Is there an easy way to read pickle files (.pkl) from Pandas Dataframe into R?
是否有一种简单的方法可以将从熊猫Dataframe到R中读取pickle文件(.pkl) ?
One possibility is to export to CSV and have R read the CSV but that seems really cumbersome for me because my dataframes are rather large. Is there an easier way to do so?
一种可能是导出到CSV，让R读取CSV，但这对我来说很麻烦，因为我的数据aframes非常大。有没有更简单的方法?
Thanks!
谢谢!
1 个解决方案
#1
6
You could load the pickle in python and then export it to R via the python package rpy2 (or similar). Once you've done so, your data will exist in an R session linked to python. I suspect that what you'd want to do next would be to use that session to call R and saveRDS to a file or RAM disk. Then in RStudio you can read that file back in. Look at the R packages rJython and rPython for ways in which you could trigger the python commands from R.
您可以在python中加载pickle，然后通过python包rpy2(或类似的包)将其导出到R。一旦您这样做了，您的数据将存在于一个链接到python的R会话中。我怀疑您接下来要做的是使用会话调用文件或RAM磁盘的R和saveRDS。然后在RStudio中，您可以重新读取该文件。查看rJython和rPython的R包，了解如何从R触发python命令。
Alternatively, you could write a simple python script to load your data in Python (probably using one of the R packages noted above) and write a formatted data stream to stdout. Then that entire system call to the script (including the argument that specifies your pickle) can use used as an argument to fread in the R package data.table. Alternatively, if you wanted to keep to standard functions, you could use combination of system(..., intern=TRUE) and read.table.
或者，您可以编写一个简单的python脚本来在python中加载数据(可能使用上面提到的一个R包)，并将格式化的数据流写入stdout。然后，对脚本的整个系统调用(包括指定pickle的参数)可以用作在R包data.table中fread的参数。或者，如果您希望保持标准函数，您可以使用system(…,实习生= TRUE)和read.table。
As usual, there are /many/ ways to skin this particular cat. The basic steps are:
和往常一样，有很多方法可以剥这只猫的皮。的基本步骤是:
- Load the data in python
- 在python中加载数据
- Express the data to R (e.g., exporting the object via rpy2 or writing formatted text to stdout with R ready to receive it on the other end)
- 将数据表示为R(例如，通过rpy2导出对象，或者将格式化文本写入stdout, R准备在另一端接收)
- Serialize the expressed data in R to an internal data representation (e.g., exporting the object via rpy2 or
fread) - 将R中的表示数据序列化为内部数据表示(例如，通过rpy2或fread导出对象)
- (optional) Make the data in that session of R accessible to another R session (i.e., the step to close the loop with rpy2, or if you've been using
freadthen you're already done). - (可选)使该会话中的数据可由另一个会话访问(即，使用rpy2关闭循环的步骤，或者如果您已经使用了fread，那么您已经完成了)。
#1
6
You could load the pickle in python and then export it to R via the python package rpy2 (or similar). Once you've done so, your data will exist in an R session linked to python. I suspect that what you'd want to do next would be to use that session to call R and saveRDS to a file or RAM disk. Then in RStudio you can read that file back in. Look at the R packages rJython and rPython for ways in which you could trigger the python commands from R.
您可以在python中加载pickle，然后通过python包rpy2(或类似的包)将其导出到R。一旦您这样做了，您的数据将存在于一个链接到python的R会话中。我怀疑您接下来要做的是使用会话调用文件或RAM磁盘的R和saveRDS。然后在RStudio中，您可以重新读取该文件。查看rJython和rPython的R包，了解如何从R触发python命令。
Alternatively, you could write a simple python script to load your data in Python (probably using one of the R packages noted above) and write a formatted data stream to stdout. Then that entire system call to the script (including the argument that specifies your pickle) can use used as an argument to fread in the R package data.table. Alternatively, if you wanted to keep to standard functions, you could use combination of system(..., intern=TRUE) and read.table.
或者，您可以编写一个简单的python脚本来在python中加载数据(可能使用上面提到的一个R包)，并将格式化的数据流写入stdout。然后，对脚本的整个系统调用(包括指定pickle的参数)可以用作在R包data.table中fread的参数。或者，如果您希望保持标准函数，您可以使用system(…,实习生= TRUE)和read.table。
As usual, there are /many/ ways to skin this particular cat. The basic steps are:
和往常一样，有很多方法可以剥这只猫的皮。的基本步骤是:
- Load the data in python
- 在python中加载数据
- Express the data to R (e.g., exporting the object via rpy2 or writing formatted text to stdout with R ready to receive it on the other end)
- 将数据表示为R(例如，通过rpy2导出对象，或者将格式化文本写入stdout, R准备在另一端接收)
- Serialize the expressed data in R to an internal data representation (e.g., exporting the object via rpy2 or
fread) - 将R中的表示数据序列化为内部数据表示(例如，通过rpy2或fread导出对象)
- (optional) Make the data in that session of R accessible to another R session (i.e., the step to close the loop with rpy2, or if you've been using
freadthen you're already done). - (可选)使该会话中的数据可由另一个会话访问(即，使用rpy2关闭循环的步骤，或者如果您已经使用了fread，那么您已经完成了)。