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  1. Use line charts to display a series of data points that are connected by lines. Analysts use line charts to emphasize changes in a metric on the vertical Y-axis by another variable on the horizontal X-axis.

    • Contour Plots

      Use contour plots to display the relationship between two...

  2. 29 gru 2021 · In data mining, the graph is used to find subgraph patterns for discrimination, classification, clustering of data, etc. The graph is used in network analysis. By linking the various nodes, graphs form network-like communications, web and computer networks, social networks, etc.

  3. 17 gru 2021 · Above is an example with the age variable, which is by default split by the target variable diameter narrowing in Orange. The visualization shows two box plots, one for each target value (patients with and without diameter narrowing). The yellow vertical line shows the median value for each box.

  4. 19 wrz 2023 · Our curated collection of line chart examples takes you on a journey that turns complexity into clarity, one line at a time. It doesn’t matter if you’re a data visualization novice or a seasoned analyst, our examples serve as a rich repository of inspiration and practical application.

  5. 22 sty 2018 · There are a ton of amazing examples—too many to call out individually. Speaking of which... There's been a friendly debate at my house regarding this challenge. Rewind to last night, and I'm scrolling through the finally-completed draft post of all the entries to show my husband, saying, "how cool is this?!?"

  6. Once we represent data as a graph using the NetworkX library in Python, a few short lines of code can be illuminating. We can visualize our dataset, measure and compare node characteristics, and cluster nodes sensibly via community detection algorithms.

  7. Example. Line Plot is a standard visualization widget, which displays data profiles, normally of ordered numerical data. In this simple example, we will display the iris data in a line plot, grouped by the iris attribute. The plot shows how petal length nicely separates between class values.

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