How to convert Python Pandas Dataframe to R data.frame

Question

I'm using the R package PythonInR, and wanted to convert the pandas dataframe to R dataframe using function pyGet(), but I got the error below:

Error in as.data.frame.default(xi, optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class ""PythonObject"" to a data.frame

The text.csv file only contains two columns, name(string) and value(int). The code is as below:

library(PythonInR) 
pyConnect() 
pyIsConnected() 
pyVersion()
pyOptions("usePandas", TRUE) 
pyImport("pandas", as="pd") 
test_code <-'py_df = pd.read_csv("test.csv")' 
pyExec(code = test_code) 
r_df <- pyGet("py_df")

And the output of the code is:

library(PythonInR)
pyConnect()
R is already connected to Python!
pyIsConnected()
[1] TRUE
pyVersion()
[1] "3.6.2 (v3.6.2:5fd33b5, Jul  8 2017, 04:57:36) [MSC v.1900 64 bit (AMD64)]"
pyOptions("usePandas", TRUE)
pyImport("pandas", as="pd")
test_code <- 'py_df = pd.read_csv("test.csv")'
pyExec(code = test_code)
r_df <- pyGet("py_df")

Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class ""PythonObject"" to a data.frame

Can anyone help to suggest how to convert a Pandas data frame to R data.frame using PythonInR?

Answer 1

it's hard to say why it is not working.

Do you have a reproducible example, or can you provide "test.csv". If you think it's a bug, you could write the package author a mail.

As far I see,

sessionInfo()

## R version 3.4.0 (2017-04-21)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 8 (jessie)
## 
## Matrix products: default
## BLAS: /home/florian/bin/R_dev/lib/libRblas.so
## LAPACK: /home/florian/bin/R_dev/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=de_AT.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=de_AT.UTF-8        LC_COLLATE=de_AT.UTF-8    
##  [5] LC_MONETARY=de_AT.UTF-8    LC_MESSAGES=de_AT.UTF-8   
##  [7] LC_PAPER=de_AT.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=de_AT.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] knitr_1.16      PythonInR_0.1-3
## 
## loaded via a namespace (and not attached):
## [1] compiler_3.4.0 magrittr_1.5   R6_2.2.1       markdown_0.8  
## [5] tools_3.4.0    stringi_1.1.5  pack_0.1-1     stringr_1.2.0 
## [9] evaluate_0.10

_

library(PythonInR)
pyConnect() 
## R is already connected to Python!

_

pyIsConnected() 
## [1] TRUE

_

pyVersion()
## [1] "2.7.9 (default, Mar  1 2015, 13:01:26) \n[GCC 4.9.2]"

_

pyOptions("usePandas", TRUE) 
pyImport("pandas", as="pd") 

_

pySet("x", head(cars))   
pyExecp("x")
##    dist  speed
## 0     2      4
## 1    10      4
## 2     4      7
## 3    22      7
## 4    16      8
## 5    10      9

_

pyExecp("type(x)")
## <class 'pandas.core.frame.DataFrame'>
str(pyGet("x"))
## 'data.frame':    6 obs. of  2 variables:
##  $ speed: num  4 4 7 7 8 9
##  $ dist : num  2 10 4 22 16 10

Answer 2

You could use json. The pandas dataframe has a to_json method and you can use the rjson R package to read the json string using fromJSON.

You may also find this and this interesting. Planning to submit to CRAN soon, but I need to do more testing.