categorical-data-visualization

There are 2 repositories under categorical-data-visualization topic.

• ggalluvial

  corybrunson / ggalluvial

  ggplot2 extension for alluvial plots

  ggplot2alluvial-diagramscategorical-data-visualizationrrepeated-measures-dataalluvial-plots
  Language:R 508

• friendly / vcdExtra

  Extensions and additions to vcd: Visualizing Categorical Data

  categorical-data-visualizationgeneralized-linear-modelsmosaic-plotsr-package
  Language:HTML 24

• gdagstn / swatcheR

  Fast automatic selection of color swatches from images

  color-pickercolor-schemedatavizcategorical-data-visualizationrcontinous-data-visualization
  Language:R 22

• alastairrushworth / inspectpd

  📈 📊 Methods for Exploring Pandas Data Frames

  categorical-data-visualizationcorrelationdataframeedaexploratory-data-analysispandaspython
  Language:Python 7

• Ravjot03 / Data-Visualization-with-Seaborn

  datavisualizationpythonseabornseaborn-plotsseaborn-tutorialcategorical-data-visualizationrelationalrelationaldatacountplotsbarplothistogrampointplotsscatter-plot
  Language:Jupyter Notebook 6

• g-insana / CMPlot.jl

  Cloudy Mountain Plot function in Julia

  categorical-data-visualizationcmplotdataframedensity-curvesjuliajulia-languagepirate-plotsplotlyplotsrdiviolin-plots
  Language:Julia 5

• g-insana / cmplot.py

  Cloudy Mountain Plot function in Python

  categorical-data-visualizationcmplotdataframedensity-curvespandaspirate-plotsplotlyplotspythonpython3rdiviolin-plots
  Language:Python 5

• mb7419 / egm

  A python package for plotting Evidence Gap Maps using Plotly

  scatterplotplotlycategorical-data-visualizationbubbleevidence-gap-mapcategoricalbin
  Language:Python 5

• Julien-Yacine / cramer_v_heatmap

  Vizualisation of the "correlation" between categorical variables using a cramer's v heatmap

  categorical-data-visualizationcorrelationheatmaprrstudiostatistics
  Language:HTML 4

• swilliamc / SAS_StatisticalBusinessAnalyst

  SAS Professional Certificate in Statistical Business Analyst using SAS

  sasstatisticsdata-analysisbusiness-analyticsregression-modelslogistic-regressionstatistical-analysisanovapearson-correlationpredictive-modelingcategorical-data-visualizationt-testsscoring-models
  4

• y656 / Data-Analytics-model-on-Behavioural-Challenges-of-ASD-kids

  This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset

  area-plotbarchartbivariate-analysisboxplotcategorical-data-visualizationcorrelation-matricescrosstabexploratory-data-analysisheatmaphistogrammatplotlib-pyplotmissing-valuesoutlier-detectionpandas-dataframepie-chartpythonscatter-plotseabornunivariate-analysis
  Language:Jupyter Notebook 4

• nicolelumagui / ML-Exercise_Telco-Customer-Churn_Classification

  Machine Learning Exercise: Exploring categorical plots, LabelEncoder, pipelines and GridSearchCV using Telco Customer Churn data from Kaggle

  python3machine-learningseaborncategorical-data-visualizationpipelinegridsearchcvchurnlogistic-regressionrandom-forest-classifierxgboostlabel-encoderresamplingcross-validate
  Language:Jupyter Notebook 2

• ashfaq-sadat / column-percent-calc

  In this repository I have calculated percent of all columns individually and created a bar graph showing what percent of respondents answered "yes" in a particular question.

  categorical-data-visualizationdata-analysisr
  Language:R 1

• NilsOle / categorical_data_explorer

  Client-sided visualization tool for categorical data (prototype)

  jqueryjquery-ui-widgetjquery-plugincategorical-data-visualizationjavascriptbootstraphandsontablehighchartsdashboard
  Language:HTML 1

• AVINASH-KURREY / Exploratory-data-analysis-EDA-

  Exploratory data analysis (EDA) NOTES

  bivariate-analysiscategorical-data-visualizationdata-analysismissing-valuesnormanumerical-dataoutlier-detectionoutlier-removaloutliersstandardizationtransformationunivariate-analysis
  0

• g-insana / cmplot

  Docs for Cloudy Mountain Plot

  categorical-data-visualizationcmplotdataframejuliapandaspirate-plotsplotplotlypythonviolin-plot
  0

• GLeurquin / Faithful-visualization-of-categorical-datasets

  Algorithm to reorder binary and categorical matrices using convolution

  seriationcategorical-data-visualizationbinary-datalocal-search
  Language:Scala 0

• zdanish1 / CategoricalDataExploration

  categorical-data-visualizationseabornanalysisfill-rate
  Language:Jupyter Notebook 0

• ashishyadav24092000 / EDA_on_HousePrice

  In this repository I have performed Exploratory data analysis on the dataset famously known as House Price Prediction.

  exploratory-data-analysiscategorical-featurescategorical-data-visualizationnumerical-analysisoutliers-detectioncardinalityseabornpandas-dataframemissing-datadistributions
  Language:Jupyter Notebook

• cjunwon / ODAQ-SDA

  Applying Categorical Exploratory Data Analysis (CEDA) methods to study audio quality perception

  audioaudio-processingcategorical-cross-entropycategorical-datacategorical-data-visualizationhierarchical-clusteringranking
  Language:Jupyter Notebook

• corybrunson / alluvial

  Alluvial diagrams

  alluvial-diagramscategorical-data-visualizationr
  Language:R

• DeepakKumarGS / Categorical-Encoding

  Repository for Categorical Feature Encoding Challenge in Kaggle 2019

  kaggle-competitioncategorical-data-visualizationonehot-encodingmachine-learningsklearnpython3
  Language:Jupyter Notebook

• guevara-erik / Wolrldwide-Suicide-Rates-Bivariate-Analysis

  Problem to solve: find the patterns for increased suicide rates (1985 to 2016) among different cohorts globally, across the socioeconomic spectrum, using exploratory data analysis. Using bivariate analysis, I try to determine if there is any relationship between two variables.

  analyticsbivariate-analysiscategorical-datacategorical-data-visualizationcorrelationjapannumerical-analysisnumerical-dataplottingsuicidesuicide-datasuicide-preventionworld-datawolrldwide-suicide-rates
  Language:Jupyter Notebook

• hoyirul / classification-naive-bayes-lingkungan

  Suatu pemecahan masalah dimana kondisi lingkungan di jakarta dibagi menjadi 3 yaitu BAIK, SEDANG dan TIDAK SEHAT dari dataset tersebutlah maka akan diolah dan diklasifikasi menurut kategorinya

  categorical-data-visualizationclassificationdatasetnaive-bayes-classifierpython
  Language:Jupyter Notebook