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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:
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 only T, F, TRUE or FALSE.

  • 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 times

  • col_number() [n], finds the first number in the field. A number is defined
    as a sequence of -, "0-9", decimal_mark and grouping_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 with strptime().

  • 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/


BruceZhaoR
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数据攻城狮


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