python - 将python中的RDa文件作为 Pandas 数据框读取

Question

我有一个在 R 中创建的 RDa 文件。我想在 python 上将此文件作为 pandas 数据帧读取。我有以下代码来做同样的事情:

import rpy2.robjects as robjects
import numpy as np
from rpy2.robjects import pandas2ri
pandas2ri.activate()

# load your file
robjects.r['load']('Data.RDa')

matrix = robjects.r['data']

matrix

我得到以下结果:

R object with classes: ('data.frame',) mapped to:
<DataFrame - Python:0x0CF46F58 / R:0x0ED0F200>
[Float..., Float..., Float..., ..., Float..., Float..., Float...]
  area: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0CF56A80 / R:0x0F281898>
[NA_real_, NA_real_, NA_real_, ..., NA_real_, NA_real_, NA_real_]
  i: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0CF68E68 / R:0x0F2B9520>
[NA_real_, NA_real_, NA_real_, ..., NA_real_, NA_real_, NA_real_]
  s: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0CF68940 / R:0x0F380008>
[NA_real_, NA_real_, NA_real_, ..., NA_real_, NA_real_, NA_real_]
  ...
  upslope_area: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0D03FDA0 / R:0x0FE87C90>
[NA_real_, NA_real_, NA_real_, ..., 292.256494, NA_real_, NA_real_]
  i: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0D03FC88 / R:0x0FEBF918>
[331347.500000, 331352.500000, 331357.500000, ..., 332187.500000, 332192.500000, 332197.500000]
  s: <class 'rpy2.robjects.vectors.FloatVector'>
  R object with classes: ('numeric',) mapped to:
<FloatVector - Python:0x0D03FE68 / R:0x0FEF75A0>
[4554812.500000, 4554812.500000, 4554812.500000, ..., 4553982.500000, 4553982.500000, 4553982.500000]

如何将其转换为 pandas 数据框？

Answer 1

从搜索路径中检索带有符号“数据”的第一个 R 对象时，这看起来像是对当前转换的缺失调用(简而言之，在执行 robjects.r["data"] 时).如果还没有问题，请在 rpy2 跟踪器上打开一个问题，或者如果未解决或假设过早解决，请在已经打开的问题的评论中发出声音。

显式调用仅限于代码块的转换规则应该是一个简单的解决方法，并且可能有助于确保良好的性能。转换机制提供了便利，但通常以牺牲性能为代价，因为每次在转换进行的任一方向上都会制作数据帧的副本。

下面是这样的:

from rpy2.robjects import default_converter
from rpy2.robjects import pandas2ri
from rpy2.robjects.conversion import localconverter

# use the default conversion rules to which the pandas conversion
# is added
with localconverter(default_converter + pandas2ri.converter) as cv:
    dataf = robjects.r["data"]

这是在文档中:http://rpy2.readthedocs.io/en/version_2.8.x/robjects_convert.html#local-conversion-rules