在读入excel和csv的数据的时候总是回碰到小数点的问题,不能正确的显示。早就该弃用 read.csv这个函数。
现在来介绍两个比较好的读入数据的包,Hadley出品 ——readxl&readr
测试数据:
函数介绍:
readxl::read_excel("test.xlsx",col_names = F,col_types = rep("numeric",3))
col_types一共有四种模式可选: "blank", "numeric", "date" or "text"。blank就是skip这一列,其他的三个都很好理解。
vignette("column-types") #参考这里的文档
readr::read_csv("test.csv",col_names = F,col_types = cols(X1="d",X2=col_skip(),X3="d"))
这里的col_types 更为丰富,
col_logical()[l], containing onlyT,F,TRUEorFALSE.col_integer()[i], integers.col_double()[d], doubles.col_character()[c], everything else.col_date(format = "")[D]: Y-m-d dates.col_datetime(format = "")[T]: ISO8601 date timescol_number()[n], finds the first number in the field. A number is defined
as a sequence of -, "0-9",decimal_markandgrouping_mark. This is useful for currencies and percentages.
decimal_mark这个是在locale()里面设置的,具体见帮助文档vignette("locales").
You can also manually specify other column types:
col_skip()[ _, -], don't import this column.col_date(format), dates with given format.col_datetime(format, tz), date times with given format. If the timezone is UTC (the default), this is >20x faster than loading then parsing withstrptime().col_time(format), times. Returned as number of seconds past midnight.col_factor(levels, ordered), parse a fixed set of known values into a factor
例子
read_csv("iris.csv", col_types = cols(
Sepal.Length = "d",
Sepal.Width = "d",
Petal.Length = "d",
Petal.Width = "d",
Species = col_factor(c("setosa", "versicolor", "virginica"))
))
读入数据后,我们往往会碰到这样的东西
a$X3
[1] 3.000000e-06 1.237595e+06
解决办法:
formattable::digits(a$X3,7)
[1] 0.0000030 1237594.5455460
这个formattable包 还有很多的用途,详情见:http://renkun.me/formattable/
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