視覺工程師面試指南

When it comes to effective data visualization, the very first and also the most critical step is to select the right graph/visual for the data that you want to present. With a wide range of visualization software that is available offering a large number of chart varieties, it’s often a challenging task to pick the right one, which explains the data and insights in the simplest possible manner. I recently read a very famous book on data visualization — “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic. This book is the best resource that I’ve seen till date on data visualization, and in this article, I’ll explain a topic from the book — Choosing an Effective Visual.

當(dāng)涉及有效的數(shù)據(jù)可視化時(shí)，最重要也是最關(guān)鍵的一步是為要呈現(xiàn)的數(shù)據(jù)選擇正確的圖形/視覺。 借助提供大量圖表品種的廣泛可視化軟件，選擇合適的可視化軟件通常是一項(xiàng)艱巨的任務(wù)，它以最簡(jiǎn)單的方式解釋數(shù)據(jù)和見解。 我最近讀了一本關(guān)于數(shù)據(jù)可視化的非常著名的書— Cole Nussbaumer Knaflic撰寫的“用數(shù)據(jù)講故事：業(yè)務(wù)專業(yè)人員的數(shù)據(jù)可視化指南”。 本書是迄今為止我所見過的有關(guān)數(shù)據(jù)可視化的最佳資源，在本文中，我將解釋本書中的一個(gè)主題-選擇有效的視覺。

Most of the data can be visualized using any one of the 12 kinds of visuals that I’ll be discussing in this article. The visuals can be classified into:

我將在本文中討論的12種視覺方式中的任何一種都可以可視化大多數(shù)數(shù)據(jù)。 視覺效果可分為：

Simple Text

簡(jiǎn)單文字

Table (table, heatmap)

表格(表格，熱圖)

Points (scatterplot)

點(diǎn)(散點(diǎn)圖)

Line (line graph, slope graph)

線(線圖，斜率圖)

Bar (horizontal, vertical, stacked, waterfall)

酒吧(水平，垂直，堆疊，瀑布式)

Area

區(qū)

Note:

注意：

All the graphs shown are made using Google Sheets. Link to the document.

顯示的所有圖形都是使用Google表格制作的。 鏈接到文檔 。

Data used for generating graphs are entirely imaginary and not taken from any source.

用于生成圖形的數(shù)據(jù)完全是虛構(gòu)的，不能從任何來源獲取 。

So let’s start exploring each one on the list.

因此，讓我們開始探索列表中的每一個(gè)。

Simple Text

簡(jiǎn)單文字

You don’t have to always use a graph for showing numbers. If there are just a few numbers with some supporting text, directly showing the numbers might be the best way out. Let’s look at an example to understand better.

您不必總是使用圖形來顯示數(shù)字。 如果只有幾個(gè)數(shù)字帶有一些支持文字，則直接顯示數(shù)字可能是最好的選擇。 讓我們看一個(gè)例子以更好地理解。

Image by Author圖片作者

In the above case, the graph doesn’t provide much aid in interpretation and only ends up occupying a lot of space. So, when you only have a few numbers, show them directly.

在上述情況下，圖形在解釋方面并沒有提供太多幫助，最終僅占用了大量空間。 因此，當(dāng)您只有幾個(gè)數(shù)字時(shí)，請(qǐng)直接顯示它們。

Table

表

If you’re looking to communicate multiple units of measure, a table might be the right visual to use. Creating a table is pretty easy, but always make sure that the design fades into the background and data is the main focus. Here’s an example of fading the design to the background and focusing on the data:

如果您要傳達(dá)多個(gè)度量單位，則表可能是使用的正確視覺效果。 創(chuàng)建表格非常容易，但是始終要確保設(shè)計(jì)淡入背景并且數(shù)據(jù)是主要重點(diǎn)。 這是一個(gè)將設(shè)計(jì)淡化為背景并著重于數(shù)據(jù)的示例：

Image by Author圖片作者

Can you observe the improvement after every iteration? This is why it’s so important.

每次迭代后您都能觀察到改進(jìn)嗎？ 這就是為什么它如此重要的原因。

Heatmap

熱圖

Heatmap is simply an upgraded version of a table where we add colors to interpret the data or numbers better. In a plain table, the reader has to scan every element to get a sense of what’s there. By adding colors, we are making the reader to directly focus on the area of interest, which results in a better understanding of data.

Heatmap只是表格的升級(jí)版本，我們?cè)诒砀裰刑砑恿祟伾愿玫亟忉寯?shù)據(jù)或數(shù)字。 在普通表中，讀者必須掃描每個(gè)元素以了解其中的內(nèi)容。 通過添加顏色，我們使讀者可以直接關(guān)注感興趣的區(qū)域，從而可以更好地理解數(shù)據(jù)。

Image by Author圖片作者

Graphing applications like Excel have conditional formatting options to create heatmaps. And it’s also a good practice to include a legend for better understanding.

諸如Excel之類的制圖應(yīng)用程序具有條件格式選項(xiàng)來創(chuàng)建熱圖。 包括圖例以更好地理解也是一種很好的做法。

Scatterplot

散點(diǎn)圖

Scatterplots are useful for showing relationships between 2 variables where each variable is encoded in X-axis and Y-axis, respectively. It’s especially useful while explaining correlations.

散點(diǎn)圖可用于顯示兩個(gè)變量之間的關(guān)系，其中每個(gè)變量分別在X軸和Y軸上編碼。 在解釋相關(guān)性時(shí)特別有用。

Image by Author圖片作者

Line Graph

線形圖

Line graphs are best when it comes to plotting continuous data like date and time. Since all the points are connected using a line, it’s easy to interpret continuous data, but at the same time, it doesn’t make sense for plotting categorical variables. Line graphs can be used to show a single series or multiple series of data, as shown in the figure.

折線圖最好用于繪制連續(xù)數(shù)據(jù)，例如日期和時(shí)間。 由于所有的點(diǎn)都用一條線連接，因此很容易解釋連續(xù)的數(shù)據(jù)，但是同時(shí)繪制分類變量也沒有意義。 折線圖可用于顯示一個(gè)或多個(gè)數(shù)據(jù)系列，如圖所示。

Image by Author圖片作者

Slope Graph

斜率圖

Slope graph is simply a special case of line graph which is ideal for comparing change in metrics over two different points or time periods. This is really good to intuitively show the rate of change (increase or decrease rate is indicated by the slope of lines) along with the absolute values.

斜率圖只是線圖的一種特殊情況，非常適合比較兩個(gè)不同點(diǎn)或時(shí)間段上度量的變化。 這對(duì)于直觀地顯示變化率(直線的斜率表示上升或下降的速度)以及絕對(duì)值非常好。

Image by Author圖片作者

Next, we’ll look at a few variations of the bar chart, which is ideal for categorical variables. Bar charts tend to be avoided because they are common, but since they are common, it’s very easy for the readers to understand bar charts compared to other types of visuals. This makes bar charts one of the most important forms of visuals.

接下來，我們將看一下條形圖的一些變體，它是分類變量的理想選擇。 由于條形圖很常見，因此傾向于避免使用條形圖，但是由于它們很常見，因此與其他類型的視覺效果相比，讀者很容易理解條形圖。 這使條形圖成為最重要的視覺形式之一。

Vertical Bar

豎條

This is the plain bar chart where each column represents a category. Similar to line graphs, bar charts can also hold multiple series.

這是簡(jiǎn)單的條形圖，其中每列代表一個(gè)類別。 與折線圖相似，條形圖也可以容納多個(gè)系列。

Image by Author圖片作者

Stacked Vertical Bar

堆疊豎條

Stacked bar charts can be used to compare subcomponent pieces across different categories. It can hold either actual numbers or percentages using a 100% stacked chart.

堆疊的條形圖可用于比較不同類別的子組件。 它可以使用100％堆積圖來保存實(shí)際數(shù)字或百分比。

Image by Author圖片作者

Again you mustn’t stuff the categories with too many subcomponents as it becomes difficult to understand and compare.

同樣，您也不能用太多子組件來填充類別，因?yàn)檫@將變得難以理解和比較。

Waterfall

瀑布

A waterfall chart is another special case of a vertical bar that can be used to either pull subcomponents of a stacked bar to focus one at a time, or to show a starting point, increases and decreases, and the resulting ending point.

瀑布圖是垂直條的另一種特殊情況，可用于拉動(dòng)堆疊條的子組件一次集中焦點(diǎn)，或顯示起點(diǎn)，增加和減少以及最終的終點(diǎn)。

Image by Author圖片作者

Horizontal bar

單杠

A horizontal bar is often the go-to option for categorical data because it’s easy to read than the vertical bar and can also accommodate large category names. Similar to vertical bars, it can also have single or multiple series of data.

水平條通常是分類數(shù)據(jù)的首選選項(xiàng)，因?yàn)樗却怪睏l更易于閱讀，并且還可以容納較大的類別名稱。 類似于豎線，它也可以具有單個(gè)或多個(gè)系列的數(shù)據(jù)。

Image by Author圖片作者

Stacked Horizontal Bar

堆積單杠

This is similar to the stacked vertical bar chart but comparatively better because of the reasons discussed for the horizontal bar.

這類似于堆疊的垂直條形圖，但是相對(duì)更好，因?yàn)橛懻摿怂綏l形圖的原因。

Area Graph

面積圖

Area graphs should be avoided whenever possible because human eyes are not so good at comparing values in two-dimensional space. But if you badly want to include multiple metrics, then the area graph might work out.

應(yīng)盡可能避免使用面積圖，因?yàn)槿搜鄄惶瞄L(zhǎng)在二維空間中比較值。 但是，如果您非常想包含多個(gè)指標(biāo)，則面積圖可能會(huì)適用。

With this, I’ve covered graphs that can be used to visualize a majority of data available out there. So choose a graph that can clearly explain the message that you’re trying to convey.

到此為止，我已經(jīng)介紹了可用于可視化大部分可用數(shù)據(jù)的圖表。 因此，選擇一個(gè)可以清楚地解釋您要傳達(dá)的信息的圖表。

As we’ve gone through the best practices, now it’s time to look at some of the practices to be avoided.

當(dāng)我們經(jīng)歷了最佳實(shí)踐時(shí)，現(xiàn)在該考慮一些應(yīng)避免的實(shí)踐了。

Visual Practices to be Avoided

避免視覺行為

Avoid using pie charts because the readers have to compare areas of the arc, which becomes very difficult and is not intuitive. Using a standard bar chart makes it much easier to interpret. Look at the example below to understand better.

避免使用餅圖，因?yàn)樽x者必須比較弧的區(qū)域，這變得非常困難且不直觀。 使用標(biāo)準(zhǔn)條形圖使解釋變得更加容易。 查看下面的示例以更好地理解。

Image by Author圖片作者

Never use 3D charts. 3D charts create unnecessary distractions and make it difficult to interpret. So never use 3D.

切勿使用3D圖表。 3D圖表會(huì)造成不必要的干擾，并使其難以解釋。 因此，切勿使用3D 。

Conclusion

結(jié)論

I hope this article would have given you a good understanding of different visuals and the right place to use each visual. So always choose a visual that adequately conveys the information you are looking to present. And, coming to the application/software that you can use, it’s entirely up to you. Excel, Tableau, Power BI, Google Sheets are some available applications, and you can use anything that you are comfortable with. Remember that the graphing application does not know the actual purpose of the visual, and it’s on you to customize it according to the need. I hope it helped.

我希望本文能使您對(duì)不同的視覺效果有很好的理解，并能正確使用每種視覺效果。 因此，請(qǐng)始終選擇能夠充分傳達(dá)您要呈現(xiàn)的信息的視覺效果。 而且，使用您可以使用的應(yīng)用程序/軟件，完全取決于您。 Excel，Tableau，Power BI，Google表格是一些可用的應(yīng)用程序，您可以使用任何您喜歡的東西。 請(qǐng)記住，制圖應(yīng)用程序不知道視覺效果的實(shí)際用途，您可以根據(jù)需要自定義視覺效果。 希望對(duì)您有所幫助。

翻譯自: https://towardsdatascience.com/ultimate-guide-to-choosing-the-right-visual-2a77aa8eec08

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