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  • Book Overview & Buying KNIME Essentials
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KNIME Essentials

KNIME Essentials

By : Gábor Bakos
3.1 (10)
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KNIME Essentials

KNIME Essentials

3.1 (10)
By: Gábor Bakos

Overview of this book

KNIME is an open source data analytics, reporting, and integration platform, which allows you to analyze a small or large amount of data without having to reach out to programming languages like R. "KNIME Essentials" teaches you all you need to know to start processing your first data sets using KNIME. It covers topics like installation, data processing, and data visualization including the KNIME reporting features. Data processing forms a fundamental part of KNIME, and KNIME Essentials ensures that you are fully comfortable with this aspect of KNIME before showing you how to visualize this data and generate reports. "KNIME Essentials" guides you through the process of the installation of KNIME through to the generation of reports based on data. The main parts between these two phases are the data processing and the visualization. The KNIME variants of data analysis concepts are introduced, and after the configuration and installation description comes the data processing which has many options to convert or extend it. Visualization makes it easier to get an overview for parts of the data, while reporting offers a way to summarize them in a nice way.
Table of Contents (11 chapters)
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Computing statistics


When you want to explore your data, it usually is a good idea to compute some statistics about them so that you can spot the obviously wrong data (for example, when some data should be positive and it appears as a negative minimal value, it is suspicious).

Most of the nodes require you to not have NaN values within the data to be analyzed. You can remove them with the value modification techniques presented in the previous chapter, or by filtering the rows, also discussed in the previous chapter.

The minimal and maximal values can be checked in the port view's Spec Columns tab. This can already be used to spot certain kinds of problems.

For statistics within groups, we have the good old GroupBy node. That allows you to aggregate using the functions described on the Description tab of the configuration dialog.

When you do not need the grouping, you can use the Statistics node with easier configuration. Just select the columns, the number of values that should be present in...

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