R odds and ends R basics
| Description | R | Comments | Python |
|---|---|---|---|
| exam type | class() | type() | |
| vector | c(...) | one-dimension arrays same type | |
| name vector | names(vect)<-c(...) | ||
| slicing vector | vect[3] vect[c(3,5,6)] | starting from 1 compares to 0 in Python | |
| 2:5 | !ERROR! unexpected operator '=' | includes 5 | |
| vect[3:5] | !ERROR! illegal character '[' | ||
| use names as index | vec[c('name1','name2',...)] | ||
| calculate average | mean() | in Python, have to import other libraries | np.mean() |
| vectors comparison | c(2,3,4,5)>3 | in Python, have to in numpy, pandas | |
| logical selection | vect[c(...)>n] vect[vect2(logical)] | in Python, pandas is common | |
| matrix | matrix() matrix(1:9, byrow = TRUE, nrow = 3) | two-dimensional same data type | np.matrix() |
| Naming a matrix | rownames(my_matrix) <- row_names_vector colnames(my_matrix) <- col_names_vector | ||
| dimnames = list(rowname, columnname) | |||
| Sum of values of each row | rowSums(some_matrix) | ndarray.sum(axis=1) df.sum(axis=1) |
|
| add column(s) to a matrix | bigger<- cbind(matrix1, matrix2, ...) | pd.concat([df1,df2],axis=1) | |
| Adding a row(s) to a matrix | rbind(matrix1, matrix2, ...) | pd.concat([df1,df2],axis=0) df1.append(df2) |
|
| Sum of values of each column | ndarray.sum(axis=0) df.sum(axis=0) |
||
| slicing Matrix | matrix[row,col] my_matrix[1,2] my_matrix[1:3,2:4] my_matrix[ ,1] my_matrix[2, ] | ||
| factors | factor() | categorical | |
| Convert vector to factor | my_factor<-(vector, | ||
| order/ non-order | temp_vector <- c("High", "Low", "High","Low", "Medium") factor_temp_vector <- factor(temp_vector, order = TRUE, levels = c("Low", "Medium", "High")) | nominal categorical variable ordinal categorical variable. | s = pd.Series(["a","b","c","a"], dtype="category") raw_cat = pd.Categorical(["a","b","c","a"], categories=["b","c","d"], .... ordered=False) |
| Factor levels | levels() levels(factor_vector) <- c("name1", "name2",...) | ||
| summary() | summary(my_var) | df.describe() Series.value_counts() |
|
| ordered | factor_speed_vector <-factor(speed_vector,ordered=TRUE,levels=c('slow','fast','insane')) | ordered factor can be compared | |
| data frame | head(df) tail(df) | each column must be same data type | |
| examine structure of a dataframe | str(df) | ||
| create data frame | data.frame(vectors) | ||
| slicing | df[rows,columns] df[row2,] entire row2 df[,column3] entire column3 | ||
| use name slicing | df[2:5, 'name'] df['name', ] df[ ,'name'] | ||
| subset() create | subset(planets_df, diameter<1) == planets_df[planets_df[,'diameter']<1,] | ||
| sorting | order() returns ranked index not values values: a[order(a)] | ||
| sorting df | indexes=order(df$column3) df[indexes, ] | ||
| list | my_list <- list(comp1, comp2 ...) | ||
| Creating a named list | my_list <- list(name1 = your_comp1, name2 = your_comp2) | ||
| same as above | my_list <- list(your_comp1, your_comp2) names(my_list) <- c("name1", "name2") | ||
| selecting elements from a list | shining_list[["reviews"]] == shining_list$reviews | ||
| list[[2]][1] | |||
| add data to list | ext_list <- c(my_list , my_val) | ||
| comparison | & and | or ! not | double sign only compares the first element && || | |
| if syntax in R | if (condition) {do sth} else if (condition) {do sth} else {do sth} | ||
| read data | read.table read.delim read.csv read.csv2 | hotdogs2 <- read.delim("hotdogs.txt", header = FALSE, col.names = c("type", "calories", "sodium"), colClasses = c("factor", "NULL", "numeric")) | |
| check environment | environment(func) | ||
| specify func without a name | function(x){x+1}(2) => 3 | ||
| mean() | mean(c(1:9, NA),trim=0.1,na.rm=TRUE) | trim -> remove outliers | |
| environment | > f<-function () x > x<-99 > f() [1] 99 | ||
| exists() | a<-5 exists("a") TRUE | ||
| vector properties | typeoff() length() | ||
| nun value in R | NULL (absent of entire vector) NA (absent of one value in vector) | ||
| check nun | is.na() | ||
| sequence | seq(1,10) 1:10 | ||
| merge vector | c(vector1, vector2, singlevalue, ...) | ||
| paste() paste0() | paste() sep=" " paste0 sep="" | string.join(list) | |
| paste0("year_", 1:5) | [1] "year_1" "year_2" "year_3" "year_4" "year_5" | ||
| plotting | hist(one_dim_data) hist(df$column) boxplot(multi_dim_data) boxplot(df) | ||