timsaucer commented on code in PR #1108: URL: https://github.com/apache/datafusion-python/pull/1108#discussion_r2061619030
########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method Review Comment: double back ticks ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- Review Comment: The ---- needs to be the same length as the title above it. It's one - too short ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output. + +Customizing HTML Rendering +------------------------- + +You can customize how DataFrames are rendered in HTML by configuring the formatter: + +.. code-block:: python + + from datafusion.html_formatter import configure_formatter + + # Change the default styling + configure_formatter( + max_rows=50, # Maximum number of rows to display + max_width=None, # Maximum width in pixels (None for auto) + theme="light", # Theme: "light" or "dark" + precision=2, # Floating point precision + thousands_separator=",", # Separator for thousands + date_format="%Y-%m-%d", # Date format + truncate_width=20 # Max width for string columns before truncating + ) + +The formatter settings affect all DataFrames displayed after configuration. + +Custom Style Providers +--------------------- + +For advanced styling needs, you can create a custom style provider: + +.. code-block:: python + + from datafusion.html_formatter import StyleProvider, configure_formatter + + class MyStyleProvider(StyleProvider): + def get_table_styles(self): + return { + "table": "border-collapse: collapse; width: 100%;", + "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;", + "td": "border: 1px solid #ddd; padding: 8px;", + "tr:nth-child(even)": "background-color: #f2f2f2;", + } + + def get_value_styles(self, dtype, value): + """Return custom styles for specific values""" + if dtype == "float" and value < 0: + return "color: red;" + return None + + # Apply the custom style provider + configure_formatter(style_provider=MyStyleProvider()) + +Creating a Custom Formatter +-------------------------- + +For complete control over rendering, you can implement a custom formatter: + +.. code-block:: python + + from datafusion.html_formatter import Formatter, get_formatter + + class MyFormatter(Formatter): + def format_html(self, batches, schema, has_more=False, table_uuid=None): + # Create your custom HTML here + html = "<div class='my-custom-table'>" + # ... formatting logic ... + html += "</div>" + return html + + # Set as the global formatter + configure_formatter(formatter_class=MyFormatter) + + # Or use the formatter just for specific operations + formatter = get_formatter() + custom_html = formatter.format_html(batches, schema) + +Managing Formatters +------------------ Review Comment: Needs one more `-` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output. + +Customizing HTML Rendering +------------------------- Review Comment: Needs one more `-` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. Review Comment: These need double back ticks to render properly. ``` ``collect()`` or ``show()`` ``` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- Review Comment: Needs on extra `-` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output. + +Customizing HTML Rendering +------------------------- + +You can customize how DataFrames are rendered in HTML by configuring the formatter: + +.. code-block:: python + + from datafusion.html_formatter import configure_formatter + + # Change the default styling + configure_formatter( + max_rows=50, # Maximum number of rows to display + max_width=None, # Maximum width in pixels (None for auto) + theme="light", # Theme: "light" or "dark" + precision=2, # Floating point precision + thousands_separator=",", # Separator for thousands + date_format="%Y-%m-%d", # Date format + truncate_width=20 # Max width for string columns before truncating + ) + +The formatter settings affect all DataFrames displayed after configuration. + +Custom Style Providers +--------------------- Review Comment: Needs one more `-` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output. + +Customizing HTML Rendering +------------------------- + +You can customize how DataFrames are rendered in HTML by configuring the formatter: + +.. code-block:: python + + from datafusion.html_formatter import configure_formatter + + # Change the default styling + configure_formatter( + max_rows=50, # Maximum number of rows to display + max_width=None, # Maximum width in pixels (None for auto) + theme="light", # Theme: "light" or "dark" + precision=2, # Floating point precision + thousands_separator=",", # Separator for thousands + date_format="%Y-%m-%d", # Date format + truncate_width=20 # Max width for string columns before truncating + ) + +The formatter settings affect all DataFrames displayed after configuration. + +Custom Style Providers +--------------------- + +For advanced styling needs, you can create a custom style provider: + +.. code-block:: python + + from datafusion.html_formatter import StyleProvider, configure_formatter + + class MyStyleProvider(StyleProvider): + def get_table_styles(self): + return { + "table": "border-collapse: collapse; width: 100%;", + "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;", + "td": "border: 1px solid #ddd; padding: 8px;", + "tr:nth-child(even)": "background-color: #f2f2f2;", + } + + def get_value_styles(self, dtype, value): + """Return custom styles for specific values""" + if dtype == "float" and value < 0: + return "color: red;" + return None + + # Apply the custom style provider + configure_formatter(style_provider=MyStyleProvider()) + +Creating a Custom Formatter +-------------------------- Review Comment: Needs one more `-` ########## docs/source/user-guide/dataframe.rst: ########## @@ -0,0 +1,179 @@ +.. 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. + +DataFrames +========== + +Overview +-------- + +DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow. + +A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like `collect()` or `show()` are called. + +Basic Usage +---------- + +.. code-block:: python + + import datafusion + from datafusion import col, lit + + # Create a context and register a data source + ctx = datafusion.SessionContext() + ctx.register_csv("my_table", "path/to/data.csv") + + # Create and manipulate a DataFrame + df = ctx.sql("SELECT * FROM my_table") + + # Or use the DataFrame API directly + df = (ctx.table("my_table") + .filter(col("age") > lit(25)) + .select([col("name"), col("age")])) + + # Execute and collect results + result = df.collect() + + # Display the first few rows + df.show() + +HTML Rendering +------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data. + +The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output. + +Customizing HTML Rendering +------------------------- + +You can customize how DataFrames are rendered in HTML by configuring the formatter: + +.. code-block:: python + + from datafusion.html_formatter import configure_formatter + + # Change the default styling + configure_formatter( + max_rows=50, # Maximum number of rows to display + max_width=None, # Maximum width in pixels (None for auto) + theme="light", # Theme: "light" or "dark" + precision=2, # Floating point precision + thousands_separator=",", # Separator for thousands + date_format="%Y-%m-%d", # Date format + truncate_width=20 # Max width for string columns before truncating + ) + +The formatter settings affect all DataFrames displayed after configuration. + +Custom Style Providers +--------------------- + +For advanced styling needs, you can create a custom style provider: + +.. code-block:: python + + from datafusion.html_formatter import StyleProvider, configure_formatter + + class MyStyleProvider(StyleProvider): + def get_table_styles(self): + return { + "table": "border-collapse: collapse; width: 100%;", + "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;", + "td": "border: 1px solid #ddd; padding: 8px;", + "tr:nth-child(even)": "background-color: #f2f2f2;", + } + + def get_value_styles(self, dtype, value): + """Return custom styles for specific values""" + if dtype == "float" and value < 0: + return "color: red;" + return None + + # Apply the custom style provider + configure_formatter(style_provider=MyStyleProvider()) + +Creating a Custom Formatter +-------------------------- + +For complete control over rendering, you can implement a custom formatter: + +.. code-block:: python + + from datafusion.html_formatter import Formatter, get_formatter + + class MyFormatter(Formatter): + def format_html(self, batches, schema, has_more=False, table_uuid=None): + # Create your custom HTML here + html = "<div class='my-custom-table'>" + # ... formatting logic ... + html += "</div>" + return html + + # Set as the global formatter + configure_formatter(formatter_class=MyFormatter) + + # Or use the formatter just for specific operations + formatter = get_formatter() + custom_html = formatter.format_html(batches, schema) + +Managing Formatters +------------------ + +Reset to default formatting: + +.. code-block:: python + + from datafusion.html_formatter import reset_formatter + + # Reset to default settings + reset_formatter() + +Get the current formatter settings: + +.. code-block:: python + + from datafusion.html_formatter import get_formatter + + formatter = get_formatter() + print(formatter.max_rows) + print(formatter.theme) + +Contextual Formatting +-------------------- Review Comment: Needs one more `-` -- This is an automated message from the Apache Git Service. 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