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  • This is the perfect video, if you would like to avoid creating charts like this one.

  • Or perhaps this one

  • And especially this one

  • Being able to choose the right type of chart for the data you are working with is not an

  • exact science, but I’m sure you will agree something went wrong with these examples.

  • One can’t be certain whether they have been taken from a horror movie or a hippie fest.

  • In 99.9% of cases, we don’t want to show this to our audience.

  • Charts are an opportunity.

  • A storytelling tool.

  • A chance to make a convincing argument through visualizing data.

  • We are not going to convince anybody if we choose a type of chart that is not the right

  • fit for the data.

  • To help you overcome or avoid this issue, in this video well discuss:

  • a) the different types of charts, and b) the type of data they are suitable for

  • Bar charts Probably the most frequently used type of

  • chart is the basic bar chart.

  • As its name suggests it is composed of a series of bars illustrating a variable’s development.

  • Given that bar charts are so common, people are generally familiar with them and can understand

  • them easily.

  • Examples like this one are straightforward to read.

  • However, please be aware that bar charts can be confusing, too.

  • Especially if one uses them to compare several variables.

  • I personally believe that a comparison of more than two variables with a clustered bar

  • chart becomes too cluttered.

  • Here is an example of a clustered bar chart that is not exactly crystal clear:

  • This isn’t a horrible visualization, but it leaves plenty to be desired.

  • First of all, it is difficult to follow the trend of all five variables simultaneously,

  • isn’t it?

  • Moreover, it is hard to gain an idea about the overall state of the Fiction Book Sales

  • market, and how it changed, which was probably what the person who created the chart wanted

  • to show in the first place.

  • When to use bar charts So, bar charts are nice, but limited.

  • We have to consider the type of data we want to visualize and the number of variables that

  • will be added to the chart.

  • Bar charts are great when we want to track the development of one or two variables over

  • time.

  • For example, one of the most frequent applications of bar charts in corporate presentations is

  • to show how a company’s total revenues have developed during a given period.

  • A bar chart can be used to make both a year-on-year comparison, and to provide a monthly breakdown.

  • Moreover, bar charts can be pretty intuitive when we compare the development of two numerical

  • variables over time.

  • Let’s say we would like to compare the revenues of two companies in the timeframe between

  • 2014 and 2018.

  • When to avoid using bar charts Simple bar charts are far from ideal in situations

  • when we have several variables and all of them are part of a whole.

  • Such as the case In the Fiction Book Sales chart we showed you, there were five categories:

  • Young adult; classics; mystery; romance; and Sci-fi.

  • All of which account for all fiction books.

  • Meaning, their sum gives us the total volume of the Fiction book sales market.

  • Do we get any of this information with this bar chart?

  • We don’t.

  • It simply shows us multiple lines and one has to start making calculations on their

  • own to understand how numbers developed over time.

  • And if they have to do that, why bother creating a chart?

  • We are better off showing the data in a table format, right?

  • So, this certainly is one case where we should use a different type of chart.

  • Along the same lines, a simple bar chart isn’t suitable when we have a single period breakdown

  • of a variable.

  • If I want to portray the main business lines that contributed to a company’s revenues

  • in 2018, I wouldn’t use a bar chart.

  • Instead, I’d create a pie chart or one of its variations.

  • Pie charts A pie chart is a circular graph divided into

  • slices.

  • The larger a slice is, the bigger portion of the total quantity it represents.

  • When to use a pie chart So, pie charts are best suited to depict sections

  • of a whole.

  • What does that mean?

  • If a company operates three separate divisions, at year end its top management would be interested

  • in seeing what portion of total revenue each division accounted for.

  • A pie chart is perfect in this case.

  • However, we need to be certain that the sum of the proportions makes 100% of the total.

  • That is, we cannot afford to forget any of the three divisions contributing to total

  • revenue.

  • When to avoid pie charts Obviously, we can’t use a pie chart in situations

  • when we would like to show how a variable (or multiple variables) develops over time.

  • Pie charts are a definite no-go in these cases.

  • Moreover, as mentioned earlier, a pie chart would be misleading if we don’t consider

  • all values.

  • In the context of our example from earlier, we shouldn’t create a pie chart that includes

  • revenue of only two of the firm’s three divisions.

  • Doughnut charts Doughnut charts are basically pie charts with

  • a hole in the middle.

  • (It is as if their heart is missing…)

  • When to use doughnut charts The use cases of pie and doughnut charts are

  • identical.

  • The only important difference is that doughnut charts allow us to indicate the total amount

  • by adding a text box in the middle.

  • If you use a pie chart, you will have to include the total amount elsewhere (like adding it

  • to the title).

  • When to avoid using doughnut charts We already explained when to avoid using pie

  • charts.

  • The same is valid for doughnut charts.

  • One piece of advice when choosing whether to include a pie or a doughnut chart would

  • be to think of your audience.

  • How likely is it they would be interested in seeing the total figure for breakdown you

  • are providing?

  • If the split itself is more important, then go ahead and use a pie chart.

  • If the value of the total is important too, then perhaps a doughnut chart would be preferable.

  • Moreover, some studies have shown that people tend to get a distorted idea when shown pie

  • charts, as larger portions can look even more so because they cover more space.

  • With doughnut charts this isn’t as much of an issue.

  • Line charts A line chart is, as one can easily imagine,

  • a line or multiple lines showing how single, or multiple variables develop over time.

  • It is a great tool because we can easily highlight the magnitude of change of one or more variables

  • over a period.

  • When to use line charts Remember the awkward Fiction book sales chart

  • we saw earlier?

  • Well, a simple line chart would have been way better in that case.

  • A line chart allows us to track the development of several variables at the same time.

  • It is very easy to understand, and the reader doesn’t feel overwhelmed.

  • When to avoid line charts Line charts are not that great in situations

  • when you want to show how the individual parts of a whole change over time.

  • Yes, in theory one could use a stacked line chart (where line values accumulate) or a

  • 100% stacked line chart (where lines accumulate to 100%), but a stacked area chart would look

  • better.

  • Area charts Area charts are very similar to line charts.

  • In fact, at first, I wanted to show them together.

  • However, one major confusion could have arisen.

  • So, please pay attention.

  • The idea of an area chart is based on the line chart.

  • Coloured regions (areas) show us the development of each variable over time.

  • There are three types of area charts: regular area chart, stacked area chart, and 100% stacked

  • area chart.

  • When to use an area chart Whenever we want to show how the parts of

  • a whole change over time, we should consider an area chart.

  • So, for example, if the company has three revenue generating divisions, it is very likely

  • that management would like to see the development of each of these divisions.

  • This is a great way to draw attention to the total value and still emphasize an important

  • trendsay, revenues from one division have been growing rapidly while the other

  • two have kept the same level.

  • A stacked area chart is perfect in this case.

  • However, if we are interested in the portion of revenue generated by each division and

  • not that much of the total amount of revenues, we can simply use a 100% stacked area chart.

  • This will show each division’s percentage contribution over time.

  • When to avoid area charts Obviously, similarly to line charts, area

  • charts are not suitable for representing parts of a whole over a single period.

  • In our example, we can’t use an area chart to show the proportion of revenues each division

  • generated in say, 2018 alone.

  • So that’s a situation where we can’t use an area chart.

  • In general, I would stay away from the classical area chart too.

  • It can be very confusing and even Microsoft themselves recommend avoiding it and to consider

  • using a simple line chart.

  • If we wanted to show the development of revenues generated by each of the firm’s divisions

  • over time with a simple area chart, we would have something looking like this.

  • I know.

  • A nightmare.

  • So, to recap.

  • Line and area charts function in a strange symbiosis between each other:

  • It is recommended to use the line chart, stacked area chart, and 100% stacked area chart;

  • We should avoid using: area chart, stacked line chart, and 100%-line chart

  • Ok, great!

  • We are doing really well.

  • Let’s make a short pause here and in our next video, we will discuss treemap, bridge,

  • scatter, and histogram charts.

  • Make sure you don’t miss it because it is a great one!

This is the perfect video, if you would like to avoid creating charts like this one.

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圖表哪種好在14種圖表中進行選擇 第一部分 (Which is the best chart: Selecting among 14 types of charts Part I)

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    林宜悉 發佈於 2021 年 01 月 14 日
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