#dataframes

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Dataframes explained: The modern in-memory data science format

Dataframes provide efficient and powerful data manipulation in data science, surpassing traditional methods like SQL and Excel.
#open-source

Polars Plugins: let's make them easier to use

Bruno Kind shares his transformative internship experience contributing to Polars plugins, highlighting the significance of user defined functions and community engagement.

Episode #224: Narwhals: Expanding DataFrame Compatibility Between Libraries - The Real Python Podcast

Narwhals enhances compatibility among Python libraries, enabling modern data handling features.
The project mainly supports library maintainers to improve interlibrary functionality.

Polars Plugins: let's make them easier to use

Bruno Kind shares his transformative internship experience contributing to Polars plugins, highlighting the significance of user defined functions and community engagement.

Episode #224: Narwhals: Expanding DataFrame Compatibility Between Libraries - The Real Python Podcast

Narwhals enhances compatibility among Python libraries, enabling modern data handling features.
The project mainly supports library maintainers to improve interlibrary functionality.
moreopen-source

Dataframe interoperability - what has been achieved, and what comes next?

Simple and clear common language enables collaboration among diverse attendees at PyCon Lithuania 2024.

From CSV to Parquet: A Journey Through File Formats in Apache Spark with Scala

SparkSession is used as the entry point to Spark SQL functionality.
Different file formats like CSV, Parquet, JSON, and Avro can be read into DataFrames in Spark.
#python

Polars vs. pandas: What's the Difference? | The PyCharm Blog

Polars is a high-performance Python dataframe library for large datasets, outperforming pandas on speed and memory usage.

Exploring Data Tables in Tkinter with PandasTable - CodersLegacy

PandasTable library allows for easy display and interaction with DataFrames in a Tkinter GUI.
Modifying PandasTable internally is possible by accessing the dataframe through table.model.df attributes.

Polars vs. pandas: What's the Difference? | The PyCharm Blog

Polars is a high-performance Python dataframe library for large datasets, outperforming pandas on speed and memory usage.

Exploring Data Tables in Tkinter with PandasTable - CodersLegacy

PandasTable library allows for easy display and interaction with DataFrames in a Tkinter GUI.
Modifying PandasTable internally is possible by accessing the dataframe through table.model.df attributes.
morepython
#machine-learning

How Narwhals and scikit-lego came together to achieve dataframe-agnosticism

Scikit-lego now supports multiple dataframe implementations like Polars alongside pandas with the help of Narwhals.

Skrub 0.2.0: tabular learning made easy

Skrub 0.2.0 simplifies machine learning on complex dataframes using tabular_learner.

How Narwhals and scikit-lego came together to achieve dataframe-agnosticism

Scikit-lego now supports multiple dataframe implementations like Polars alongside pandas with the help of Narwhals.

Skrub 0.2.0: tabular learning made easy

Skrub 0.2.0 simplifies machine learning on complex dataframes using tabular_learner.
moremachine-learning
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