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3495c1d2c32dafde00697335f4389a98dead3f18
LadyoftheWater/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
anupkumardixit/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
richardmarkhunt/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
martingascon/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
ashishchandan/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
bospetersen/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Jackson85/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
JeromeAli/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
dvbhagavathi/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
tjautio/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
adri894/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
niloynibhochaudhury/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
AMPrescott/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
smuch/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
anfe67/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
MeiSenTafsm/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
amalarrachidi/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
johnneyb/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
fbagirov/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
AnyaMit/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
GundamYeti/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
emiels/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
jmacarter/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
aruneral01/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
shrekodn/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
maskegger/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
richardwei2008/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
noahchense/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
pegasusTH/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
lblinder/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
dhduncan/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
k3140285kop/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
drnuance/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Jambiol/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
gringwald/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
mmfern01/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Hris2013/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
TeddyTiome/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
johnsonzhj/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Romka11/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
xiang-tischhauser/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
dpc5090/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
martik617/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
sriramanathan/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
warszawiak/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
jrgantunes/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
sagigr/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Jutair/R-programming-Coursera
Swirl/Rsubversion/branches/eda/Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-2.0
3495c1d2c32dafde00697335f4389a98dead3f18
arjitmazumdar/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
tapangoel1994/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
MarcoTomasetta/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
CarlosJunior4763/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
horrorkumani/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
akhilK17/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
yechen1974/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
jacobmbr/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
chenyan1994/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
fvdgeer/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
vishalshastri/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
jdgriffin/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
pavanmg/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
xujiawei1993/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
gccmsu/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
brezniczky/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
kevinbgunn/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
wengers11/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
fainafr/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
lgreski/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
momoa16/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
patricksu/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
pmijar/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
ZiTUNG/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
ndeltortoiii/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
Evegen55/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
fanglu01/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
3495c1d2c32dafde00697335f4389a98dead3f18
ABourcevet/swirl_courses
Exploratory_Data_Analysis/Hierarchical_Clustering/complete2.R
points(x[11],y[11],col="orange",pch=3,lwd=3,cex=3) segments(x[8],y[8],x[11],y[11],lwd=3,col="orange")
102
gpl-3.0
b7856bd8442fdcc422b8d8a2c0d7310b7782d9f2
CodeGit/SequenceImp
dependencies-bin/macosx/bin/R/lib/R/library/gdata/unitTests/runit.drop.levels.R
### runit.drop.levels.R ###------------------------------------------------------------------------ ### What: Tests for drop.levels ### $Id: runit.drop.levels.R 993 2006-10-30 17:10:08Z ggorjan $ ### Time-stamp: <2006-08-29 14:21:12 ggorjan> ###------------------------------------------------------------------------ #...
1,022
gpl-3.0
b7856bd8442fdcc422b8d8a2c0d7310b7782d9f2
CodeGit/SequenceImp
dependencies-bin/windows/bin/R/library/gdata/unitTests/runit.drop.levels.R
### runit.drop.levels.R ###------------------------------------------------------------------------ ### What: Tests for drop.levels ### $Id: runit.drop.levels.R 993 2006-10-30 17:10:08Z ggorjan $ ### Time-stamp: <2006-08-29 14:21:12 ggorjan> ###------------------------------------------------------------------------ #...
1,022
gpl-3.0
c30a7f1735d4996ead6a60022bb2ace0070a2eeb
petzi53/audiemus
daten-bereinigen/get-data.3.R
## ----label = "global-options", echo=FALSE, highlight=TRUE---------------- knitr::opts_chunk$set( message = F, error = F, warning = F, comment = NA, highlight = T, prompt = T ) if (!require("tidyverse")) {install.packages("tidyverse", repos = 'http://cr...
10,812
gpl-3.0
8b49dcafd812ec404a97f7d9e5e4a91f7e4a9aec
bedatadriven/renjin
tests/src/test/R/test.eapply.R
# # Renjin : JVM-based interpreter for the R language for the statistical analysis # Copyright © 2010-2019 BeDataDriven Groep B.V. and contributors # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundati...
1,138
gpl-2.0
de9dbeb50a1d1c87c1273c4ef9f3f3cdcd41d1b0
sqor/3rdeye
individual.R
format_coder <- function(git_log_full, email){ coder <- git_log_full[git_log_full$author_email == email,] repos_count <- length(as.integer((unique(coder$repo)))) total_commmits <- median(coder$count) last <- head(coder[ order(coder$time , decreasing = TRUE ),],n=1) first <- head(coder[ order(coder$time , decreasi...
1,705
mit
25f29472c9d10406e27575ff8a5f4887d554aba2
C2SM/gevXgpd
R/F.of.T.R
"F.of.T" <- function (t,lamda=1) {1-1/(lamda*t)}
50
gpl-2.0
5ffbe24ad0731d2f83bfa34090792118f25beb18
DarrenCook/h2o
code/glm.mnist.R
seed = 450 source("load.mnist.R") #With 3.10.0.8, on notebook: 2.727 0.387 152.600 (8 cores kept busy) # (first time to be using seed) # Scored 775 on valid, 0.0627 error on train. 740 on test # (the values in the book are 782 on valid, 746 on test, and it took 4 minutes) system.time( m <- h2o.glm(x, y, ...
23,106
mit
6acc7f7639f48d9e015aa478e6d059fd1c4451fb
snoweye/pbdDEMO
R/verify.R
#' Distributed Linear Algebra Verification #' #' At-scale verification routines for distributed linear algebra. #' #' These routines numerically verify the accuracy of the given #' operation. Each operation generates only the local data that #' is needed, and one never needs to store the global problem on #' any one...
7,776
mpl-2.0
6acc7f7639f48d9e015aa478e6d059fd1c4451fb
wrathematics/pbdDEMO
R/verify.R
#' Distributed Linear Algebra Verification #' #' At-scale verification routines for distributed linear algebra. #' #' These routines numerically verify the accuracy of the given #' operation. Each operation generates only the local data that #' is needed, and one never needs to store the global problem on #' any one...
7,776
mpl-2.0
beb8f1e5a4e8988d14982f486c50bad2aa11dfa7
CSCAP/Sustainable_Corn_Paper
Code/SoilDataCleaning_forSP.R
# LOAD DATA --------------------------------------------------------- setwd("C:/Users/Gio/Documents") dir() # get table from database library(ggplot2) library(dplyr) library(lubridate) source("~/GitHub/R/My_Source_Codes/CSCAPpostgerDBconnect.R") # READ AGRO DATA ---------------------------------------------------- # ...
15,597
mit
2ab2fc8bffe1f3676f594d55d83d5ba8e3bb3ec6
topsoil/patternCNV
R/computeMultiCNV.R
computeMultiCNV <- function( session.name, data.name=NULL, sample.type=NULL, ref.type='average.pattern', episl=1, small.delta=1e-5, bin.size=10, zero.median.adjust=TRUE,is.verbose=FALSE) { if(class(session.name)!='PatCNVSession') { stop('input session.name should be class of "PatCNV...
3,655
artistic-2.0
6acc7f7639f48d9e015aa478e6d059fd1c4451fb
RBigData/pbdDEMO
R/verify.R
#' Distributed Linear Algebra Verification #' #' At-scale verification routines for distributed linear algebra. #' #' These routines numerically verify the accuracy of the given #' operation. Each operation generates only the local data that #' is needed, and one never needs to store the global problem on #' any one...
7,776
mpl-2.0
6acc7f7639f48d9e015aa478e6d059fd1c4451fb
cran/pbdDEMO
R/verify.R
#' Distributed Linear Algebra Verification #' #' At-scale verification routines for distributed linear algebra. #' #' These routines numerically verify the accuracy of the given #' operation. Each operation generates only the local data that #' is needed, and one never needs to store the global problem on #' any one...
7,776
mpl-2.0
6222694b39bc9674018b830208f09a3e5656d667
ritviksahajpal/meteoForecast
R/grepVar.R
grepVar <- function(x, service, complete = FALSE){ varsFile <- switch(service, meteogalicia = 'varsMG', openmeteo = 'varsOM', gfs = 'varsGFS', nam = 'varsNAM', rap = 'varsRAP', s...
512
gpl-3.0
462926025a7214b26eeddec2296a4844e2396277
cran/RadioSonde
R/setupSkewt.R
"setupSkewt" <- function( BROWN = "brown3", GREEN = "green4", redo = FALSE, tempRangeF = c( -20, 104 ),...) { #--------------------------------------------------------------------- # # This program generates a skew-T, log p thermodynamic diagram. This # program was derived to riff off of the USAF sk...
2,628
gpl-2.0
2561991470ba07db0ad25f66fc740fd8a162c1cd
miken22/BaseballWithR
src/Chap4.R
# Chapter 4 # Following the examples worked through in the chapter with modifications # to players/teams followed. Written by Mike Nowicki. # Load packages into environment if not already. require(curl) require(data.table) require(chron) require(dplyr) require(Lahman) require(pitchRx) require(plyr) require(retrosheet)...
12,066
gpl-2.0
2fccc90815dd59f614285605020a796eb3f19ade
ygraham/segment-mteval
proc-hits/trk-mean-sd.R
# Copyright 2015 Yvette Graham # # This file is part of SegmentMTeval. # # SegmentMTeval is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later vers...
1,477
gpl-3.0
01210f9429afaaf9d2e614f5a36a3b372327ca86
joelfiddes/toposubv2
workdir/modalSurface.R
#==================================================================== # SETUP #==================================================================== #INFO #DEPENDENCY require(raster) #==================================================================== # PARAMETERS/ARGS #===============================================...
920
gpl-3.0
2fccc90815dd59f614285605020a796eb3f19ade
alvations/segment-mteval
proc-hits/trk-mean-sd.R
# Copyright 2015 Yvette Graham # # This file is part of SegmentMTeval. # # SegmentMTeval is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later vers...
1,477
gpl-3.0
01210f9429afaaf9d2e614f5a36a3b372327ca86
joelfiddes/toposubv2
topoMAPP/rsrc/modalSurface.R
#==================================================================== # SETUP #==================================================================== #INFO #DEPENDENCY require(raster) #==================================================================== # PARAMETERS/ARGS #===============================================...
920
gpl-3.0
01210f9429afaaf9d2e614f5a36a3b372327ca86
joelfiddes/topoMAPP
rsrc/modalSurface.R
#==================================================================== # SETUP #==================================================================== #INFO #DEPENDENCY require(raster) #==================================================================== # PARAMETERS/ARGS #===============================================...
920
mit
9d79bb3611042b6c3ba0742fa99c01b76bd6b260
stdlib-js/stdlib
lib/node_modules/@stdlib/math/base/special/maxabs/benchmark/r/benchmark.R
#!/usr/bin/env Rscript # # @license Apache-2.0 # # Copyright (c) 2018 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #...
2,891
apache-2.0
3d865e9fdb8ffb6cef4497b7fb3f69b24ea11c9e
feralindia/CWC
Hydrographs/stn_102.R
## Station 103 is associated with: ## wlr: 103, 103a ## flume: 113 ## tbrg: 103, 109 ## bs: 102, 123 ## this script collates data for wlr 103 & 103a and ## runs a routine for flume 113 ##--- define constants stn.no <- 102 ar.cat <- 748462.5 catch.type <- "Wattle Catchment" wlr.path <- "~/OngoingProjects/CWC/Data/Nilgi...
1,230
gpl-3.0
b3a835605856a925061b674daf552b3c629db145
BCCVL/org.bccvl.compute
src/org/bccvl/compute/content/toolkit/demosdm/demosdm.R
#### ## ## INPUT: ## ## occur.data ... filename for occurence data ## absen.data ... filename for absence data ## enviro.data.current ... list of filenames for climate data ## enviro.data.type ... continuous ## opt.tails ... predict parameter ## ## outputdir ... root folder for output data #define the worki...
19,030
gpl-2.0