R-Python-Matlab (Basics)
A brief cheatsheet for those who use R daily, and use other script programing languages, Python and Matlab, occasionally.
Contents
- Arithmetic Operators
- Basic function
- Function
- Round
- Trigonometry
- Logical Operators
- Data structure
- Data frame
- Finding
- Missing
- Set operator
- Conditional operator
- Loop
- Summary statistics
- Random Number
- Sequences
- Repeating
- Working directory
Arithmetic Operators
| R | Python | Matlab | Description |
|---|---|---|---|
| x<-c x=c |
x=c | x=c | define x and assign c to it |
| x+y | x+y | x+y | addition |
| x-y | x-y | x-y | subtraction |
| x*y | x*y | x*y | multiplication |
| x/y | x/y | x/y | division |
| x^y | x**y | x.^y | power |
| x%/%y | x%y | rem(x,y) | Reminder |
Basic function
| R | Python | Matlab | Description |
|---|---|---|---|
| sqrt(x) | math.sqrt(x) | sqrt(x) | square root |
| log(x) | math.log(x) | log(x) | logarithm base e |
| log10(x) | math.log10(x) | log10() | logarithm base 10 |
| exp(x) | math.exp(x) | exp(x) |
Function
| R | Python | Matlab | Description |
|---|---|---|---|
| name<-function(arguments){ script return(output) } |
def name (arguments): script return output |
function [returns]=name(argument): script returns=output |
Round
| R | Python | Matlab | Description |
|---|---|---|---|
| round() | round() | round() | round |
| ceil() | math.ceil() | ceil() | round up |
| floor() | math.floor() | floor() | round down |
Trigonometry
| R | Python | Matlab | Description |
|---|---|---|---|
| sin(x) | math.sin(x) | sin(x) | |
| asin(x) | math.asin(x) | asin(x) |
Logical Operators
| R | Python | Matlab | Description |
|---|---|---|---|
| FALSE | False | false | |
| TRUE | True | true | |
| a & b | a & b | a & b | AND |
| a|b | a|b | a|b | OR |
| !a | not a | ~a | Not |
| xor(a,b) | a!=b | xor(a,b) | Logical exclusive OR |
| x&&y | and | x&&y | Short-circuit FALSE |
| || | or | || | Short-circuit TRUE |
| any(x,y) | any([x,y]) | any(x,y) | TRUE if any element is TRUE |
| all(a,b) | all([x,y]) | all(x,y) | TRUE if all element is TRUE |
Data structure
| R | Python | Matlab | Description |
|---|---|---|---|
| vec=c(x,y,z) | vec=np.array([[x, y, z]]) | vec=[x y z] | vector |
| vec[i] | vec[i] | cev(i) | call the ith element |
| t(c(x,y,z)) | np.array([[x, y, z]]).T | [x y z]’ | transpose of vector |
| mat=matrix(c(x,y,z,w),ncol=2) | mat=np.array([[x, y], [z,w]]) | mat=[x y, z w] | matrix |
| matrix(0,x,y) | zeros(x,y) | zeros(x,y) | Zero x*y matrix |
| dim(mat) | mat.shape | size(mat) | size of matrix |
| diag(x) | np.diag(x) | diag(x) | diagonal matrix |
| mat[i,] | mat[i-1,] | mat(i,:) | call the ith row |
| mat[,j] | mat[,j-1] | mat(:,j) | call the ith column |
| rbind(mat1,mat2) | np.concatenate(mat1,mat2,axis=0) | [mat1;mat2] | combine by row |
| cbind(mat1,mat2) | np.concatenate(mat1,mat2,axis=1) | [mat1,mat2] | combine by column |
Data frame
| R | Python | Matlab | Description |
|---|---|---|---|
| df=data.frame() | df=pd.DataFrame() | ds = mat2dataset(X) | |
| apply(df, 2, FUN) | df.apply(FUN, axis=1) | varfun(FUN,ds) | Run function on columns |
| apply(df, 1, FUN) | df.apply(FUN, axis=0) | varfun(FUN,ds) | Run function on rows |
df = pd.DataFrame([[4, 4], [5, 5]])
df.apply(lambda x: x.mean(), axis=0)
df.apply(lambda x: x.mean(), axis=1)
Finding
| R | Python | Matlab | Description |
|---|---|---|---|
| which(x==a) | np.where(x == a) | find(x == a) | Check the condition |
| which.max(x) | np.where(x==np.max(x)) | find(x == max(x)) | Find maximum |
| which.min(x) | np.where(x==np.min(x)) | find(x == min(x)) | Find minimum |
Missing
| R | Python | Matlab | Description | |
|---|---|---|---|---|
| NA | np.nan | NaN | Missing | |
| NaN | np.nan | NaN | Not a number | |
| Inf | ‘inf’ | Inf | infinity | |
| is.na(x) | np.isnan(x) | isnan(x) | Test whether it na | |
| anyNA(X) | x.isnull().any().any() | sum(isnan(x)>1 | Test whether there is any na |
Set operator
| R | Python | Matlab | Description | |
|---|---|---|---|---|
| unique(x) | np.unique(x) | unique(x) | find unique value | |
| intersect(x,y) | x.intersectionf(y) | intersect(x,y) | find itersect value | |
| setdiff(x,y) | x-y | setdiff(x,y) | difference of set | |
| see below | x.symmetric_difference(y) | setxor(x,y) | set exclusion | |
| is.element(c,x) c%in%x |
np.isin(c,x) | ismemner(c,x) | True if x includes c |
setxor <- function(x,y) setdiff(union(x,y), intersect(x,y))
Conditional operator
| R | Python | Matlab | Description |
|---|---|---|---|
| if (condition){ dd } |
if condition : codes |
if condition code end |
|
| ifelse | elif | elseif | |
| else | else | else |
loop
| R | Python | Matlab | Description |
|---|---|---|---|
| for (i in indices){ codes } |
for i in indices: codes |
for i=indices codes end |
Summary statistics
| R | Python | Matlab | Description |
|---|---|---|---|
| mean(x) | np.mean(x) | mean(x) | |
| median(x) | np.median(x) | median(x) | calculate sample mdeian |
| var(x) | np.var(x) | var(x) | |
| sd(x) | np.std(x) | std(x) | |
| cov(x,y) | np.cov(x,y) | cov(x,y) | |
| corr(x,y) | np.corrcoef(x,y) | corr(x,y) |
Random number
| R | Python | Matlab | Description |
|---|---|---|---|
| runif(n,a,b) | np.random.uniform(a,b,n) | unifrnd(a,b,1,n) | |
| rnorm(n,a,b) | np.random.normal(a,b,n) | normrnd(a,b,1,n) |
Sequences
| R | Python | Matlab | Description |
|---|---|---|---|
| seq(a,b,by=c) | np.arange(a,b,c) | a:c:b | |
| seq(a,b,length.out=c) | np.linspace(a,b,c) | linspace(a,b,c) |
Repeating
| R | Python | Matlab | Description |
|---|---|---|---|
| rep(a,n) | np.repeat(a,n) | repmat(a,1,n) | |
| a:b | a:b | a:b |
Working directory
R | Python | Matlab|Description ——- | ——-| ——-| ——- dir()| os.dir(“.”) |dir | list files and folders getwd|os.getwcd() | pwd | Display the current working directory setwd|os.chdir(“folder”) | cd folder | Change the current working directory ls()| dir() | who | list of loaded objects rm(x)| del x| clear x | clear object x from memory rm(list = ls())| see below|clear all | clear all objects from memory
for obj in dir():
if obj[0] == '_': continue
del globals()[obj]
Needed Python library
import math
import numpy as np
import pandas as pd
More useful link:
License
Copyright (c) 2018 Saeid Amiri
