ggplot2
  • Grammar of Graphics in ggplot
  • Data Import and Basic Manipulation in R – German Credit Dataset
  • Create ggplot Graph with German Credit Data in R
  • Splitting Plots with Facets in ggplots
  • ggplot2 – Chart Aesthetics and Position Adjustments in R
  • Creating a Line Chart in ggplot 2 in R
  • Add a Statistical Layer on Line Chart in ggplot2
  • stat_summary for Statistical Summary in ggplot2 R
  • Facets for ggplot2 Charts in R (Faceting Layer)
  • Coordinates in ggplot2 in R
  • Changing Themes (Look and Feel) in ggplot2 in R

Latest Tutorials

    • Data Visualization with R
    • Derivatives with R
    • Machine Learning in Finance Using Python
    • Credit Risk Modelling in R
    • Quantitative Trading Strategies in R
    • Financial Time Series Analysis in R
    • VaR Mapping
    • Option Valuation
    • Financial Reporting Standards
    • Fraud
Facebook Group

Membership

Unlock full access to Finance Train and see the entire library of member-only content and resources.

Subscribe

Footer

Recent Posts

  • How to Improve your Financial Health
  • CFA® Exam Overview and Guidelines (Updated for 2021)
  • Changing Themes (Look and Feel) in ggplot2 in R
  • Coordinates in ggplot2 in R
  • Facets for ggplot2 Charts in R (Faceting Layer)

Products

  • Level I Authority for CFA® Exam
  • CFA Level I Practice Questions
  • CFA Level I Mock Exam
  • Level II Question Bank for CFA® Exam
  • PRM Exam 1 Practice Question Bank
  • All Products

Quick Links

  • Privacy Policy
  • Contact Us

CFA Institute does not endorse, promote or warrant the accuracy or quality of Finance Train. CFA® and Chartered Financial Analyst® are registered trademarks owned by CFA Institute.

Copyright © 2021 Finance Train. All rights reserved.

  • About Us
  • Privacy Policy
  • Contact Us