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DO YOU WANT TO VISUALIZE YOUR DATA MORE EASILY!! ๐Ÿ‘‰THEN TRY DATAEXPLORER PACKAGE ๐Ÿ‘‡

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The most time-consuming and tedious data science endeavor is cleaning and organizing data. DataExplorer is one of the resources available that has the express goal of reducing the 80% and making it pleasurable. As a result, being exceedingly user-friendly is a basic design principle. One function call is typically all you need. DataExplorer is an R package that provides a set of functions for creating summaries and visualizations of data. It is designed to make it easy for users to quickly get an overview of their data and identify patterns and trends. Here are some key features of DataExplorer:   ๐Ÿ‘‰Provides a variety of summary statistics and visualizations for different types of data, including numerical, categorical, and text data.   ๐Ÿ‘‰Allows users to easily create plots, tables, and summary statistics for a single variable or for multiple variables.   ๐Ÿ‘‰Offers options for customizing the appearance and formatting of plots and tables.   ๐Ÿ‘‰Can handle large datasets...

USING DIFFERENT THEMES IN R FOR DATA VISUALIZATION

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There are several built-in themes available in R. Some common themes include: ๐Ÿ‘‰ theme_grey() applies a simple grey background to the plot. ๐Ÿ‘‰ theme_bw() removes colors and grid lines from the plot. ๐Ÿ‘‰ theme_minimal() and theme_light() provide a more modern and clean look to the plot.  ๐Ÿ‘‰ theme_classic() has a white background, grid lines, and a black axis line. It also includes a title, axis labels, and a legend, if applicable. This theme is often used for traditional data visualizations and is a good choice for plots that will be printed or included in reports. ๐Ÿ‘‰ theme_dark()  i s often used for data visualizations that will be displayed on a screen, such as in a dashboard or web application. The dark background helps to make the data points and other visual elements stand out, making the plot easier to read. ๐Ÿ‘‰ theme_linedraw() is a function in the R programming language that is used to apply the "linedraw" theme to a plot or graph. This theme is based on the "li...

LATTICE PACKAGE IN R-DATA VISUALIZATION

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 The lattice package is a powerful data visualization library for the R programming language. It is designed to provide a high-level interface for creating attractive and informative statistical graphics. The package is built on top of the grid graphics engine, which provides a consistent API for creating a wide variety of plots. It is written by Deepayan Sarkar. Numerous helpful functions are offered by the lattice package, which can produce single factor graphs (such as dot plots, histograms, bar plots, and box plots), bivariate graphs (such as scatter plots, strip graphs, and parallel boxplots), and multivariate charts (three-dimensional graphs and scatter plot matrixes). Install the lattice package > install.packages("lattice") load lattice > library(lattice) Common graph_function: xyplot() : Scatter plot splom() : Scatter plot matrix cloud() : 3D scatter plot stripplot() : strip plots (1-D scatter plots) bwplot() : Box plot dotplot() : Dot plot barchart() : bar cha...

R - EDA(EXPLORATORY DATA ANALYSIS)

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I'll explain the exploratory data analysis(EDA) process in this blog post, which is a crucial step in data science using the diabetes dataset.   EDA (Exploratory Data Analysis) is a method for examining datasets to highlight their significant characteristics, frequently using visual techniques.   EDA can be divided into three categories: 1. Data Comprehension 2. Eliminating Extraneous Data 3. Analyzing Data for Relationships   Information About The Dataset This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage. Pregnancies: Number of times pregnant Glucose: Plasma ...