數(shù)據(jù)可視化的10個(gè)關(guān)鍵術(shù)語_數(shù)據(jù)分析師

Format 交互方式

Interactive visualisations allow you to modify, manipulate and explore a computer-based display of data. The vast majority of interactive visualisations are found on websites but increasingly might also exist within apps on tablets and smartphones. By contrast, a static visualisation displays a single, non-interactive display of data, often with the aim for it to be viewed in print as well as on a screen.

交互式可視化允許您修改，操作和探索計(jì)算機(jī)顯示的數(shù)據(jù)。絕大多數(shù)交互式可視化系統(tǒng)在計(jì)算機(jī)網(wǎng)絡(luò)上，但越來越多出現(xiàn)在平板電腦和智能手機(jī)上。相比之下，靜態(tài)可視化只顯示單一的、非交互數(shù)據(jù)，它通常是為了打印和在屏幕上顯示。

Chart type 圖表類型

Charts are individual visual representations of data. There are many ways of representing your data, using different marks, shapes and layouts: these are all called types of charts. Some chart types you might be familiar with, such as the bar chart, pie chart or line chart, whilst others may be new to you, like the sankey diagram, tree map, choropleth map. See the section called ‘Taking time with visualisation’ for more on chart types.

圖表是數(shù)據(jù)視覺化表示的特殊方式。表示數(shù)據(jù)的方法有很多，如使用不同的符號、形狀和排列，我們把這些稱之為圖表的類型。一些圖表類型你比較熟悉，如條形圖、餅圖、折線圖，但其他類型你可能就很少見了，如?；鶊D、樹圖、等值線圖的地圖。

Dataset 數(shù)據(jù)集合

A dataset is a collection of data upon which a visualisation is based. It is useful to think of a dataset as taking the form of a table with rows and columns, usually existing in a spreadsheet or database. The rows are the records – instances of things – and the columns are the variables – details about the things. Datasets are visualised in order to ‘see’ the size, patterns and relationships that are otherwise hard to observe.

數(shù)據(jù)集合是需要可視化處理的數(shù)據(jù)集合。你可以簡單認(rèn)為數(shù)據(jù)集合就是很多行和列的數(shù)據(jù)，這些數(shù)據(jù)通常在電子表格或數(shù)據(jù)庫中。行代表一個(gè)記錄，也就是一個(gè)事務(wù)的實(shí)例；列是變量，代表事務(wù)的具體信息。數(shù)據(jù)集合的大小、形式和關(guān)系是可以看到的，否則我們就很難觀察。

Data source 數(shù)據(jù)源

When visualisers want to show you where the data or information comes from, they will include it in the visualisation. Sometimes it appears near the title or the bottom of the page. Other times, if the visualisation comes with an article, you can find it in the accompanying text.

當(dāng)數(shù)據(jù)可視圖的作者想告訴你展示的數(shù)據(jù)或信息的來源時(shí)，這些來源信息也會顯示出來。通常會顯示在標(biāo)題附近或頁面的底部。如果數(shù)據(jù)可視圖有文章資料，你可以在文章中找到來源信息。

Axis 軸

Many types of chart have axes. These are the lines that go up and down (the vertical Y axis), or left and right (the horizontal X axis), providing a reference for reading the height or position of data values. Axes are the place where you will usually see the scale (see below) providing a stable reference point against which you form your reading of the chart.

許多類型的圖表有軸。軸分為垂直的Y軸(向上或向下）和水平X軸(向左或向右)，目的是為閱讀數(shù)值的高度或位置提供一個(gè)參考。軸的位置通常會有刻度(見下文)，刻度為閱讀圖標(biāo)提供一個(gè)固定的參考點(diǎn)。

Scale 度量

Scales are marks on a visualisation that tell you the range of values of data that is presented. Scales are often presented as intervals (10, 20, 30 etc.) and will represent units of measurement, such as prices, distances, years, or percentages.

度量表示數(shù)值的規(guī)模和范圍。度量通常以間隔表示(10、20、30等等)，代表度數(shù)字的單位，如價(jià)格、距離、年，或百分比。

Legend 圖例

Many charts will use different visual properties such as colours, shapes or sizes to represent different values of data. A legend or key tells you what these associations mean and therefore helps you to read the meaning from the chart.

許多圖表使用不同的視覺樣式來表示不同的數(shù)據(jù)，如顏色、形狀或大小。一個(gè)圖例或樣例告訴你這些樣式是什么意思，從而幫助你閱讀圖表。

Variables 變量

Variables are the different items of data held about a ‘thing’, for example it might be the name, date of birth, gender and salary of an employee. There are different types of variables, including quantitative (e.g. salary), categorical (e.g. gender), others are qualitative or text-based (e.g. name). A chart plots the relationship between different variables. For example, the bar chart to the right might show the number of staff (height of bar), by department (different clusters) broken down by gender (different colours).

我們可以用變量描述不同的人或事，例如，它可能是名字,出生日期,性別和工資。變量有不同類型,包括數(shù)量(如工資)、類別(如性別)，還包括屬性或文本信息(如名字)。圖表可以表示不同變量之間的關(guān)系。例如，右邊的條形圖可以顯示不同部門(不同的組)的員工的數(shù)量(柱的高度)和性別組成(不同的顏色)。

Outliers 離群值

Outliers are those points of data that are outside the normal range of data in some way. Visualisations can often help to identify patterns in the data – in the example on the right, the higher the number on the x axis, the greater the number on the y axis. Sometimes individual bits of data don’t fit in to the pattern, like the orange dot here; those are the outliers.

離群值是那些數(shù)值超出了正常數(shù)值范圍的數(shù)據(jù)。我們知道圖表常?？梢詭椭R別數(shù)據(jù)模式，在右邊的例子中,x軸上的數(shù)量越大，在y軸上數(shù)量就越大，這就是一種數(shù)據(jù)模式。有時(shí)候有些特殊的數(shù)據(jù)不符合圖表中數(shù)據(jù)模式，如圖中橙色點(diǎn)，它們就是離群值。

Input area 輸入?yún)^(qū)

Input areas allow you to enter information into a visualisation, maybe to search for certain names or places, or to input information about yourself that will be used in the visualisation.

輸入?yún)^(qū)允許你在圖表中輸入信息，或是尋找特定名字或位置，或?yàn)榱溯斎肽阕约旱男畔ⅰ?/span>