读取csv格式数据

数据来源是西南财经大学 司亚卿 老师的课程作业

方法一:read.csv()函数

 file.choose()
read.csv("C:\\Users\\Administrator\\Desktop\\Astocks.csv",
head=T,sep=',',nrows = ,stringsAsFactors = FALSE)
结果

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alt="" />

file.choose():读入该文件,这样我们知道该文件的具体路径。

file参数:        路径和文件名,windows下用的是反斜杠\\

head=T:       是首行问题,T表明文件有标题,将文件中的第一行作为列名。若head=F,则原来文件没有

标题,增加一行V1,V2,...作为文件的第一行,即作为列名。read.csv()函数默认为head=T。

sep=“,”:       分隔符问题,这里分隔符的选择会影响输入的被引用的字符串。

nrows=200: 行数问题,表明读取该文件的前200行。

stringsAsFactors = FALSE :   字符型数据读入时自动转换为因子,防止转换为因子,

令参数stringsAsFactors = FALSE,  防止导入的数据任何因子的转换。

还有一个参数:fileEncoding='utf-8',在win下一般不用设置,但是在Linux下若出现乱码问题,基本上就是要加上这个参数。就这个文件而言加上这个会报错,应该是fileEncoding='GBK',这样才能正常运行。这里涉及到字符集的问题。

方法二:read.table()函数

 a<-read.table('C:\\Users\\Administrator\\Desktop\\Astocks.csv',
head=T,sep=',',nrows = ,stringsAsFactors = FALSE )
a
 a[:,:]

结果

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" alt="" />

切片:选取行数和列数(选取1到3行和1到3列)

aaarticlea/png;base64,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" 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也可以进行这样读取:

 a<-read.table(file.choose(),header = T,sep = ',',nrows = )
a

结果:

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