Python Pandas 到 R 数据框
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Python Pandas to R dataframe
提问by JonghoKim
I am going to convert Python pandas dataframe to dataframe in R. I found out few libraries for this problem
我打算将 Python pandas 数据帧转换为 R 中的数据帧。我发现了几个解决这个问题的库
http://pandas.pydata.org/pandas-docs/stable/r_interface.html
http://pandas.pydata.org/pandas-docs/stable/r_interface.html
which is rpy2
这是 rpy2
But I couldn't find the methods for saving or transfer it to R.
但是我找不到将其保存或传输到 R 的方法。
Firstly I tried "to_csv"
首先我尝试了“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
但它给了我一个错误
"AttributeError: 'DataFrame' object has no attribute 'to_csv' "
So I tried to see its data type it was
所以我试图查看它的数据类型
<class 'rpy2.robjects.vectors.DataFrame'>
how could I save this type object to csv file or transfer to R?
如何将这种类型的对象保存到 csv 文件或传输到 R？
采纳答案by lgautier
The recent documentation https://rpy2.github.io/doc/v3.2.x/html/generated_rst/pandas.htmlhas a section about interacting with pandas.
最近的文档https://rpy2.github.io/doc/v3.2.x/html/generated_rst/pandas.html有一个关于与pandas.
Otherwise objects of type rpy2.robjects.vectors.DataFramehave a method to_csvfile, not to_csv:
否则类型的对象rpy2.robjects.vectors.DataFrame有一个方法to_csvfile，而不是to_csv：
https://rpy2.github.io/doc/v3.2.x/html/vector.html#rpy2.robjects.vectors.DataFrame.to_csvfile
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:
如果想在 Python 和 R 之间传递数据，有比读写 CSV 文件更有效的方法。试试转换系统：
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)
回答by jayelm
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).
如果标准的基于文本的格式 (csv) 太慢或太笨重，我建议使用feather，一种基于Apache Arrow的序列化格式。它是由 RStudio/ggplot2/etc (Hadley Wickham) 和 pandas (Wes McKinney) 的创建者明确开发的，用于 Python 和 R 之间的性能和互操作性（请参见此处）。
You need pandas verson 0.20.0+, pip install feather-format, then you can use the to_feather/read_featheroperations as drop-in replacements for to_csv/read_csv:
您需要 pandas 版本 0.20.0+, pip install feather-format，然后您可以使用to_feather/read_feather操作作为to_csv/ 的替代品read_csv：
df_R.to_feather('filename.feather')
df_R = pd.read_feather('filename.feather')
The Requivalents (using the package feather) are
的R等同物（使用包feather）是
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.
除了一些小的调整（例如，你不能保存在羽定制数据帧索引，所以你需要调用df.reset_index()第一），这是一个快速和容易下降的替代产品csv，pickle等等。
回答by agstudy
Once you have your data.frame you can save it using write.tableor one of the wrappers of the latter, for example writee.csv.
拥有 data.frame 后，您可以使用write.table或后者的包装器之一保存它，例如writee.csv。
In rpy2 :
在 rpy2 中：
import rpy2.robjects as robjects
## get a reference to the R function
write_csv = robjects.r('write.csv')
## save
write_csv(df_R,'filename.csv')
