thisisnic commented on a change in pull request #11914:
URL: https://github.com/apache/arrow/pull/11914#discussion_r765813835
##########
File path: r/vignettes/python.Rmd
##########
@@ -10,6 +10,11 @@ vignette: >
The `arrow` package provides `reticulate` methods for passing data between
R and Python in the same process. This document provides a brief overview.
+Why you might want to use `pyarrow`?
+* To use a Python functionality, for example: `concat_arrays` function.
+* To transfer Python objects into R, for example Pandas datatrame into R
+ arrow array.
Review comment:
```suggestion
Why you might want to use `pyarrow`?
* To use some Python functionality that is not yet implemented in R, for
example, the `concat_arrays` function.
* To transfer Python objects into R, for example, a Pandas dataframe into an
R Arrow Array.
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -45,7 +55,7 @@ use_virtualenv("arrow-env")
pa <- import("pyarrow")
```
-The package includes support for sharing Arrow `Array` and `RecordBatch`
+The `pyarrow` package includes support for sharing Arrow `Array` and
`RecordBatch`
objects in-process between R and Python. For example, let's create an `Array`
in `pyarrow`.
Review comment:
```suggestion
in pyarrow.
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -76,10 +86,10 @@ a[a > 1]
## ]
```
-We can send data both ways. One reason we might want to use `pyarrow` in R is
+You can send data both ways. One reason you might want to use `pyarrow` in R is
to take advantage of functionality that is better supported in Python than in
R.
For example, `pyarrow` has a `concat_arrays` function, but as of 0.17, this
-function is not implemented in the `arrow` R package. We can use `reticulate`
+function is not implemented in the `arrow` R package. You can use `reticulate`
Review comment:
```suggestion
function is not implemented in the arrow R package. You can use reticulate
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -101,13 +111,24 @@ a_and_b
## ]
```
-Now we have a single `Array` in R.
+Now you have a single `Array` in R.
Review comment:
```suggestion
Now you have a single Array in R.
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -45,7 +55,7 @@ use_virtualenv("arrow-env")
pa <- import("pyarrow")
```
-The package includes support for sharing Arrow `Array` and `RecordBatch`
+The `pyarrow` package includes support for sharing Arrow `Array` and
`RecordBatch`
Review comment:
```suggestion
The pyarrow package includes support for sharing Arrow `Array` and
`RecordBatch`
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -28,6 +33,11 @@ add `nightly = TRUE`:
install_pyarrow("arrow-env", nightly = TRUE)
```
+A virtualenv or a virtual environment is a specific Python installation
+created for one project or purpose. It is a good practice to use
+specific environments in Python so that updating a package doesn't
+impact packages in other projects.
Review comment:
Love this!
##########
File path: r/vignettes/python.Rmd
##########
@@ -10,6 +10,11 @@ vignette: >
The `arrow` package provides `reticulate` methods for passing data between
Review comment:
```suggestion
The arrow package provides
[reticulate](https://rstudio.github.io/reticulate/) methods for passing data
between
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -76,10 +86,10 @@ a[a > 1]
## ]
```
-We can send data both ways. One reason we might want to use `pyarrow` in R is
+You can send data both ways. One reason you might want to use `pyarrow` in R is
to take advantage of functionality that is better supported in Python than in
R.
For example, `pyarrow` has a `concat_arrays` function, but as of 0.17, this
Review comment:
```suggestion
For example, pyarrow has a `concat_arrays()` function, but as of 0.17, this
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -76,10 +86,10 @@ a[a > 1]
## ]
```
-We can send data both ways. One reason we might want to use `pyarrow` in R is
+You can send data both ways. One reason you might want to use `pyarrow` in R is
Review comment:
```suggestion
You can send data both ways. One reason you might want to use pyarrow in R is
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -62,8 +72,8 @@ a
## ]
```
-`a` is now an `Array` object in our R session, even though we created it in
Python.
-We can apply R methods on it:
+`a` is now an `Array` object in our R session, even though you created it in
Python.
Review comment:
```suggestion
`a` is now an `Array` object in your R session, even though you created it
in Python.
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -101,13 +111,24 @@ a_and_b
## ]
```
-Now we have a single `Array` in R.
+Now you have a single `Array` in R.
+
+## How this works
"Send", however, isn't the correct word. Internally, we're passing pointers to
the data between the R and Python interpreters running together in the same
process, without copying anything. Nothing is being sent: we're sharing and
accessing the same internal Arrow memory buffers.
+## Arrow object types
+
+For more information about Arrow object types see the Internals section of
+the Arrow vignette by calling:
Review comment:
```suggestion
the "arrow" vignette:
```
##########
File path: r/vignettes/python.Rmd
##########
@@ -101,13 +111,24 @@ a_and_b
## ]
```
-Now we have a single `Array` in R.
+Now you have a single `Array` in R.
+
+## How this works
"Send", however, isn't the correct word. Internally, we're passing pointers to
the data between the R and Python interpreters running together in the same
process, without copying anything. Nothing is being sent: we're sharing and
accessing the same internal Arrow memory buffers.
+## Arrow object types
+
+For more information about Arrow object types see the Internals section of
Review comment:
```suggestion
For more information about Arrow object types see the "Internals" section of
```
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