Introductionto R

Factor

• Factor 可以把向量Vector轉換成因子
• 可以沒有order，比如動物種類，我們不能說猴子比大象高階；也可以有order，比如氣溫高低，顯然是有順序的

factor_temperature_vector <- factor(temperature_vector, order = TRUE, levels = c("Low", "Medium", "High"))

• Factor Levels

levels(factor_survey_vector) <- c("Female", "Male")
 

順序很重要，原來的Level順序是"F","M",一定要對應

• 用Summary來觀察結果

# Generate summary for survey_vector 這裡是向量
summary(survey_vector)
   Length     Class      Mode 
        5 character character 
# Generate summary for factor_survey_vector 這裡是因子
summary(factor_survey_vector)
Female   Male 
     2      3
 

• Ordered factors

# Create factor_speed_vector
speed_vector <- c("medium", "slow", "slow", "medium", "fast")
factor_speed_vector <- factor(speed_vector, ordered = TRUE, levels = c("slow", "medium", "fast"))#在這裡設定的level是從小到大的順序
# Factor value for second data analyst
da2 <- factor_speed_vector[2]
# Factor value for fifth data analyst
da5 <-factor_speed_vector[5]
# Is data analyst 2 faster than data analyst 5? FALSE=No
da2>da5
[1] FALSE
 

可以比較大小

Have a look at the structure

The functionstr()shows you the structure of your data set. Applying thestr()function will often be the first thing that you do when receiving a new data set or data frame. It is a great way to get more insight in your data set before diving into the real analysis.

For a data frame it tells you:

• The total number of observations (e.g. 32 car types)
• The total number of variables (e.g. 11 car features)
• A full list of the variables names (e.g.mpg,cyl… )
• The data type of each variable (e.g.num)
• The first observations

# Investigate the structure of mtcars
str(mtcars)
'data.frame':	32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

Daraframe

選擇Dataframe中元素的方法

用[1，2]選擇第一行第二列，或者[1,"列的名字"]

# Select first 5 values of diameter column
planets_df[1:5,'diameter']
[1]  0.382  0.949  1.000  0.532 11.209

用$直接選擇一列

# Select the rings variable from planets_df
rings_vector <- planets_df$rings
  
# Print out rings_vector
rings_vector
[1] FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE

# Select planets with diameter < 1
subset(planets_df,subset = diameter<1)
     name               type diameter rotation rings
1 Mercury Terrestrial planet    0.382    58.64 FALSE
2   Venus Terrestrial planet    0.949  -243.02 FALSE
4    Mars Terrestrial planet    0.532     1.03 FALSE
>

List

# Adapt list() call to give the components names
my_list <- list(my_vector, my_matrix, my_df)
names(my_list) = c('vec','mat','df')

How to construct and name lists.

# Finish the code to build shining_list
shining_list <- list(moviename = mov, actors = act, reviews = rev)

Selecting elements from a list

Your list will often be built out of numerous elements and components. Therefore, getting a single element, multiple elements, or a component out of it is not always straightforward.

One way to select a component is using the numbered position of that component. For example, to "grab" the first component ofshining_listyou type

shining_list[[1]]

A quick way to check this out is typing it in the console. Important to remember: to select elements from vectors, you use single square brackets:[ ]. Don't mix them up!

You can also refer to the names of the components, with[[ ]]or with the$sign. Both will select the data frame representing the reviews:

shining_list[["reviews"]]
shining_list$reviews

Besides selecting components, you often need to select specific elements out of these components. For example, withshining_list[[2]][1]you select from the second component,actors(shining_list[[2]]), the first element ([1]). When you type this in the console, you will see the answer is Jack Nicholson.