我试图以两种不同的方式从Rpy中的MNP包中复制示例，从rpy2复制。首先，我只是将robjects.r与一个完全复制并粘贴R代码的字符串一起使用：
import rpy2.robjects as robjects
import rpy2.robjects.numpy2ri
import rpy2.robjects.pandas2ri
import rpy2.robjects.packages as rpackages
robjects.pandas2ri.activate()
mnp = rpackages.importr('MNP')
base = rpackages.importr('base')
r = robjects.r
r.data('detergent')
rcmd = '''\
mnp(choice ~ 1, choiceX = list(Surf=SurfPrice, Tide=TidePrice,
Wisk=WiskPrice, EraPlus=EraPlusPrice,
Solo=SoloPrice, All=AllPrice),
cXnames = "price", data = detergent, n.draws = 500, burnin = 100,
thin = 3, verbose = TRUE)'''
res = r(rcmd)
这可以很好地工作，并再现了我可以直接在R中执行的操作。我还想尝试使用python可访问对象运行此代码，并从数据帧中传入数据：
import rpy2.rlike.container as rlc
df = robjects.pandas2ri.ri2py(r['detergent'])
choiceX = rlc.TaggedList(['SurfPrice', 'TidePrice', 'WiskPrice', 'EraPlusPrice', 'SoloPrice', 'AllPrice'],
tags=('Surf', 'Tide', 'Wisk', 'EraPlus', 'Solo', 'All'))
res = mnp.mnp('choice ~ 1',
choiceX=['SurfPrice', 'TidePrice', 'WiskPrice', 'EraPlusPrice', 'SoloPrice', 'AllPrice'],
cXnames='price',
data=df, n_draws=500, burnin=100,
thin=3, verbose=True)
失败并显示以下错误：
Error in xmatrix.mnp(formula, data = eval.parent(data), choiceX = call$choiceX, :
Error: Invalid input for `choiceX.'
You must specify the choice-specific varaibles at least for all non-base categories.
在另一个SO response中建议用rpy2 TaggedList替换R命名列表。如果我删除MNP的
choiceX和cXnames参数（它们是可选的），则代码将运行，因此看起来熊猫数据帧已正确传递。我不确定TaggedList进入R后是否不能正确地解释为命名列表，或者MNP不能将
choiceX的内容与熊猫数据帧相关联而出现问题。有人对这里可能发生的事情有想法吗？
更新资料
按照@lgautier的建议，我将代码修改为：
choiceX = rlc.TaggedList([base.as_symbol('SurfPrice'), base.as_symbol('TidePrice'),
base.as_symbol('WiskPrice'), base.as_symbol('EraPlusPrice'),
base.as_symbol('SoloPrice'), base.as_symbol('AllPrice')],
tags=('Surf', 'Tide', 'Wisk', 'EraPlus', 'Solo', 'All'))
res = mnp.mnp(robjects.Formula('choice ~ 1'),
choiceX=choiceX,
cXnames='price',
data=df, n_draws=500, burnin=100,
thin=3, verbose=True)
但是，我得到了与以前发布的相同的错误。
更新2
按照@lgautier建议的解决方法，执行以下代码：
choiceX = rlc.TaggedList([base.as_symbol('SurfPrice'),
base.as_symbol('TidePrice'),
base.as_symbol('WiskPrice'),
base.as_symbol('EraPlusPrice'),
base.as_symbol('SoloPrice'),
base.as_symbol('AllPrice')],
tags=('Surf', 'Tide', 'Wisk',
'EraPlus', 'Solo', 'All'))
choiceX = robjects.conversion.py2ro(choiceX)
# add the names
choiceX.names = robjects.vectors.StrVector(('Surf', 'Tide',
'Wisk', 'EraPlus',
'Solo', 'All'))
res = mnp.mnp(robjects.Formula('choice ~ 1'),
choiceX=choiceX,
cXnames='price',
data=df, n_draws=500, burnin=100,
thin=3, verbose=True)
仍然会产生错误（尽管有所不同）：
Error in as.vector(x, mode) :
cannot coerce type 'symbol' to vector of type 'any'
---------------------------------------------------------------------------
RRuntimeError Traceback (most recent call last)
<ipython-input-21-7de5ad805801> in <module>()
3 cXnames='price',
4 data=df, n_draws=500, burnin=100,
----> 5 thin=3, verbose=True)
/Users/lev/anaconda/envs/rmnptest/lib/python2.7/site-packages/rpy2-2.5.6-py2.7-macosx-10.5-x86_64.egg/rpy2/robjects/functions.pyc in __call__(self, *args, **kwargs)
168 v = kwargs.pop(k)
169 kwargs[r_k] = v
--> 170 return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
171
172 pattern_link = re.compile(r'\\link\{(.+?)\}')
/Users/lev/anaconda/envs/rmnptest/lib/python2.7/site-packages/rpy2-2.5.6-py2.7-macosx-10.5-x86_64.egg/rpy2/robjects/functions.pyc in __call__(self, *args, **kwargs)
98 for k, v in kwargs.items():
99 new_kwargs[k] = conversion.py2ri(v)
--> 100 res = super(Function, self).__call__(*new_args, **new_kwargs)
101 res = conversion.ri2ro(res)
102 return res
RRuntimeError: Error in as.vector(x, mode) :
cannot coerce type 'symbol' to vector of type 'any'
最佳答案
Python代码与您的R不对应。自发布以来就已经弄清楚了，因此请在下面提供详细信息。总结是R符号和Python字符串不是等效的（尽管R通过在某些地方允许两者使用（例如，library("MNP")和library(MNP)都可以使用）混淆了自己的用户。
这与以下问题没什么不同：pandas and rpy2: Why does ezANOVA work via robjects.r but not robjects.packages.importr?
...除了choiceX是未经评估的R表达式，而不仅仅是符号。
R代码是：
data(detergent)
mnp(choice ~ 1,
# ^- this is a "formula", which is an expression in R
choiceX = list(Surf=SurfPrice, Tide=TidePrice,
Wisk=WiskPrice, EraPlus=EraPlusPrice,
Solo=SoloPrice, All=AllPrice),
# ^- this is a list of objects, but with the cautionary note
# that R evaluates expressions in argument lazily. Therefore
# the safest is to have it as an R expression (it may or may
# not work if evaluated, but this depends on the code in
# `mnp`)
cXnames = "price",
# ^- this is a string
data = detergent,
n.draws = 500, burnin = 100,
thin = 3, verbose = TRUE)
您拥有的Python（带有有关差异的注释）：
choiceX = rlc.TaggedList(['SurfPrice', 'TidePrice', 'WiskPrice',
'EraPlusPrice', 'SoloPrice', 'AllPrice'],
tags=('Surf', 'Tide', 'Wisk',
'EraPlus', 'Solo', 'All'))
# ^- this is a "tagged list", and the R equivalent would be
# list(Surf="SurfPrice", Tide="TidePrice", Wisk="WiskPrice",
# EraPlus="EraPlusPrice", Solo="SoloPrice", All="AllPrice")
# Something closer to your R code above would be:
# rlc.TaggedList([as_symbol('SurfPrice'), as_symbol('TidePrice'),
# ...
# tags=('Surf', 'Tide', ...))
res = mnp.mnp('choice ~ 1',
# ^- this is a string. To make it an R formula, do
# robjects.Formula('choice ~ 1')
choiceX=['SurfPrice', 'TidePrice', 'WiskPrice',
'EraPlusPrice', 'SoloPrice', 'AllPrice'],
# ^- this should be choiceX defined above, I guess
cXnames='price',
# ^- this is a string, like in R
data=df,
n_draws=500, burnin=100,
thin=3, verbose=True)
编辑：
现在这意味着以下应该起作用
choiceX = robjects.rinterface.parse("""
list(Surf=SurfPrice, Tide=TidePrice,
Wisk=WiskPrice, EraPlus=EraPlusPrice,
Solo=SoloPrice, All=AllPrice)""")
当前
rpy2尚未提供许多用于构造R表达式的实用程序。如果变量名称是Python级别的参数您可以考虑以下内容：
rcode = 'list('+''.join('%s=%s' % (k,v) \
for k,v in \
(('Surf','SurfPrice'),
('Tide', 'TidePrice'),
('Wisk','WiskPrice'),
('EraPlus','EraPlusPrice'),
('Solo','SoloPrice'),
('All','AllPrice'))) + ')'
choiceX = robjects.rinterface.parse(rcode)
关于python - 等效于rpy2/dataframe访问的命名列表，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/31190863/