8 Popular Chart Types and When to Use Them

There are dozens of chart types that can be utilised in data visualization, hence why so many of us find it challenging to select the charts that best suits our data or objective.

The struggle to distinguish between various charts and utilise the right choices to quickly display vast amounts of data means that the majority of people guess which is the best option. So, I'm going to show you the most popular chart types and how to distinguish between to ensure you select the appropriate chart type quickly.

Chart Type Differentiation

You can compare each style of chart to its respective usages to distinguish between them and select the best visual. following tips will help you to distinguish between chart types.

TIPS:

• Analysing a Trend
  There are two basic charts that are suitable for you when you require a chart to show the trend of a series of data over a set period: a column chart and a line chart. With different sets of data, the two charts both display a changing trend. Additionally, you can combine them into a single figure known as a Pareto chart, which is better for identifying pertinent trends.
• Recognising Relationships
  Finding the correlations between data points is important because you can identify the relationships between a single data variable and the entire group or other variables, scatter plots, spider charts and bubble charts are the ideal tools for studying relationships.
• Representing Distribution
  The distribution of items across multiple categories is shown in distribution charts. The ideal graphs to use for this kind of data include scatter plots, line graphs and histograms.
• Conducting Comparisons
  The majority of charts are designed with data comparison in mind. Since data usually comes in a large quantities, comparing functions aids in the visualization of large amounts of data. Bar charts, column charts, six sigma, and spider charts can be used to compare various elements when they are divided into two segments, whereas line charts and column charts can be used to compare one fixed item over multiple time periods.
• Reviewing Composition
  The makeup of a problem can be seen using three different sorts of charts. As different slices of a pie can represent different compositions and the entire pie represents the entirety of an item, it is evident that pie charts are made to display compositions. Additionally, different coloured sections can be used to show compositions in area charts and stacked bar charts.

Bar charts, line charts, scatter plots, column charts, pie charts, area charts, radar charts and gauges are often the most common forms of charts.

Here is a quick look at all of these different kinds of charts. The main challenge is deciding which sort of chart is best for your purpose.

In general, you should take into account the total number of variables, data points, and time period of your data while selecting the most appropriate chart type. Every chart type offers unique benefits. For instance, scatter diagrams are useful for expressing relationships between various aspects or topics whereas line types are ideal for displaying trends.

Bar Charts

When you have at least one category or discrete variable, use bar charts to compare categories. Longer bars denote greater values, and each bar represents a summary value for one discrete level. Counts, sums, averages, and standard deviations are a few examples of summary values.

Use a Bar Chart when:

• You have lengthy category labels
• You have a number of categories to compare

Bar Chart tips:

• Order your categories either by value (high to low, low to high) or alphabetically
• Enhance readability by writing your labels horizonatally, not vertically
• Use colour to highlight a significant value or data point, otherwise use one colour (or gradient of one colour)

Column Charts

Histograms are charts that show how your continuous data is distributed. Because they can highlight characteristics about your data that summary statistics cannot, they are ideal for exploratory analysis. For instance, histograms give your data life while the mean and standard deviation can mathematically summarise your data.

Use a Column Chart when:

• You want to show a comparison between subjects or categories
• You want to highlight a particular point in time
• To quickly identify differences in your values

Column Chart tips:

• Order your categories by value
• Keep the visul 2D to improve readability
• Always plot against a zero-value baseline

Line Charts

To show a series of data points connected by lines, use line charts. To highlight changes in a measure on the vertical Y-axis by another variable on the horizontal X-axis, analysts employ line charts. The X-axis frequently, but not always, represents time. Line plots are another name for line charts.

Use a Line Chart when:

• Showing trends in your data over time
• To forecast future potential results
• Comparisons of multiple topics over a certain time period

Line Chart tips:

• Ensure your data is ordered consistently
• Add labels to your lines to make yoru data clear
• Use a solid line over a dotted line
• Use as few lines as possible to enable clarity

Pie Charts

Pie charts can be used to compare category sizes to the full dataset. You need a categorical variable that separates your data into categories in order to make a pie chart. These graphs feature a circle (the pie), with slices signifying different subgroups. Each slice's size reflects how much a fraction of each category makes up overall.

The sizes of the slices in these charts can be determined using proportions or summary statistics. For illustration, you could make a pie chart that displays the percentage of each sort of sales (jeans, t-shirts, accessories, etc.). Or design one that shows total sales broken down into various categories.

Use a Pie Chart when:

• To identify differences in volume
• Compare multiple datapoints
• Showcase part-to-whole comparisons

Pie Chart tips:

• Ensure your pie chart totals 100%
• Utilise colour to indicate an important slice
• Reduce clutter by combining similar slices
• Limit your categories to improve insight

Scatter Plots

To display relationships between two continuous variables, use scatterplots. These graphs provide symbols for the paired variables at the X and Y coordinates of the data points. Other names for scatterplots include scattergrams and scatter charts.

You can tell whether there is a relationship or correlation between two continuous variables by looking at the pattern of dots on a scatterplot. If a relationship is present, the scatterplot shows its direction as well as whether it is straight or curved.

Use a Scatter Plot when:

• You want to show relationships between two variables

Scatter Plot tips:

• Use a baseline of zero for your y-axis to improve readability
• Utilize colour, shapes and sizes to highlight important data points

Radar Chart

Web charts, star charts, and polar charts are other names for spider and radar charts. Utilizing spider and radar charts is preferable to using column ones if you have a vast collection of various data categories. When displaying many data groups using 2D diagrams with at least three variables on axes, the radar chart is helpful.

Use a Radar Chart when:

• You want to compare multivariate measures
• You are comparing two or more subjects or categories

Radar Chart tips:

• Use transparent colours to not obscure other categories
• Design in 2D to improve readability
• Limit the number of data point to around 10 to reduce clutter

Area Chart

An area chart is essentially a line chart with a colour or pattern drawn in the area between the x-axis and the line. It is helpful for illustrating part-to-whole relationships, such as highlighting how each sales representative contributed to annual sales as a whole. You can use it to evaluate data on both general and specific trends.

Use an Area Chart when:

• Indicate an important change over time
• Showcase differences between values

Area Chart tips:

• Limit the number of categories to a max of 4
• Ensure your colours are transparent to prevent masking over other items
• Group similar and smaller categories together to reduce clutter

Gauges

Gauge charts frequently display factors as individual values. These indicators are often coloured red, amber or green to indicate the appropriate message. In particular, gauge charts are perfect for displaying KPIs (Key Performance Indicators). As a result, management or employers typically use them for measuring performance.

Use Gauges when:

• You want to demonstrate KPI's or other important metrics
• Showcasing progress or change in a particular measure
• Comparing key measures or metrics

Gauge tips:

• Utilize colours to reflect positive or negative change/values

I hope you found this article helpful when deciding which chart type to choose and when. If you'd like to improve your data visualizations, visit our site for more!