tableau 数据可视化工具

Posted 2021-04-02 LearningYard新学苑

tableau

数据可视化工具（三）

教程（三）.mp3 From LearningYard新学苑 00:00 06:51

优点

数据可视化：Tableau是一种数据可视化工具，提供复杂的计算，数据混合和仪表板，用于创建漂亮的数据可视化。

快速创建交互式可视化：用户可以使用Tableau的拖放功能创建非常交互式的可视化。

实施舒适：Tableau中提供了许多类型的可视化选项，可增强用户体验。与Python相比，Tableau非常容易学习。对编码不了解的用户也可以快速学习Tableau。

Tableau可以处理大量数据：Tableau可以轻松处理数百万行数据。大量数据可以创建不同类型的可视化，而不会影响仪表板的性能。除此之外，Tableau中还有一个选项，用户可以“实时”连接不同的数据源，如SQL等。

在Tableau中使用其他脚本语言：为了避免性能问题并在Tableau中执行复杂的表计算，用户可以包含Python或R。使用Python脚本，用户可以通过使用包执行数据清理任务来删除软件的负载。但是，Python不是Tableau接受的本机脚本语言。因此，您可以导入一些包或视觉效果。

移动支持和响应式仪表板：Tableau仪表板具有出色的报告功能，它专门为移动设备或笔记本电脑等设备自定义仪表板。Tableau会自动了解用户正在查看报告的设备，并进行调整以确保将准确的报告传送到正确的设备。

 Data visualization: Tableau is a data visualization tool that provides complex calculations, data blending and dashboards for creating beautiful data visualizations. Quickly create interactive visualizations: Users can use Tableau's drag-and-drop function to create very interactive visualizations. Implementation comfort: Many types of visualization options are provided in Tableau to enhance the user experience. Compared with Python, Tableau is very easy to learn. Users who do not know coding can also learn Tableau quickly. Tableau can handle large amounts of data: Tableau can easily handle millions of rows of data. Large amounts of data can create different types of visualizations without affecting the performance of the dashboard. In addition, there is an option in Tableau where users can connect to different data sources, such as SQL, in "real time". Use other scripting languages in Tableau: To avoid performance issues and perform complex table calculations in Tableau, users can include Python or R. Using Python scripts, users can remove the software load by using packages to perform data cleaning tasks. However, Python is not a native scripting language accepted by Tableau. Therefore, you can import some packages or visual effects. Mobile Support and Responsive Dashboard: Tableau Dashboard has excellent reporting capabilities, it is specifically customized for mobile devices or laptops and other devices. Tableau will automatically understand the device the user is viewing the report and make adjustments to ensure that the accurate report is delivered to the correct device.

（来源：Google翻译）

  缺点

报告计划：Tableau不提供报告的自动计划。当用户需要更新后端数据时总是需要一些手动操作。

无自定义视觉导入：其他工具(如Power BI)，开发人员可以创建可在Tableau中轻松导入的自定义视觉，因此任何新的视觉效果都可以在导入之前重新创建，但Tableau不是一个完整的开放工具。

自定义格式：Tableau的条件格式，以及对用户非常不方便的有限16列表。此外，要在多个字段中实现相同的格式，用户无法直接对所有字段执行此操作。用户必须为每个人手动执行此操作，因此非常耗时。

静态和单值参数：Tableau参数是静态的，它始终选择单个值作为参数。每当数据发生变化时，每次都必须手动更新这些参数。对于可以自动更新参数的用户，没有其他选项。

仪表板上的屏幕分辨率：如果Tableau开发人员屏幕分辨率与用户屏幕分辨率不同，则会分发仪表板的布局。示例：如果仪表板是在1920 X 1080的屏幕分辨率上创建的，并且在2560 X 1440上查看，那么仪表板的布局将被破坏一点，它们的仪表板没有响应。因此，需要以不同方式为桌面和移动设备创建仪表板。

After connecting to the data source, Tableau will capture the metadata details of the source, such as the columns and their data types. This is used to create the dimensions, measures and calculation fields used by the view. We can browse the metadata and change certain properties of some specific requirements.

Check metadata: After connecting to the data source, Tableau will display all possible tables and columns that exist in the source, let's consider the source example coffee shop to check metadata. Click the Data menu and select Connect to data source. Browse the MS access file named Sample-Coffee Shop. Drag the table named Product to the data canvas. When selecting a file, we get the following screen showing the column names and their data types. The string data type is displayed as Abc, and the numeric data type is displayed as #.

Change the data type: If necessary, we can change the data type of some fields. Depending on the nature of the source data, sometimes Tableau may not be able to recognize the type of data in the source. In this case, we can manually edit the data type. The screen below shows the options.

Rename and hide: You can use the rename option to change the column name. In addition, we can hide a column so that it will not appear in the data view we created. These options are available by clicking the data type icon in the metadata grid, as shown below.

Column alias: You can assign an alias to each column of the data source to help better understand the nature of the column. We can select the alias option from the steps above, and then the following screen for creating or editing an alias appear.（来源：Google翻译）

参考资料：百度、易百教程

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