In this section, we will walk through the different charts and their respective uses in the corporate world.
But before we do that, let me give you the best practices that I've learned over the years. As the main point of creating data visualizations for your audience is for them to understand the information, you want to make a basic chart instead of impressing them with complicated ones. As a general rule, SIMPLE IS ALWAYS BETTER.
Do not force your data all in one chart. Have multiple small charts in a deck, rather than one big chart with different data inside.
Keep your colors consistent. This isn't a rainbow-making contest. Use one color for similar data.
Use colors for emphasis. Choose muted colors for the default data, and select a fabulous color for the data point you wish to emphasize.
Label your text, legends, axes, and charts properly and neatly. Don't let them overlap.
It's a type of chart where your data is published as rectangles and goes from left to right.
Column charts are primarily used for categorical or chronological/time-series data.
Column chart is used when comparing different categories, such as comparing sales between different brands. They may also be used to present changes in data over time, such as showing increasing or decreasing trends in volume of transactions.
Area chart and bar chart are common alternatives to column chat. Area chart showcases a more dramatic effect for volume-based data. Bar chart is used when the axis label is too long on a horizontal axis (so you basically flip the chart from left-to-right to top-to-bottom for easier readability).
It's a type of chart where your data is published as a line with or without markers for each data point and goes from left to right.
Line charts use chronological or time-series data - and IMHO nothing else.
Line charts are usually used for trend analysis - that is, showing changes over time. It is important that the sequenced information is related to - not independent of - each other.
An alternative to the line chart is the area chart, which provides more visual effect on the trends of volume. Again, there is emphasis on the need for sequential information for the contiguous design of the chart to make sense.
The most controversial chart in the data analytics world. This chart shows the relative percentage of a parcel of data against its totality.
Pie charts are exclusively used for numerical data that totals exactly 100%.
Pie chart is commonly used when emphasizing the size of a certain data's contribution to the whole population. Unlike data presented in column or bar charts, the slices of data represented in pie charts should always add up to 100%.
Donut chart is an alternative to a pie chart - with really no difference apart from the space in the middle.
A combo chart is a type of chart that combines two different chart types—typically a column chart and a line chart—on the same axes. This allows you to compare different but related data series with different measurement units or scales in a single view.
Combo charts are useful when you need to compare two related but distinct types of data within the same time scale.
Combo charts are used when you want to highlight the relationship of two sets of distinct data. This is also used to show trends especially if you want to manipulate the line or data points on a trendline (instead of using the automated trendline).
A common variation is using a dual-axis combo chart, where each data series has its own vertical axis to accommodate different scales. This is useful when one metric (e.g., revenue in dollars) is much larger than another (e.g., profit margin in percentage).
A scatterplot is a type of chart where individual data points are plotted as dots on a two-dimensional plane, showing the relationship between two variables. Unlike line charts, scatterplots do not connect points with lines.
Scatterplots are used for comparing two numerical variables to identify patterns, correlations, or clusters. Each point represents a single observation with values for both variables.
Scatterplots are used when you want to explore relationships between two continuous variables, such as identifying correlations, spotting trends, detecting outliers, or understanding distributions.
A variation of the scatterplot is the bubble chart, which adds a third variable by representing it through the size of the dots.
There are many other (sometimes fancier) charts that are available in tools such as Excel or Sheets, but the 5 above the most commonly used in the corporate setting. It is important to know your audience to know how complex your chart can get without losing them in the discussion.
Check out the Types of Presentations to know more.
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