R語言中因子相關知識點詳解
因子是用于對數據進行分類并將其存儲為級別的數據對象。 它們可以存儲字符串和整數。 它們在具有有限數量的唯一值的列中很有用。 像“男性”,“女性”和True,False等。它們在統(tǒng)計建模的數據分析中很有用。
使用factor()函數通過將向量作為輸入創(chuàng)建因子。
例
# Create a vector as input.
data <- c("East","West","East","North","North","East","West","West","West","East","North")
print(data)
print(is.factor(data))
# Apply the factor function.
factor_data <- factor(data)
print(factor_data)
print(is.factor(factor_data))
當我們執(zhí)行上面的代碼,它產生以下結果 -
[1] "East" "West" "East" "North" "North" "East" "West" "West" "West" "East" "North" [1] FALSE [1] East West East North North East West West West East North Levels: East North West [1] TRUE
數據幀的因子
在創(chuàng)建具有文本數據列的任何數據框時,R語言將文本列視為分類數據并在其上創(chuàng)建因子。
# Create the vectors for data frame.
height <- c(132,151,162,139,166,147,122)
weight <- c(48,49,66,53,67,52,40)
gender <- c("male","male","female","female","male","female","male")
# Create the data frame.
input_data <- data.frame(height,weight,gender)
print(input_data)
# Test if the gender column is a factor.
print(is.factor(input_data$gender))
# Print the gender column so see the levels.
print(input_data$gender)
當我們執(zhí)行上面的代碼,它產生以下結果 -
height weight gender 1 132 48 male 2 151 49 male 3 162 66 female 4 139 53 female 5 166 67 male 6 147 52 female 7 122 40 male [1] TRUE [1] male male female female male female male Levels: female male
更改級別順序
可以通過使用新的等級次序再次應用因子函數來改變因子中的等級的順序。
data <- c("East","West","East","North","North","East","West","West","West","East","North")
# Create the factors
factor_data <- factor(data)
print(factor_data)
# Apply the factor function with required order of the level.
new_order_data <- factor(factor_data,levels = c("East","West","North"))
print(new_order_data)
當我們執(zhí)行上面的代碼,它產生以下結果 -
[1] East West East North North East West West West East North Levels: East North West [1] East West East North North East West West West East North Levels: East West North
生成因子級別
我們可以使用gl()函數生成因子級別。 它需要兩個整數作為輸入,指示每個級別有多少級別和多少次。
語法
gl(n, k, labels)
以下是所使用的參數的說明 -
- n是給出級數的整數。
- k是給出復制數目的整數。
- labels是所得因子水平的標簽向量。
例
v <- gl(3, 4, labels = c("Tampa", "Seattle","Boston"))
print(v)
當我們執(zhí)行上面的代碼,它產生以下結果 -
Tampa Tampa Tampa Tampa Seattle Seattle Seattle Seattle Boston [10] Boston Boston Boston Levels: Tampa Seattle Boston
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