tb8_Digging Deeper_Clustering_Standard Distributions_Forecasting_tableau + python_Season_Trends

本文介绍了Tableau如何通过内置的统计模型和分析功能增强数据可视化,包括趋势分析、聚类、分布和预测。通过案例展示了如何利用线性、指数等趋势模型以及自定义时间范围来揭示数据的季节性和周期性。同时,讨论了如何使用R和Python平台进行更高级的统计分析,并利用TabPy进行集成。

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     The rapid visual analysis that is possible using Tableau is incredibly useful for answering numerous questions and making key decisions. But it only barely scratches[ˈskrætʃɪz]擦,刮,搔 the surface of the possible analysis. For example, a simple scatterplot can reveal outliers, but often, you want to understand the distribution or identify clusters of similar observations. A simple time series helps you to see the rise and fall of a measure over time, but many times, you want to see the trend or make predictions of future values.

     Tableau enables you to quickly enhance your data visualizations with statistical analysis. Built-in features such as trend models, clustering, distributions, and forecasting allow you to quickly add value to your visu

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