Statistics for everyone

[그래프 그리는 사이트] R 데이터 시각화 4권

----------- ----------- ----------- ----------- ----------- ----------- -----------

2-1. Dendro Bubble Plot https://tinyurl.com/Dendro-Bubble

2-2. Circular Chord diagram https://tinyurl.com/Chord-Plot

2-3. Sankey Wheel https://tinyurl.com/sankeywheel

2-4. Sankey Flow https://tinyurl.com/Sankey-Flow

2-5. D) Alluvial Diagrams https://tinyurl.com/D-Alluvial

2-6. Level Flow Chart https://tinyurl.com/level-flow2

2-7. Corset Plot https://tinyurl.com/Corset-Plot

2-8. Quadrant Scatter Plot https://tinyurl.com/quadscatter

2-9. Quiver(vector) Plots https://tinyurl.com/Quiver-Plots

2-10. Czekanowski’s Diagram https://tinyurl.com/Czekanowski-Diagram

2-11. Funnel Plot for Proportion

https://tinyurl.com/Funnel4P

2-12. Color Table

https://tinyurl.com/Color-Table

2-13. Multi Regression Fit

https://tinyurl.com/MultiRegression

2-14. Q-Q Boxplot

https://tinyurl.com/QQnBox

2-15. Pearson correlation with CI https://tinyurl.com/correlation-CI

2-16. Common Structures of Bias https://tinyurl.com/BiasStructures

2-17. Pair Plot https://tinyurl.com/PairPlot

2-18. Epidemiological Contacts https://tinyurl.com/Epi-Contact

2-19. R Pivot Table & Plot https://tinyurl.com/R-Pivot-table

2-20. Combination Count Plot(II) https://tinyurl.com/Combi-Plot2

2-21. Venn Diagram(IV) https://tinyurl.com/VennD4

2-22. Venn Diagram(III) https://tinyurl.com/VennDiagram3

2-23. Bipartite Network Plot https://tinyurl.com/bi2-network

2-24. Life Zones Triangle https://tinyurl.com/LifeZoneT

2-25. Isotonic Regression https://tinyurl.com/isotonicR

2-26. Grouped Box Plot https://tinyurl.com/grouped-Box

2-27. Bag Plot https://tinyurl.com/Bag-Plot

2-28. Elliplot https://tinyurl.com/Elliplot

2-29. Conditioning Plot(II) https://tinyurl.com/Conditioning-Plot-II

2-30. Multiple Duoplot https://tinyurl.com/duoplot

2-31. Letter Plot https://tinyurl.com/Letter-Plot

2-32. Stem Leaves https://tinyurl.com/Stem-Leaves

2-33. Inequality and Poverty https://tinyurl.com/Inequality-Poverty

2-34. Grouped Stack Barplot https://tinyurl.com/Barplots

2-35. Linear/Nonlinear Regression https://tinyurl.com/4Regression

2-36. Confusion Matrix Plot https://tinyurl.com/Matrix-Plot

2-37. 2D Density Plot https://tinyurl.com/2D-Density

2-38. QR code generator https://tinyurl.com/editQR

PART 3. 시간과 관련차트

3-1. Repeated Means Plot https://tinyurl.com/Re-Means

3-2. Many Repeated Means Plot https://tinyurl.com/Re-M4many

3-3. Summary Plot https://tinyurl.com/SummaryPlot

3-4. Aggregate Plot https://tinyurl.com/Aggregate-Plot

3-5. Horizon Plot(III) https://tinyurl.com/HorizonPlots3

3-6. Peak Valley Plot(Radiation) https://tinyurl.com/PeakVall

3-7. Max Point line plot https://tinyurl.com/Point-line

3-8. Detecting Anomalies in Data https://tinyurl.com/Anomalies-Data

3-9. Recurrence Plot https://tinyurl.com/Plot4Recur

3-10. Swimmer Plot https://tinyurl.com/Swimplot

3-11. Multiple Change Points https://tinyurl.com/Change-Points

3-12. Finding Inflection Points https://tinyurl.com/inflection-p

3-13. Inflection from GAM fit https://tinyurl.com/GAM-inflection

3-14. Climate Graph https://tinyurl.com/Climate-Graph

3-15. Plots for Time & State https://tinyurl.com/time-state

3-16. Surveillance Graph https://tinyurl.com/SurveilPLOT

3-17. Monthly & Yearly Calendars https://tinyurl.com/MY-Calendars

3-18. Calendars and Gannt Chart https://tinyurl.com/Cal4Gant

3-19. D) Timeline https://tinyurl.com/D-Timeline-I

3-20. Gantt Chart https://tinyurl.com/Gantt-C

3-21. Event Chart https://tinyurl.com/Event-Chart

3-22. Cosinor Regression Model https://tinyurl.com/Cosinor-Reg

3-23. Chronological Plot https://tinyurl.com/Chronplot

3-24. Bump Chart(II) https://tinyurl.com/BumpChart2

3-25. Multiple Run Charts https://tinyurl.com/MultiRun

3-26. SPC charts for NHS https://tinyurl.com/SPC4NHS

3-27. Body Weight with ID https://tinyurl.com/IDWeight

3-28. Stream Plot(III) https://tinyurl.com/stream-plot3

3-29. Comparative Line Plot https://tinyurl.com/Comparative-Line-Plot

3-30. Google Trends https://tinyurl.com/Goo-Trend

3-31. Forecast Murphy Diagrams https://tinyurl.com/Murphy-D

3-32. Lexis diagram(2) https://tinyurl.com/Lexis-D2

3-33. Trajectory Clustering https://tinyurl.com/traject-cluster

PART 4. 지도

4-1. Flights Plots https://tinyurl.com/flightsPlots

4-2. D) OECD Bar https://tinyurl.com/D-OECD-bar

4-3. D) EU Bar https://tinyurl.com/D-EU-bar2

4-4. D) Japan Bar https://tinyurl.com/D-Japan-bar

4-5. D) South East Asian Bar https://tinyurl.com/D-SEA-bar

4-6. D) USA Bar https://tinyurl.com/D-USA-bar

https://tinyurl.com/https://tinyurl.com/D-USA-DC

https://tinyurl.com/D-USA-census

https://tinyurl.com/D-USA-HHS

4-7. D) Korea-sido Bar Chart https://tinyurl.com/D-Korea-bar

4-8. D) Seoul Bar Chart https://tinyurl.com/D-Seoul-bar

4-9. D) Seoul Line Chart https://tinyurl.com/D-Seoul-line

4-10. Quiver Wind Plot https://tinyurl.com/Quiver-Wind

PART 5. 유전과 인간5

5-1. Haplotypes in a cell https://tinyurl.com/Haplotypes

5-2. Nucleobase Plot https://tinyurl.com/Nucleobase-Plot

5-3. Lollipop for Mutation https://tinyurl.com/lollipop-mutation

5-4. Population Genetics https://tinyurl.com/Pop-Gene

5-5. D) Pedigree Chart https://tinyurl.com/D-Pedigree

5-6. D) Pyramid Chart https://tinyurl.com/D-Pyramid

5-7. D) Dual Pyramid Chart https://tinyurl.com/D-Dual-Pyramid

5-8. D) Compare Populations https://tinyurl.com/D-Compare-Pop

5-9. MA plot https://tinyurl.com/ma4RNA

5-10. Gene Ontology Bubble Plot https://tinyurl.com/Ontology-Bubble

5-11. GO(gene ontology) Plot https://tinyurl.com/Goplot

5-12. Sequence Logo Plot https://tinyurl.com/Seq-Logo

5-13. Sequence Letter Plot https://tinyurl.com/Seq-Letter

5-14. Medical Illuster https://tinyurl.com/Human-ana

5-15. Blood Pressure Study https://tinyurl.com/B-Press

5-16. Growth Charts https://tinyurl.com/Chart4Growth

5-17. Growth Curves https://tinyurl.com/Growth-Curve

5-18. Cancer Adverse Events https://tinyurl.com/Cancer-AE

5-19. Brain Atlas https://tinyurl.com/Brain-Atlas

5-20. Visual Fields https://tinyurl.com/visualFields

5-21. Daily Physical Activity https://tinyurl.com/Daily-Behavior

PART 6. 통계와 차트

6-1. Confidence Interval https://tinyurl.com/Cisimul

6-2. Think-More Plot https://tinyurl.com/think-more

6-3. Compare Two Correlations https://tinyurl.com/Compare2corr

6-4. PS Matching(III) https://tinyurl.com/PS-Matching3

6-5. Many ROC https://tinyurl.com/many-ROC

6-6. Benford Test https://tinyurl.com/D-Benford

6-7. Sliding Chart https://tinyurl.com/Slidingchart

6-8. Repeated Correlation https://tinyurl.com/Repeated-Correlation

6-9. Survival ROC https://tinyurl.com/survivalROC

6-10. Find Missing https://tinyurl.com/missing-treat

6-11. Missing Data https://tinyurl.com/4Missing

6-12. Box Cox Transformation(II) https://tinyurl.com/Box-Coxes

6-13. Standardization https://tinyurl.com/easy-Standard

6-14. Fagan’s Nomogram https://tinyurl.com/Fagan-nomogram

6-15. Agreement and Reliability https://tinyurl.com/SimplyAgree

6-16. Linear Mixed Effects Model https://tinyurl.com/LMM-long

6-17. Hierarchical cluster analysis https://tinyurl.com/Item-Cluster

6-18. Supervised Heatmap https://tinyurl.com/Supervised-Heatmap

6-19. Single-Case Data Analyses https://tinyurl.com/Single-Case

6-20. Single-Case Random Test https://tinyurl.com/SingCRT

6-21. Relative survival https://tinyurl.com/Rel-surv

6-22. Correlation Funnel Plot https://tinyurl.com/Correlation-Funnel

6-23. Explore Plot https://tinyurl.com/plot4explore

6-24. Tools for regression models https://tinyurl.com/T4regression

6-25. Linearity Check Plots https://tinyurl.com/linearity-plot

6-26. Subgroups Forest Plot(I) https://tinyurl.com/Forest4Subgroups

6-27. Subgroup Forest Plot(II) https://tinyurl.com/Subgroup-S

6-28. Regression Discontinuity https://tinyurl.com/R-Discontinuity

6-29. False Discovery Rate Plot https://tinyurl.com/Plot4FDR

6-30. Bias Precision Plot https://tinyurl.com/Bias-Precision

6-31. Bioequivalence Study https://tinyurl.com/Bio-Equ2

6-32. CONSORT Diagram(I) https://tinyurl.com/ConsortDiagram

6-33. CONSORT Diagram(II) https://tinyurl.com/CONSORT-D

6-34. Flow Diagram https://tinyurl.com/Flow-D

6-35. Time-dependent ROC curve https://tinyurl.com/Time-ROC

6-36. Association Analysis https://tinyurl.com/Asso-Anal

6-37. Plateau Chart https://tinyurl.com/Plateau-Chart

6-38. FF Decision Tree https://tinyurl.com/FF-Dtree

6-39. PRECIS-2 & Radar Charts https://tinyurl.com/2PRECIS

6-40. 3D Volcano Plot https://tinyurl.com/Polar4Three

6-41. Adherence Plot https://tinyurl.com/AdherenceMed

6-42. Mean and SD from Quantiles https://tinyurl.com/estmeansd

6-43. 잘려진 정규분포 https://tinyurl.com/Detect-Nonnormal

>> 중심극한정리 실험

https://tinyurl.com/Central-Limit

part 7 발표용 plot

7-1. D) Rose Plots https://tinyurl.com/D-Rose-Plots

7-2. D) Dynamic line chart https://tinyurl.com/D-Dynamic-line

7-3. D) Infectious Dynamics https://tinyurl.com/D-Infect-Dyn

7-4. D) Matrix Bubble Plot https://tinyurl.com/D-Matrix-Bubble

7-5. D) Pareto Plot https://tinyurl.com/D-Pareto-C

7-6. D) ANOVA & Kruskal-Wallis https://tinyurl.com/D-Kruskal-Wallis

7-7. D) Bars and Lollipops https://tinyurl.com/D-LollipopBars

7-8. D) Understand ROC https://tinyurl.com/D-Understand-ROC

7-9. D) Wordcloud(I) https://tinyurl.com/D-Wordcloud

7-10. D) Wordcloud(II) https://tinyurl.com/D-wordcloud2

7-11. D) Compare Events main https://tinyurl.com/D-EventsRisk

7-12. D) SixSigma Capability https://tinyurl.com/D-6S-Capability

7-13. D) SixSigma Process Map https://tinyurl.com/D-6S-Process

7-14. D) Quality Improvement https://tinyurl.com/D-Qual-I

7-15. D) Quality Control Charts https://tinyurl.com/D-Qual-C

7-16. D) CUSUM-EWMA Chart https://tinyurl.com/D-CUSUM-EWMA

7-17. D) Quality Loss Function https://tinyurl.com/D-Qual-Loss

7-18. D) Correlogram https://tinyurl.com/D-Correlogram

7-19. D) Likert Chart(I) https://tinyurl.com/D-Likert-1

7-20. D) Matrix Correlations https://tinyurl.com/D-Mat-Corr

7-21. D) Cause Effect Diagram https://tinyurl.com/D-fish-CE

[그래프 그리는 사이트] Volcano Plot

site : Volcano_Plot

In the example data, there are only 4 columns that are actually used:

'outcome' 'logFC' 'PValue' 'labels'.

예제 데이터에서 실제 사용되는 열은

'outcome' 'logFC' 'PValue' 'labels' 즉 4개의 열뿐입니다.

In the end, 'logFC' is used as the x-axis, 'PValue' is used as the value on the y-axis,

and the value of 'outcome' is expressed as the color of the point.

결국'logFC'은 x축으로 'PValue'는 y축의 값으로 사용되며,

'outcome'의 값은 점의 색으로 표현됩니다.

'type2' expresses the y-axis in log scale,

The value in the 'labels' column is displayed through 'show label'.

'type2'는 y축을 로그스케일로 표현하며

'show label'을 통해 'labels'열에 있는 값을 표시해 줍니다.

This is to display points with small p-values and points with logFC far from zero.

It looks like a volcano exploding.

결국 많은 점들 중에서 p값이 작고 logFC가 0으로부터 먼 점들을 표시하기 위한 것입니다.

모양이 마치 화산이 폭발하는 것같은 모양이군요.

You can specify the size and x-axis name of the point.

You can also easily change the color palette and theme.

점의 크기와 x축 이름을 지정할 수 있습니다.

또 색 파레트와 테마도 쉽게 바꿀 수 있습니다.

'plot download'를 통해서 plot size를 조절하세요.

< PDF >, < SVG > < pptx >를 클릭하면 각각의 형식으로 다운로드 받을 수 있습니다.

Adjust the plot size through 'plot download'.

You can download each format by clicking < PDF >, < SVG > < pptx >.

당신의 데이터를 업로드 하려면 'want to use'를 활성화한 다음, 'Browse'를 클릭하세요.

오직 csv 파일만이 사용가능합니다.

Activate 'want to use' to upload your data, then click 'Browse'.

Only csv file is available.