I am going to convert Python pandas dataframe to dataframe in R. I found out few libraries for this problem
http://pandas.pydata.org/pandas-docs/stable/r_interface.html
which is rpy2
But I couldn't find the methods for saving or transfer it to R.
Firstly I tried "to_csv"
df_R = com.convert_to_r_dataframe(df_total)
df_R.to_csv(direc+"/qap/detail_summary_R/"+"distance_"+str(gp_num)+".csv",sep = ",")
But it gives me an error
"AttributeError: 'DataFrame' object has no attribute 'to_csv' "
So I tried to see its data type it was
<class 'rpy2.robjects.vectors.DataFrame'>
how could I save this type object to csv file or transfer to R?
There are many data manipulation tasks done in R that can also be done using Pandas in python. In this article, we are going to discuss a comparison between data manipulation using R and Pandas based on some of the important functions and features.
Learn More. Heey great post, but pandas has very similar functions as dplyr. If you use those instead, you get statements very similar to your dplyr statements and you would get the same readability.
Dplython. Package dplython is dplyr for Python users. It provide infinite functionality for data preprocessing.
The PANDA R package (Preferential Attachment based common Neighbor Distribution derived Associations) was designed to perform the following tasks: (1) identify significantly functionally associated protein pairs, (2) predict GO and KEGG terms for proteins, (3) make a cluster of proteins based on the significant protein ...
If standard text-based formats (csv) are too slow or bulky, I'd recommend feather, a serialization format built on Apache Arrow. It was explicitly developed by the creators of RStudio/ggplot2/etc (Hadley Wickham) and pandas (Wes McKinney) for performance and interoperability between Python and R (see here).
You need pandas verson 0.20.0+, pip install feather-format
, then you can use the to_feather
/read_feather
operations as drop-in replacements for to_csv
/read_csv
:
df_R.to_feather('filename.feather')
df_R = pd.read_feather('filename.feather')
The R
equivalents (using the package feather
) are
df <- feather::read_feather('filename.feather')
feather::write_feather(df, 'filename.feather')
Besides some minor tweaks (e.g. you can't save custom DataFrame indexes in feather, so you'll need to call df.reset_index()
first), this is a fast and easy drop-in replacement for csv
, pickle
, etc.
The recent documentation https://rpy2.github.io/doc/v3.2.x/html/generated_rst/pandas.html has a section about interacting with pandas
.
Otherwise objects of type rpy2.robjects.vectors.DataFrame
have a method to_csvfile
, not to_csv
:
https://rpy2.github.io/doc/v3.2.x/html/vector.html#rpy2.robjects.vectors.DataFrame.to_csvfile
If wanting to pass data between Python and R, there are more efficient ways than writing and reading CSV files. Try the conversion system:
from rpy2.robjects import pandas2ri
pandas2ri.activate()
from rpy2.robjects.packages import importr
base = importr('base')
# call an R function on a Pandas DataFrame
base.summary(my_pandas_dataframe)
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