python3调用R语言干货

R语言知识：https://www.w3cschool.cn/r/r_lists.html

1. 安装库rpy2

1. 下载与本地对应python版本模块，pip install rpy2是安装不上的

下载地址是：http://www.lfd.uci.edu/~gohlke/pythonlibs/#rpy2  这是python下包的专用地址
需要下载版本和平台都相对应的whl包，我下的是rpy2-2.9.4-cp36-cp36m-win32.whl

 pip install rpy2-2.9.4-cp36-cp36m-win32.whl安装即可。

如果还不行，参考：https://www.cnblogs.com/caiyishuai/p/9520214.html

2. 安装broom --》R语言的一个库--》与R脚本有关，可以忽略

install.packages('broom')

3. 写R脚本

library(broom)

test <- function() {
  # x <- c(1:1200000)
  # y <- c(1:1200000)
  x <- c(151, 174, 138, 186, 128, 136, 179, 163, 152, 131)
  y <- c(63, 81, 56, 91, 47, 57, 76, 72, 62, 48)
  
  relation <- lm(y ~ x)
  data <- summary(relation)
  
  data_dict <- c()
  
  newData <- c(data)
  data_dict["residuals"] <- newData["residuals"]
  data_dict["coefficients"] = newData["coefficients"]
  data_dict["aliased"] = newData["aliased"]
  data_dict["sigma"] = newData["sigma"]
  data_dict["df"] = newData["df"]
  data_dict["r.squared"] = newData["r.squared"]
  data_dict["adj.r.squared"] = newData["adj.r.squared"]
  data_dict["fstatistic"] = newData["fstatistic"]
  data_dict["cov.unscaled"] = newData["cov.unscaled"]
  data_dict["p.value"] = c(broom::glance(data))["p.value"]
  
  return(data_dict)
}


# result <- test()
# print(result)

4. 写python脚本

报错： RuntimeError: R_USER not defined.

解决方案，各种搜索都是环境变量的问题，于是我各种加

还tm不行..........................................又懒得重启

stackflow找到答案

os模块的运用，直接看脚本

import os
os.environ['R_HOME'] = r'C:\Program Files\R\R-3.6.0'
os.environ['R_USER'] = r'C:\python3.6.3\Lib\site-packages\rpy2' #path depe

import rpy2.robjects as robjects   # ----------------------------------------------> 一定要注意这句，不能放到最上面，因为要先添加环境变量，才能找到这个rpy2。一定要注意
robjects.r.source(r'C:\code\r_test\test_one\test.R')
a = robjects.r('test()')
print(type(a))
# print(list(a))
from pandas import DataFrame
print(a[0])
print(a[0][0])

打印结果，以及转换数据类型，参考：http://rpy.sourceforge.net/rpy2/doc-2.2/html/vector.html#creating-vectors https://blog.csdn.net/suzyu12345/article/details/50587267

5. python传值给R脚本，如何实现，形参方法1

R脚本：这个脚本的关键在于如何将list转换为c

library(broom)

test <- function(list_data) {
  # print(list_data)
  # print(class(list_data))
  # r语言list 转换成 vector: v = as.vector(unlist(你的list))
  x = c(as.vector(unlist(list_data['x'])))
  y = c(as.vector(unlist(list_data['y'])))

  
  relation <- lm(y ~ x)
  data <- summary(relation)
  print(data)

  return(0)
}

python脚本

import os

os.environ['R_HOME'] = r'C:\Program Files\R\R-3.6.0'
os.environ['R_USER'] = r'C:\python3.6.3\Lib\site-packages\rpy2' #path depe

from pandas import DataFrame as df
import rpy2.robjects as robjects
import time
robjects.r.source(r'C:\code\r_test\test_one\test.R')

time1 = time.time()

y =  robjects.ListVector({
    "x":[1, 2, 3],
    "y":[1, 2, 3], # 这里可以给float

    })
a = robjects.r["test"](y)

6. python传值给R脚本，如何实现，形参方法2：类似python的args

R语言脚本

library(broom)

test <- function(...) {
  list_data <- list(...) # 类似python的args，可以传递多个参数
  print(list_data)
  print(class(list_data))
  x = c(as.vector(unlist(list_data[1]))) # 注意R是从1开始的
  y = c(as.vector(unlist(list_data[2])))
  print(x)
  print(y)


  
  relation <- lm(y ~ x)
  data <- summary(relation)
  print(data)

  return(0)
}

python语言

import os

os.environ['R_HOME'] = r'C:\Program Files\R\R-3.6.0'
os.environ['R_USER'] = r'C:\python3.6.3\Lib\site-packages\rpy2' #path depe

from pandas import DataFrame as df
import rpy2.robjects as robjects
import time
robjects.r.source(r'C:\code\r_test\test_one\test.R')

x =  robjects.IntVector([151, 174, 138, 186, 128, 136, 179, 163, 152, 131])
y =  robjects.IntVector([63, 81, 56, 91, 47, 57, 76, 72, 62, 48])

a = robjects.r["test"](x, y)

来源：oschina

链接：https://my.oschina.net/u/4339883/blog/3479029

标签

rpy