[
https://issues.apache.org/jira/browse/BEAM-11951?focusedWorklogId=614695&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-614695
]
ASF GitHub Bot logged work on BEAM-11951:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 24/Jun/21 19:33
Start Date: 24/Jun/21 19:33
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on a change in pull request
#15074:
URL: https://github.com/apache/beam/pull/15074#discussion_r658220348
##########
File path:
website/www/site/content/en/documentation/dsls/dataframes/differences-from-pandas.md
##########
@@ -0,0 +1,90 @@
+---
+type: languages
+title: "Differences from pandas"
+---
+<!--
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+# Differences from pandas
+
+The Apache Beam DataFrame API aims to be a drop-in replacement for pandas, but
there are a few differences to be aware of. This page describes divergences
between the Beam and pandas APIs and provides tips for working with the Beam
DataFrame API.
+
+## Working with pandas sources
+
+Beam operations are always associated with a pipeline. To read source data
into a Beam DataFrame, you have to apply the source to a pipeline object. For
example, to read input from a CSV file, you could use
[read_csv](https://beam.apache.org/releases/pydoc/{{< param release_latest
>}}/apache_beam.dataframe.io.html#apache_beam.dataframe.io.read_csv) as follows:
+
+ df = p | beam.dataframe.io.read_csv(...)
+
+This is similar to pandas
[read_csv](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html),
but `df` is a deferred Beam DataFrame representing the contents of the file.
The input filename can be any file pattern understood by
[fileio.MatchFiles](https://beam.apache.org/releases/pydoc/{{< param
release_latest >}}/apache_beam.io.fileio.html#apache_beam.io.fileio.MatchFiles).
+
+For an example of using sources and sinks with the DataFrame API, see
[taxiride.py](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/dataframe/taxiride.py).
+
+## Classes of unsupported operations
+
+The sections below describe classes of operations that are not supported, or
not yet supported, by Beam DataFrame. Workarounds are suggested, where
applicable.
+
+### Non-parallelizable operations
+
+To support distributed processing, Beam invokes DataFrame operations on
subsets of data in parallel. Some DataFrame operations can’t be parallelized,
and these operations raise a
[NonParallelOperation](https://beam.apache.org/releases/pydoc/{{< param
release_latest
>}}/apache_beam.dataframe.expressions.html#apache_beam.dataframe.expressions.NonParallelOperation)
error by default.
+
+**Workaround**
+
+If you want to use a non-parallelizable operation, you can guard it with a
`beam.dataframe.allow_non_parallel_operations` block. For example:
+
+ with beam.dataframe.allow_non_parallel_operations:
+ quantiles = df.quantile()
Review comment:
```suggestion
from apache_beam import dataframe
with dataframe.allow_non_parallel_operations():
quantiles = df.quantile()
```
##########
File path:
website/www/site/content/en/documentation/dsls/dataframes/differences-from-pandas.md
##########
@@ -0,0 +1,90 @@
+---
+type: languages
+title: "Differences from pandas"
+---
+<!--
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+# Differences from pandas
+
+The Apache Beam DataFrame API aims to be a drop-in replacement for pandas, but
there are a few differences to be aware of. This page describes divergences
between the Beam and pandas APIs and provides tips for working with the Beam
DataFrame API.
+
+## Working with pandas sources
+
+Beam operations are always associated with a pipeline. To read source data
into a Beam DataFrame, you have to apply the source to a pipeline object. For
example, to read input from a CSV file, you could use
[read_csv](https://beam.apache.org/releases/pydoc/{{< param release_latest
>}}/apache_beam.dataframe.io.html#apache_beam.dataframe.io.read_csv) as follows:
+
+ df = p | beam.dataframe.io.read_csv(...)
+
+This is similar to pandas
[read_csv](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html),
but `df` is a deferred Beam DataFrame representing the contents of the file.
The input filename can be any file pattern understood by
[fileio.MatchFiles](https://beam.apache.org/releases/pydoc/{{< param
release_latest >}}/apache_beam.io.fileio.html#apache_beam.io.fileio.MatchFiles).
+
+For an example of using sources and sinks with the DataFrame API, see
[taxiride.py](https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/dataframe/taxiride.py).
+
+## Classes of unsupported operations
+
+The sections below describe classes of operations that are not supported, or
not yet supported, by Beam DataFrame. Workarounds are suggested, where
applicable.
Review comment:
```suggestion
The sections below describe classes of operations that are not supported, or
not yet supported, by the Beam DataFrame API. Workarounds are suggested, where
applicable.
```
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Issue Time Tracking
-------------------
Worklog Id: (was: 614695)
Time Spent: 0.5h (was: 20m)
> Add documentation page highlighting differences from standard pandas
> --------------------------------------------------------------------
>
> Key: BEAM-11951
> URL: https://issues.apache.org/jira/browse/BEAM-11951
> Project: Beam
> Issue Type: Task
> Components: dsl-dataframe, website
> Reporter: Brian Hulette
> Assignee: David Huntsperger
> Priority: P2
> Labels: dataframe-api
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
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