airline.distances.1966: Hartigan (1975) Airline Distance Between Principal Cities of...
In cluster.datasets: Cluster Analysis Data Sets
Description
Usage
Format
Details
Source
References
Examples
Description
The table contains the airline distances in hunds of miles between the
principal cities of the world. This is Table 11.1 in Chapter 11 of Hartigan (1975)
on page 192.
Usage
1
Format
A data frame with 30 observations on the following 31 variables.
codea character vector for the cities
AZa numeric vector for Azores
BDa numeric vector for Baghdad
BNa numeric vector for Berlin
BYa numeric vector for Bombay
BSa numeric vector for Buenos Aires
COa numeric vector for Cairo
CNa numeric vector for Capetown
CHa numeric vector for Chicago
GMa numeric vector for Guam
HUa numeric vector for Honolulu
ILa numeric vector for Istanbul
JUa numeric vector for Juneau
LNa numeric vector for London
MAa numeric vector for Manila
MEa numeric vector for Melbourne
MYa numeric vector for Mexico City
MLa numeric vector for Montreal
MWa numeric vector for Moscow
NSa numeric vector for New Orleans
NYa numeric vector for New York
PYa numeric vector for Panama City
PSa numeric vector for Paris
ROa numeric vector for Rio De Janeiro
REa numeric vector for Rome
SFa numeric vector for San Francisco
SOa numeric vector for Santiago
SEa numeric vector for Seattle
SIa numeric vector for Shanghai
SYa numeric vector for Sydney
TOa numeric vector for Tokyo
Details
Hartigan uses this data set with the single linkage algorithm.
Source
The World Almanac (1966).
SPAETH2 Cluster Analysis Datasets http://people.sc.fsu.edu/~jburkardt/datasets/spaeth2/spaeth2.html
References
Hartigan, J. A. (1975). Clustering Algorithms, John Wiley, New York.
Examples
1
Example output
cluster.datasets documentation built on May 2, 2019, 3:39 p.m.
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Description Usage Format Details Source References Examples
Description
The table contains the airline distances in hunds of miles between the principal cities of the world. This is Table 11.1 in Chapter 11 of Hartigan (1975) on page 192.
Usage
1 |
Format
A data frame with 30 observations on the following 31 variables.
codea character vector for the cities
AZa numeric vector for Azores
BDa numeric vector for Baghdad
BNa numeric vector for Berlin
BYa numeric vector for Bombay
BSa numeric vector for Buenos Aires
COa numeric vector for Cairo
CNa numeric vector for Capetown
CHa numeric vector for Chicago
GMa numeric vector for Guam
HUa numeric vector for Honolulu
ILa numeric vector for Istanbul
JUa numeric vector for Juneau
LNa numeric vector for London
MAa numeric vector for Manila
MEa numeric vector for Melbourne
MYa numeric vector for Mexico City
MLa numeric vector for Montreal
MWa numeric vector for Moscow
NSa numeric vector for New Orleans
NYa numeric vector for New York
PYa numeric vector for Panama City
PSa numeric vector for Paris
ROa numeric vector for Rio De Janeiro
REa numeric vector for Rome
SFa numeric vector for San Francisco
SOa numeric vector for Santiago
SEa numeric vector for Seattle
SIa numeric vector for Shanghai
SYa numeric vector for Sydney
TOa numeric vector for Tokyo
Details
Hartigan uses this data set with the single linkage algorithm.
Source
The World Almanac (1966).
SPAETH2 Cluster Analysis Datasets http://people.sc.fsu.edu/~jburkardt/datasets/spaeth2/spaeth2.html
References
Hartigan, J. A. (1975). Clustering Algorithms, John Wiley, New York.
Examples
1 |
Example output
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