A data structure that extends pyspark.sql.DataFrame with metadata information.
from metaframe import MetaFrame
mf = MetaFrame(df=df, metadata={"columns": ["a", "b"]})
mf = mf.withColumn("new_col", F.lit(1))
mf = mf.set_metadata(columns=["a", "b", "new_col"])
mf.show()
assert mf.metadata["columns"] == ["a", "b", "new_col"]
Python This is a Python data processing, analysis, visualization and data operations of the source code warehouse, book ISBN: 9787115527592 Descriptio
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DataPrep — The easiest way to prepare data in Python
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This is my first Data Engineering project, it extracts data from the user's recently played tracks using Spotify's API, transforms data and then loads it into Postgresql using SQLAlchemy engine. Data
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DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
Additional-function-for-pandas Very useful and necessary functions that simplify working with data random_fill_nan(module_name, nan) - Replaces all sp
This project is the implementation template for HW 0 and HW 1 for both the programming and non-programming tracks
MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI Hallo
MEAD: A Large-scale Audio-visual Dataset for Emotional Talking-face Generation [ECCV2020] by Kaisiyuan Wang, Qianyi Wu, Linsen Song, Zhuoqian Yang, Wa
sm_content_clustering A Python module for clustering creators of social media content into networks. Currently supports identifying potential networks
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