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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.
A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a column chart. A bar graph shows comparisons among discrete categories.
Here, with the <timeline>...</timeline>, the a vertical bars is formatted by the command "TimeAxis=orientation:vertical" (before specifying the data for the bars). The width of bars is set by "PlotData=width:20". The color of any bar can be set by appending the keyword "color:" (such as "color:lightgrey") at the end of each bar's numeric data.
Matplotlib can create plots in a variety of output formats, such as PNG and SVG. Matplotlib mainly does 2-D plots (such as line, contour, bar, scatter, etc.), but 3-D functionality is also available in some releases. Here is a simple line plot in pylab (output image is shown on the right): A simple SVG line plot in Matplotlib.
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 ...
reveal the data at several levels of detail, from a broad overview to the fine structure. serve a reasonably clear purpose: description, exploration, tabulation, or decoration. be closely integrated with the statistical and verbal descriptions of a data set. Graphics reveal data.
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]
A bar chart may be used to show the comparison across the salespersons. [52] Part-to-whole: Categorical subdivisions are measured as a ratio to the whole (i.e., a percentage out of 100%). A pie chart or bar chart can show the comparison of ratios, such as the market share represented by competitors in a market. [53]