在使用read.csv
读取数据时,可以使用skip = 1
来避免此问题。我从原始数据中抓取了几行,看起来没问题。
第一行是不必要的,它实际上会将标题行向下推入第一行,然后在读取时将列转换为因子。当您使用as.numeric
时,实际上是将所有因子值更改为其数值,这些数值与原始数值不同,并且可能不正确。这是你描述的“歪斜”。
txt <- '506,13,,,,,,,,,,,,
"CRIM","ZN","INDUS","CHAS","NOX","RM","AGE","DIS","RAD","TAX","PTRATIO","B","LSTAT","MEDV"
0.00632,18,2.31,0,0.538,6.575,65.2,4.09,1,296,15.3,396.9,4.98,24
0.02731,0,7.07,0,0.469,6.421,78.9,4.9671,2,242,17.8,396.9,9.14,21.6
0.02729,0,7.07,0,0.469,7.185,61.1,4.9671,2,242,17.8,392.83,4.03,34.7
0.03237,0,2.18,0,0.458,6.998,45.8,6.0622,3,222,18.7,394.63,2.94,33.4'
您当前的呼叫产生的因素:
sapply(read.csv(text = txt), class)
# X506 X13 X X.1 X.2 X.3 X.4
# "factor" "factor" "factor" "factor" "factor" "factor" "factor"
# X.5 X.6 X.7 X.8 X.9 X.10 X.11
# "factor" "factor" "factor" "factor" "factor" "factor" "factor"
skip = 1
似乎这样的伎俩,因为它产生的数字列:如果你改变你的第一线,
sapply(read.csv(text = txt, skip = 1), class)
# CRIM ZN INDUS CHAS NOX RM AGE
# "numeric" "integer" "numeric" "integer" "numeric" "numeric" "numeric"
# DIS RAD TAX PTRATIO B LSTAT MEDV
# "numeric" "integer" "integer" "numeric" "numeric" "numeric" "numeric"
所以
y <- read.csv("boston_house_prices.csv", skip = 1)
一切都应该罚款之后,没有其他必要的转换
这并不是那么明显。它虽然现在工作!这个文件在哪里?我查看了http://cran.r-project.org/doc/manuals/R-data.html,找不到更多的跳过参数。 – leonard 2014-09-28 04:15:55
那么这是一个Python包,所以我不希望这发生在R github数据集上。 'skip'记录在'?read.table'文件中,实际上整个帮助文件是非常有用的 – 2014-09-28 04:18:02