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https://issues.apache.org/jira/browse/BEAM-12024?focusedWorklogId=602303&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-602303
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ASF GitHub Bot logged work on BEAM-12024:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 26/May/21 12:49
Start Date: 26/May/21 12:49
Worklog Time Spent: 10m
Work Description: pcoet commented on a change in pull request #14886:
URL: https://github.com/apache/beam/pull/14886#discussion_r639684437
##########
File path: sdks/python/apache_beam/examples/dataframe/README.md
##########
@@ -0,0 +1,139 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you 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.
+-->
+
+# Example DataFrame API Pipelines
+
+This module contains example pipelines that use the [Beam DataFrame
+API](https://beam.apache.org/documentation/dsls/dataframes/overview/).
+
+### Pre-requisites
+
+You must have `apache-beam>=2.30.0` installed in order to run these pipelines,
+since the `apache_beam.exampels.dataframe` module was added in that release.
Review comment:
Typo: "exampels"
##########
File path: sdks/python/apache_beam/examples/dataframe/README.md
##########
@@ -0,0 +1,139 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you 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.
+-->
+
+# Example DataFrame API Pipelines
+
+This module contains example pipelines that use the [Beam DataFrame
+API](https://beam.apache.org/documentation/dsls/dataframes/overview/).
+
+### Pre-requisites
+
+You must have `apache-beam>=2.30.0` installed in order to run these pipelines,
+since the `apache_beam.exampels.dataframe` module was added in that release.
+
+### Wordcount Pipeline
+
+Wordcount is the "Hello World" of data analytic systems, so of course we
+had to implement it for the Beam DataFrame API! See `wordcount.py` for the
+implementation. Note it demonstrates how to integrate the DataFrame API with
+a larger Beam pipeline by using [Beam
+Schemas](https://beam.apache.org/documentation/programming-guide/#what-is-a-schema)
+in conjunction with
+[to_dataframe](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_dataframe)
+and
+[to_pcollection](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_pcollection).
+
+#### Running the pipeline
+
+To run the pipeline locally:
+
+```sh
+python -m apache_beam.examples.dataframe.wordcount \
+ --input gs://dataflow-samples/shakespeare/kinglear.txt \
+ --output counts
+```
+
+This will produce files like `counts-XXXXX-of-YYYYY` with contents like:
+```
+KING: 243
+LEAR: 236
+DRAMATIS: 1
+PERSONAE: 1
+king: 65
+of: 447
+Britain: 2
+OF: 15
+FRANCE: 10
+DUKE: 3
+...
+```
+
+### Taxi Ride Example Pipelines
+
+`taxiride.py` contains implementations for two DataFrame pipelines that
+process the well-known [NYC Taxi
+dataset](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page). These
+pipelines don't use any Beam primitives, instead they build end-to-end
pipelines
+using the DataFrame API, by leveraging [DataFrame
+IOs](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.io.html).
+
+The module defines two pipelines. The `location_id_agg` pipline does a grouped
Review comment:
Typo: "pipline"
##########
File path: sdks/python/apache_beam/examples/dataframe/README.md
##########
@@ -0,0 +1,139 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you 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.
+-->
+
+# Example DataFrame API Pipelines
+
+This module contains example pipelines that use the [Beam DataFrame
+API](https://beam.apache.org/documentation/dsls/dataframes/overview/).
+
+### Pre-requisites
+
+You must have `apache-beam>=2.30.0` installed in order to run these pipelines,
+since the `apache_beam.exampels.dataframe` module was added in that release.
+
+### Wordcount Pipeline
+
+Wordcount is the "Hello World" of data analytic systems, so of course we
+had to implement it for the Beam DataFrame API! See `wordcount.py` for the
+implementation. Note it demonstrates how to integrate the DataFrame API with
+a larger Beam pipeline by using [Beam
+Schemas](https://beam.apache.org/documentation/programming-guide/#what-is-a-schema)
+in conjunction with
+[to_dataframe](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_dataframe)
+and
+[to_pcollection](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_pcollection).
+
+#### Running the pipeline
+
+To run the pipeline locally:
+
+```sh
+python -m apache_beam.examples.dataframe.wordcount \
+ --input gs://dataflow-samples/shakespeare/kinglear.txt \
+ --output counts
+```
+
+This will produce files like `counts-XXXXX-of-YYYYY` with contents like:
+```
+KING: 243
+LEAR: 236
+DRAMATIS: 1
+PERSONAE: 1
+king: 65
+of: 447
+Britain: 2
+OF: 15
+FRANCE: 10
+DUKE: 3
+...
+```
+
+### Taxi Ride Example Pipelines
+
+`taxiride.py` contains implementations for two DataFrame pipelines that
+process the well-known [NYC Taxi
+dataset](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page). These
+pipelines don't use any Beam primitives, instead they build end-to-end
pipelines
Review comment:
"primitives, instead" -> "primitives. Instead"
##########
File path: sdks/python/apache_beam/examples/dataframe/README.md
##########
@@ -0,0 +1,139 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you 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.
+-->
+
+# Example DataFrame API Pipelines
+
+This module contains example pipelines that use the [Beam DataFrame
+API](https://beam.apache.org/documentation/dsls/dataframes/overview/).
+
+### Pre-requisites
+
+You must have `apache-beam>=2.30.0` installed in order to run these pipelines,
+since the `apache_beam.exampels.dataframe` module was added in that release.
+
+### Wordcount Pipeline
+
+Wordcount is the "Hello World" of data analytic systems, so of course we
+had to implement it for the Beam DataFrame API! See `wordcount.py` for the
+implementation. Note it demonstrates how to integrate the DataFrame API with
+a larger Beam pipeline by using [Beam
+Schemas](https://beam.apache.org/documentation/programming-guide/#what-is-a-schema)
+in conjunction with
+[to_dataframe](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_dataframe)
+and
+[to_pcollection](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_pcollection).
+
+#### Running the pipeline
+
+To run the pipeline locally:
+
+```sh
+python -m apache_beam.examples.dataframe.wordcount \
+ --input gs://dataflow-samples/shakespeare/kinglear.txt \
+ --output counts
+```
+
+This will produce files like `counts-XXXXX-of-YYYYY` with contents like:
+```
+KING: 243
+LEAR: 236
+DRAMATIS: 1
+PERSONAE: 1
+king: 65
+of: 447
+Britain: 2
+OF: 15
+FRANCE: 10
+DUKE: 3
+...
+```
+
+### Taxi Ride Example Pipelines
+
+`taxiride.py` contains implementations for two DataFrame pipelines that
+process the well-known [NYC Taxi
+dataset](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page). These
+pipelines don't use any Beam primitives, instead they build end-to-end
pipelines
+using the DataFrame API, by leveraging [DataFrame
+IOs](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.io.html).
+
+The module defines two pipelines. The `location_id_agg` pipline does a grouped
+aggregation on the drop-off location ID. The `borough_enrich` pipeline extends
+this example by joining the zone lookup table to find the borough where each
+drop off occurred, and aggregation
+
+#### Data
+Some snapshots of NYC taxi data have been staged in
+`gs://apache-beam-samples` for use with these example pipelines:
+
+- `gs://apache-beam-samples/nyc_taxi/2017/yellow_tripdata_2017-*.csv`: CSV
files
+ containing taxiride data for each month of 2017 (similar directories exist
for
Review comment:
"taxiride" -> "taxi ride"
##########
File path: sdks/python/apache_beam/examples/dataframe/README.md
##########
@@ -0,0 +1,139 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you 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.
+-->
+
+# Example DataFrame API Pipelines
+
+This module contains example pipelines that use the [Beam DataFrame
+API](https://beam.apache.org/documentation/dsls/dataframes/overview/).
+
+### Pre-requisites
+
+You must have `apache-beam>=2.30.0` installed in order to run these pipelines,
+since the `apache_beam.exampels.dataframe` module was added in that release.
+
+### Wordcount Pipeline
+
+Wordcount is the "Hello World" of data analytic systems, so of course we
+had to implement it for the Beam DataFrame API! See `wordcount.py` for the
+implementation. Note it demonstrates how to integrate the DataFrame API with
+a larger Beam pipeline by using [Beam
+Schemas](https://beam.apache.org/documentation/programming-guide/#what-is-a-schema)
+in conjunction with
+[to_dataframe](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_dataframe)
+and
+[to_pcollection](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.convert.html#apache_beam.dataframe.convert.to_pcollection).
+
+#### Running the pipeline
+
+To run the pipeline locally:
+
+```sh
+python -m apache_beam.examples.dataframe.wordcount \
+ --input gs://dataflow-samples/shakespeare/kinglear.txt \
+ --output counts
+```
+
+This will produce files like `counts-XXXXX-of-YYYYY` with contents like:
+```
+KING: 243
+LEAR: 236
+DRAMATIS: 1
+PERSONAE: 1
+king: 65
+of: 447
+Britain: 2
+OF: 15
+FRANCE: 10
+DUKE: 3
+...
+```
+
+### Taxi Ride Example Pipelines
+
+`taxiride.py` contains implementations for two DataFrame pipelines that
+process the well-known [NYC Taxi
+dataset](https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page). These
+pipelines don't use any Beam primitives, instead they build end-to-end
pipelines
+using the DataFrame API, by leveraging [DataFrame
+IOs](https://beam.apache.org/releases/pydoc/current/apache_beam.dataframe.io.html).
+
+The module defines two pipelines. The `location_id_agg` pipline does a grouped
+aggregation on the drop-off location ID. The `borough_enrich` pipeline extends
+this example by joining the zone lookup table to find the borough where each
+drop off occurred, and aggregation
Review comment:
It seems like this sentence is not finished.
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Issue Time Tracking
-------------------
Worklog Id: (was: 602303)
Time Spent: 6h 20m (was: 6h 10m)
> Add well-documented DataFrame example pipelines
> -----------------------------------------------
>
> Key: BEAM-12024
> URL: https://issues.apache.org/jira/browse/BEAM-12024
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Priority: P2
> Labels: dataframe-api
> Time Spent: 6h 20m
> Remaining Estimate: 0h
>
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