When I pass a pandas DataFrame as an input argument to magic line I get an error.
%R -i df
ValueError: Buffer for this type not yet supported.
Pasted below is the complete code where I pass a pandas df as an input to a magic cell.
I am running my code on Windows 10. I have the 2019.10 Windows 64 bit version of Anaconda. The packages have the following versions - rpy2 - 2.9.4, python - 3.6.9, jupyter - 1.0.0, pandas - 0.25.2.
I have recently re-installed anaconda on my computer. I have the same packages installed, however different versions from the past. I do not what my previous version of the packages where. My code was working prior to the reinstall. The code below is a sample but
After I ran the magic cell I get the error.
%%R -i df
df$index <- as.numeric(row.names(df))
library(ggplot2)
ggplot(data = df, aes(x = index)) +
geom_line(aes(y = col1, color = 'col1'), size = 0.5) +
geom_line(aes(y = col2, color = 'col2'), size = 0.5)
ValueError: Buffer for this type not yet supported.
Now I go back to the same cell and delete the input argument and re-run it again and I get the desired output without any error.
%%R
df$index <- as.numeric(row.names(df))
library(ggplot2)
ggplot(data = df, aes(x = index)) +
geom_line(aes(y = col1, color = 'col1'), size = 0.5) +
geom_line(aes(y = col2, color = 'col2'), size = 0.5)
Below is the complete code.
--> import pandas as pd
df = pd.DataFrame({'col1': [1, 2, 3, 4], 'col2': [5, 6, 7, 8], 'col3': ['a','b','a','b']})
df
-- >%load_ext rpy2.ipython
--> %%R -i df
df$index <- as.numeric(row.names(df))
library(ggplot2)
ggplot(data = df, aes(x = index)) +
geom_line(aes(y = col1, color = 'col1'), size = 0.5) +
geom_line(aes(y = col2, color = 'col2'), size = 0.5)
I expected R magic to work in order for me to plot my data using ggplot2 as it had prior to my reinstall of anaconda.
Below is the error.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-57-4a5dfe23f86a> in <module>
----> 1 get_ipython().run_cell_magic('R', '-i df', "df$index <- as.numeric(row.names(df))\nlibrary(ggplot2)\nggplot(data = df, aes(x = index)) + \n geom_line(aes(y = col1, color = 'col1'), size = 0.5) + \n geom_line(aes(y = col2, color = 'col2'), size = 0.5)\n")
C:\Anaconda3\envs\keras\lib\site-packages\IPython\core\interactiveshell.py in run_cell_magic(self, magic_name, line, cell)
2357 with self.builtin_trap:
2358 args = (magic_arg_s, cell)
-> 2359 result = fn(*args, **kwargs)
2360 return result
2361
<C:\Anaconda3\envs\keras\lib\site-packages\decorator.py:decorator-gen-131> in R(self, line, cell, local_ns)
C:\Anaconda3\envs\keras\lib\site-packages\IPython\core\magic.py in <lambda>(f, *a, **k)
185 # but it's overkill for just that one bit of state.
186 def magic_deco(arg):
--> 187 call = lambda f, *a, **k: f(*a, **k)
188
189 if callable(arg):
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\ipython\rmagic.py in R(self, line, cell, local_ns)
688 raise NameError("name '%s' is not defined" % input)
689 with localconverter(converter) as cv:
--> 690 ro.r.assign(input, val)
691
692 tmpd = self.setup_graphics(args)
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\functions.py in __call__(self, *args, **kwargs)
176 v = kwargs.pop(k)
177 kwargs[r_k] = v
--> 178 return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
179
180 pattern_link = re.compile(r'\\link\{(.+?)\}')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\functions.py in __call__(self, *args, **kwargs)
105 new_kwargs[k] = conversion.py2ri(v)
106 res = super(Function, self).__call__(*new_args, **new_kwargs)
--> 107 res = conversion.ri2ro(res)
108 return res
109
C:\Anaconda3\envs\keras\lib\functools.py in wrapper(*args, **kw)
805 '1 positional argument')
806
--> 807 return dispatch(args[0].__class__)(*args, **kw)
808
809 funcname = getattr(func, '__name__', 'singledispatch function')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\ipython\rmagic.py in _(obj)
147 if 'data.frame' in obj.rclass:
148 # request to turn it to a pandas DataFrame
--> 149 res = converter.ri2py(obj)
150 else:
151 res = ro.sexpvector_to_ro(obj)
C:\Anaconda3\envs\keras\lib\functools.py in wrapper(*args, **kw)
805 '1 positional argument')
806
--> 807 return dispatch(args[0].__class__)(*args, **kw)
808
809 funcname = getattr(func, '__name__', 'singledispatch function')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\pandas2ri.py in ri2py_listvector(obj)
181 def ri2py_listvector(obj):
182 if 'data.frame' in obj.rclass:
--> 183 res = ri2py(DataFrame(obj))
184 else:
185 res = numpy2ri.ri2py(obj)
C:\Anaconda3\envs\keras\lib\functools.py in wrapper(*args, **kw)
805 '1 positional argument')
806
--> 807 return dispatch(args[0].__class__)(*args, **kw)
808
809 funcname = getattr(func, '__name__', 'singledispatch function')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\pandas2ri.py in ri2py_dataframe(obj)
188 @ri2py.register(DataFrame)
189 def ri2py_dataframe(obj):
--> 190 items = tuple((k, ri2py(v)) for k, v in obj.items())
191 res = PandasDataFrame.from_items(items)
192 return res
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\pandas2ri.py in <genexpr>(.0)
188 @ri2py.register(DataFrame)
189 def ri2py_dataframe(obj):
--> 190 items = tuple((k, ri2py(v)) for k, v in obj.items())
191 res = PandasDataFrame.from_items(items)
192 return res
C:\Anaconda3\envs\keras\lib\functools.py in wrapper(*args, **kw)
805 '1 positional argument')
806
--> 807 return dispatch(args[0].__class__)(*args, **kw)
808
809 funcname = getattr(func, '__name__', 'singledispatch function')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\pandas2ri.py in ri2py_vector(obj)
137 @ri2py.register(SexpVector)
138 def ri2py_vector(obj):
--> 139 res = numpy2ri.ri2py(obj)
140 return res
141
C:\Anaconda3\envs\keras\lib\functools.py in wrapper(*args, **kw)
805 '1 positional argument')
806
--> 807 return dispatch(args[0].__class__)(*args, **kw)
808
809 funcname = getattr(func, '__name__', 'singledispatch function')
C:\Anaconda3\envs\keras\lib\site-packages\rpy2\robjects\numpy2ri.py in ri2py_sexp(obj)
157 def ri2py_sexp(obj):
158 if (obj.typeof in _vectortypes) and (obj.typeof != VECSXP):
--> 159 res = numpy.asarray(obj)
160 else:
161 res = ro.default_converter.ri2py(obj)
C:\Anaconda3\envs\keras\lib\site-packages\numpy\core\numeric.py in asarray(a, dtype, order)
536
537 """
--> 538 return array(a, dtype, copy=False, order=order)
539
540
ValueError: Buffer for this type not yet supported.
