datacompy VS popmon

Compare datacompy vs popmon and see what are their differences.

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datacompy popmon
4 1
382 486
8.9% 1.0%
7.4 6.9
6 days ago 3 months ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

datacompy

Posts with mentions or reviews of datacompy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-26.

popmon

Posts with mentions or reviews of popmon. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing datacompy and popmon you can also consider the following projects:

koalas - Koalas: pandas API on Apache Spark

sweetviz - Visualize and compare datasets, target values and associations, with one line of code.

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

cape-dataframes - Privacy transformations on Spark and Pandas dataframes backed by a simple policy language.

data-diff - Compare tables within or across databases

ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

dbt-audit-helper - Useful macros when performing data audits

visualiza - A general-purpose dynamic data visualizer.

lifetimes - Lifetime value in Python

diffable-sql

Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark