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Ggplot2

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Ggplot2 refers to a data visualization package for the R programming language, designed to create complex and informative graphics based on the principles of the Grammar of Graphics. This skill encompasses the ability to construct a wide ra...

Skills CategoryAnalysis
Skills SubcategoryData Visualization
Skills TypeSpecialized Skill
Specialized TagsSoftware

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Dplyr

Dplyr is a package in the R programming language that provides an efficient and intuitive way to manipulate and filter data sets. It offers a set of functions that operate on data frames, including selecting columns, filtering rows, summarising data, and more. Dplyr is a powerful tool for data wrangling and is commonly used in data science and analysis projects.

Matplotlib is a data visualization library for creating static, animated, and interactive plots in Python. It is widely used in scientific computing and data analysis for presenting data in a visually appealing and informative way. Matplotlib provides a variety of plot types such as line, bar, scatter, contour, 3D, and more, as well as customizable features for tuning plot aesthetics, labeling axes, and adding legends. Skilled use of Matplotlib requires knowledge of Python and familiarity with data visualization concepts.

Seaborn is a powerful Python data visualization library that provides a high-level interface for creating informative and attractive statistical graphics. It is built on top of Matplotlib and provides a number of additional features, such as more advanced chart types, built-in color palettes, and sophisticated statistical visualization techniques. Seaborn is widely used in data science and machine learning to explore data, identify patterns, and communicate insights to stakeholders.

Shiny (R Package) refers to an open source software library for creating interactive web applications in the R programming environment. It is used to build dashboards, data visualizations, and analytical tools that allow users to explore data through forms, filters, and dynamic outputs. In work settings, it supports reporting, decision support, and the sharing of statistical results through browser based interfaces.

Text Mining refers to the process of extracting valuable information and insights from unstructured text data using various analytical techniques. This skill involves the application of natural language processing, statistical analysis, and machine learning to identify patterns, trends, and relationships within textual content. Knowledge of Text Mining is used to enhance decision-making in fields such as market research, sentiment analysis, and information retrieval by transforming raw text into structured data for further analysis.

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