A Colombian Departmental grid inspired by Manuel Aristaran's Argentina province grid and Mike Bostock's state grid. Originally seen on Allison McCann's graphic about US state taxes.
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icd10cm,desc_short,desc_long,ED_Care_Needed__not_Preventable_,ED_Care_Needed__Preventable_Avoi,Emergent__PC_Treatable,Non_Emergent,Alcohol,Drug,Injury,Psych,Unclassified | |
A000,"Cholera due to Vibrio cholerae 01, biovar cholerae","Cholera due to Vibrio cholerae 01, biovar cholerae",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A001,"Cholera due to Vibrio cholerae 01, biovar eltor","Cholera due to Vibrio cholerae 01, biovar eltor",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A009,"Cholera, unspecified","Cholera, unspecified",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0100,"Typhoid fever, unspecified","Typhoid fever, unspecified",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0101,Typhoid meningitis,Typhoid meningitis,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0102,Typhoid fever with heart involvement,Typhoid fever with heart involvement,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0103,Typhoid pneumonia,Typhoid pneumonia,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0104,Typhoid arthritis,Typhoid arthritis,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0105,Typhoid osteomyelitis,Typhoid osteomyelitis,0%,0%,0%,0%,0%,0%,0%,0%,100% |
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icd10cm,desc_short,desc_long,ED_Care_Needed__not_Preventable_,ED_Care_Needed__Preventable_Avoi,Emergent__PC_Treatable,Non_Emergent,Alcohol,Drug,Injury,Psych,Unclassified | |
A000,"Cholera due to Vibrio cholerae 01, biovar cholerae","Cholera due to Vibrio cholerae 01, biovar cholerae",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A001,"Cholera due to Vibrio cholerae 01, biovar eltor","Cholera due to Vibrio cholerae 01, biovar eltor",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A009,"Cholera, unspecified","Cholera, unspecified",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0100,"Typhoid fever, unspecified","Typhoid fever, unspecified",0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0101,Typhoid meningitis,Typhoid meningitis,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0102,Typhoid fever with heart involvement,Typhoid fever with heart involvement,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0103,Typhoid pneumonia,Typhoid pneumonia,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0104,Typhoid arthritis,Typhoid arthritis,0%,0%,0%,0%,0%,0%,0%,0%,100% | |
A0105,Typhoid osteomyelitis,Typhoid osteomyelitis,0%,0%,0%,0%,0%,0%,0%,0%,100% |
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###--- | |
### Sample Data Preparation | |
###--- | |
#install.packages("dplyr") | |
#install.packages("readr") | |
library(dplyr) | |
library(readr) | |
# read dataset |
El enunciado pide hacer una gráfica en GNUPLOT desde C. Una solución viable es usar popen para abrir y cerrar gnuplot.
Acá pueden ver una pequeña implementación.
Recuerden: Se quiere comparar el desempeño de los algoritmos desarrollados en 1a,b,c en una visualización estática. Para esto sugiero pensar en series de tiempo. Cuál es la variable tiempo para medir el desempeño de un algoritmo?
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Process: Mailbox (Beta) [855] | |
Path: /Applications/Mailbox (Beta).app/Contents/MacOS/Mailbox (Beta) | |
Identifier: com.dropbox.mbd.external-beta | |
Version: 0.3.14 (0.3.14) | |
Code Type: X86-64 (Native) | |
Parent Process: ??? [1] | |
Responsible: Mailbox (Beta) [855] | |
User ID: 501 | |
Date/Time: 2015-02-11 21:47:43.649 -0500 |
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Verifying that +spsaaibi is my Bitcoin username. You can send me #bitcoin here: https://onename.io/spsaaibi |
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## transform an arbitrary 'wide' data.frame into a 'long' data.frame. | |
# load packages | |
library(reshape) | |
# sample wide data.frame | |
wide.df <- data.frame(Code = c("PPP001","PPP002"), | |
Country = c("ESP","FRA"), January2012 = c(110,50), February2012 = c(40,55), | |
March2012 = c(56,32)) |
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### Keybase proof | |
I hereby claim: | |
* I am spsaaibi on github. | |
* I am spsaaibi (https://keybase.io/spsaaibi) on keybase. | |
* I have a public key whose fingerprint is 9FB7 FD7C 81DA 0E26 3C90 71E6 58DB F7CE D441 4223 | |
To claim this, I am signing this object: |
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