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ggplot2 - Easy way to mix multiple graphs on the same page - R software and...
Install and load required packagesInstall and load the package gridExtraInstall and load the package cowplotPrepare some dataCowplot: Publication-ready plotsBasic plotsArranging multiple graphs using...
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How to choose the appropriate clustering algorithms for your data? -...
1 Clustering validation measures in clValid package1.1 Internal validation measures1.2 Stability validation measures1.3 Biological validation measures2 R function clValid()2.1 Format2.2 Examples of...
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Hybrid hierarchical k-means clustering for optimizing clustering outputs -...
1 How this article is organized2 Required R packages3 Data preparation4 R function for clustering analyses4.1 Example of k-means clustering4.2 Example of hierarchical clustering5 Combining hierarchical...
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HCPC: Hierarchical clustering on principal components - Hybrid approach (2/2)...
1 Why combining principal component and clustering methods?1.1 Case of continuous variables: Use PCA as denoising step1.2 Case of categorical variables: Use CA or MCA before clustering2 Algorithm of...
View Articlefacto_summarize - Subset and summarize the output of factor analyses - R...
DescriptionInstall and load factoextraUsageArgumentsDetailsValueExamplesPrincipal component analysisCorrespondence AnalysisMultiple Correspondence AnalysisInfosDescriptionSubset and summarize the...
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fviz_ca: Quick Correspondence Analysis data visualization using factoextra -...
DescriptionInstall and load factoextraUsageArgumentsDetailsValueExamplesCorrespondence Analysisfviz_ca_row(): Graph of row variablesfviz_ca_col(): Graph of column categoriesfviz_ca_biplot(): Biplot of...
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DBSCAN: density-based clustering for discovering clusters in large datasets...
1 Concepts of density-based clustering2 Algorithm of DBSCAN3 R packages for computing DBSCAN4 R functions for DBSCAN5 Method for determining the optimal eps value6 Cluster predictions with DBSCAN...
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fviz_mca: Quick Multiple Correspondence Analysis data visualization - R...
DescriptionInstall and load factoextraUsageArgumentsDetailsValueExamplesMultiple Correspondence Analysisfviz_mca_ind(): Graph of individualsfviz_mca_var(): Graph of variable...
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fviz_pca: Quick Principal Component Analysis data visualization - R software...
DescriptionInstall and load factoextraUsageArgumentsValueExamplesPrincipal component analysisfviz_pca_ind(): Graph of individualsfviz_pca_var(): Graph of variablesfviz_pca_biplot(): Biplot of...
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qplot: Quick plot with ggplot2 - R software and data visualization
Data formatUsage of qplot() functionScatter plotsBasic scatter plotsScatter plots with linear fitsLinear fits by groupsChange scatter plot colorsChange the shape and the size of pointsScatter plot with...
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ggplot2 area plot : Quick start guide - R software and data visualization
Prepare the dataBasic area plotsChange line types and colorsChange colors by groupsCalculate the mean of each group :Change fill colorsChange the legend positionUse facetsContrasting bar plot and area...
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ggplot2 line plot : Quick start guide - R software and data visualization
Basic line plotsDataCreate line plots with pointsLine plot with multiple groupsDataCreate line plotsChange line types by groupsChange line colors by groupsChange the legend positionLine plot with a...
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ggplot2 : Quick correlation matrix heatmap - R software and data visualization
Prepare the dataCompute the correlation matrixCreate the correlation heatmap with ggplot2Get the lower and upper triangles of the correlation matrixFinished correlation matrix heatmapReorder the...
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Clustering Validation Statistics: 4 Vital Things Everyone Should Know -...
1 Required packages2 Data preparation3 Relative measures: Determine the optimal number of clusters4 Clustering analysis4.1 Example of partitioning method results4.2 Example of hierarchical clustering...
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Determining the optimal number of clusters: 3 must known methods -...
1 Required packages2 Data preparation3 Example of partitioning method results4 Example of hierarchical clustering results5 Three popular methods for determining the optimal number of clusters5.1 Elbow...
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Hybrid hierarchical k-means clustering for optimizing clustering outputs -...
1 How this article is organized2 Required R packages3 Data preparation4 R function for clustering analyses4.1 Example of k-means clustering4.2 Example of hierarchical clustering5 Combining hierarchical...
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ggplot2 axis scales and transformations
Prepare the dataExample of plotsChange x and y axis limitsUse xlim() and ylim() functionsUse expand_limts() functionUse scale_xx() functionsAxis transformationsLog and sqrt transformationsFormat axis...
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ggplot2 colors : How to change colors automatically and manually?
Prepare the dataSimple plotsUse a single colorChange colors by groupsDefault colorsChange colors manuallyUse RColorBrewer palettesUse Wes Anderson color palettesUse gray colorsContinuous colorsGradient...
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ggplot2 texts : Add text annotations to a graph in R software
Create some dataText annotations using the function geom_textChange the text color and size by groupsAdd a text annotation at a particular coordinateannotation_custom : Add a static text annotation in...
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GGally R package: Extension to ggplot2 for correlation matrix and survival...
InstallationLoading GGally packageggcorr(): Plot a correlation matrixggpairs(): ggplot2 matrix of plotsggsurv(): Plot survival curve using ggplot2DataSurvival curvesInfosGGally extends ggplot2 by...
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