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Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...
1. Choose a Time Frame. Google Finance / Google Finance. In the first example, you’ll see five years’ worth of Amazon stock history starting in 2016 through early 2021. The timeline progresses ...
The Google Chart API allows a variety of graphs to be created. Livegap Charts creates line, bar, spider, polar-area and pie charts, and can export them as images without needing to download any tools. Veusz is a free scientific graphing tool that can produce 2D and 3D plots. Users can use it as a module in Python.
linewidth: line width for line charts or distance between the pie segments for pie charts. Setting to 0 with type=line creates a scatter plot. linewidths: different line widths may be defined for each series of data with csv, if set to 0 with "showSymbols" results with points graph, eg.: linewidths=1, 0, 5, 0.2.
Market profile. A Market Profile is an intra-day charting technique (price vertical, time/activity horizontal) devised by J. Peter Steidlmayer, a trader at the Chicago Board of Trade (CBOT), ca 1959-1985. Steidlmayer was seeking a way to determine and to evaluate market value as it developed in the day time frame.
Statistical graphics have been central to the development of science and date to the earliest attempts to analyse data. Many familiar forms, including bivariate plots, statistical maps, bar charts, and coordinate paper were used in the 18th century. Statistical graphics developed through attention to four problems: [3]
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