Reticulate: cannot coerce pandas dataframe to R dataframe

[VyshaliEnukonda]

``````

use_virtualenv("C:\Users\venukond\AppData\Local\Continuum\Anaconda3\envs\py35\")
py_config()
python: C:UsersvenukondAppDataLocalCONTIN~1ANACON~1python.exe
libpython: C:/Users/venukond/AppData/Local/CONTIN~1/ANACON~1/python35.dll
pythonhome: C:UsersvenukondAppDataLocalCONTIN~1ANACON~1
version: 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)]
Architecture: 64bit
numpy: C:UsersvenukondAppDataLocalCONTIN~1ANACON~1libsite-packagesnumpy
numpy_version: 1.11.1
pandas: C:UsersvenukondAppDataLocalCONTIN~1ANACON~1libsite-packagespandas

python versions found:
C:UsersvenukondAppDataLocalCONTIN~1ANACON~1python.exe
C:UsersvenukondAppDataRoamingBLACKR~1python3420B8~1.3python.exe
C:UsersvenukondAppDataLocalContinuumAnaconda3envspy34python.exe
C:UsersvenukondAppDataLocalContinuumAnaconda3envspy34_testpython.exe
C:UsersvenukondAppDataLocalContinuumAnaconda3envspy35python.exe

pd <- import("pandas")
library(reticulate)
pd <- import("pandas")
np <- import("numpy")

df <- pd$DataFrame(

• list(
• 'A' = 1.,
• 'B' = pd$Timestamp('20130102'),
• 'C' = pd$Series(1, index = seq(4), dtype = 'float32'),
• 'D' = np$array(rep(3L, 4), dtype='int32'),
• 'E' = pd$Categorical(c("test","train","test","train")),
• 'F' = 'foo'
• )
• )
  class(df)
  [1] "pandas.core.frame.DataFrame" "pandas.core.generic.NDFrame" "pandas.core.base.PandasObject" "pandas.core.base.StringMixin"
  [5] "python.builtin.object"
  as.data.frame(df)
  Error in as.data.frame.default(df) :
  c("cannot coerce class "c("pandas.core.frame.DataFrame", "pandas.core.generic.NDFrame", " to a data.frame", "cannot coerce class ""pandas.core.base.PandasObject", "pandas.core.base.StringMixin", " to a data.frame", "cannot coerce class ""python.builtin.object")" to a data.frame")

sessionInfo()
R version 3.3.0 (2016-05-03)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252

attached base packages:
[1] stats graphics grDevices datasets utils methods base

other attached packages:
[1] reticulate_1.1

loaded via a namespace (and not attached):
[1] tools_3.3.0 Rcpp_0.12.9 jsonlite_1.2
>

[jjallaire]

That's correct, we don't currently have support for marshaling data frames. We do plan on working on this in the future, in the meantime you can convert the slice(s) of the data frame you want access to in R into NumPy arrays: https://stackoverflow.com/questions/13187778/convert-pandas-dataframe-to-numpy-array-preserving-index

[kenahoo]

Hi @jjallaire, I don't quite see what your suggestion means - is it the df.reset_index().values.ravel().view(dtype=[('index', int), ('A', float), ('B', float), ('C', float)]) thing in meteore's answer? Or the df_to_sarray() in Phil's answer maybe?

[mkoohafkan]

Another workaround is to use JSON:

library(reticulate)
pandas = import('pandas')
numpy = import('numpy')
numpy.random = import('numpy.random')
p.df = pandas$DataFrame(numpy.random$randint(low = 0, high = 10, size = c(5, 5)),
  columns = c('a', 'b', 'c', 'd', 'e'))

library(rjson)
do.call(rbind,lapply(fromJSON(p.df$to_json(orient='records')), as.data.frame))

A bit clunky though.

[harryprince]

Wrong Code:

numpy.random$randint(low = 0, high = 10, size = c(5, 5))

Error:

Error in py_call_impl(callable, dots$args, dots$keywords) : TypeError: 'float' object cannot be interpreted as an index

Right Code:

numpy.random$randint(low = 0, high = 10, size = c(5L, 5L))

@VyshaliEnukonda

[jjallaire]

We've just merged support for converting to and from Pandas data frames onto master. Would love it if anyone subscribed to this thread could test it out. You can install with:

devtools::install_github("rstudio/reticulate")

[jjallaire]

cc @kevinushey

[kevinushey]

Looks like the example in this issue doesn't quite work yet -- I'll take a look.

[Liiiii2101]

try py_to_r(), it helps for me