Python programming | Pandas - DTU
Python programming ¡ª Pandas
Finn A?rup Nielsen
DTU Compute
Technical University of Denmark
October 5, 2013
Pandas
Overview
Pandas?
Reading data
Summary statistics
Indexing
Merging, joining
Group-by and cross-tabulation
Statistical modeling
Finn A?rup Nielsen
1
October 5, 2013
Pandas
Pandas?
¡°Python Data Analysis Library¡±
Young library for data analysis
Developed from
Main author Wes McKinney has written a 2012 book (McKinney, 2012).
Finn A?rup Nielsen
2
October 5, 2013
Pandas
Why Pandas?
A better Numpy: keep track of variable names, better indexing, easier
linear modeling.
A better R: Access to more general programming language.
Why not pandas?
R: Still primary language for statisticians, means most avanced tools are
there.
NaN/NA (Not a number/Not available)
Support to third-party algorithms compared to Numpy? Numexpr? (NumExpr in 0.11)
Finn A?rup Nielsen
3
October 5, 2013
Pandas
Get some data from R
Get a standard dataset, Pima, from R:
$ R
> library(MASS)
> write.csv(Pima.te, "pima.csv")
pima.csv now contains comma-separated values:
"","npreg","glu","bp","skin","bmi","ped","age","type"
"1",6,148,72,35,33.6,0.627,50,"Yes"
"2",1,85,66,29,26.6,0.351,31,"No"
"3",1,89,66,23,28.1,0.167,21,"No"
"4",3,78,50,32,31,0.248,26,"Yes"
"5",2,197,70,45,30.5,0.158,53,"Yes"
"6",5,166,72,19,25.8,0.587,51,"Yes"
Finn A?rup Nielsen
4
October 5, 2013
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