datacompy
Pandas and Spark DataFrame comparison for humans and more! (by capitalone)
blog
By remysucre
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.
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.
- How to Check 2 SQL Tables Are the Same
-
Comparing 2 CSV files
datacompy is a package to compare 2 pandas dataframes
- Performing Data Tests on External Data/Complex Data Quality Checks
-
Best Practice When Comparing Data Across Two SQL Servers in Python
https://github.com/capitalone/datacompy will allow you to compare two tables/dataframes against one another, and see detailed results on the difference.
blog
Posts with mentions or reviews of blog.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-26.
What are some alternatives?
When comparing datacompy and blog you can also consider the following projects:
koalas - Koalas: pandas API on Apache Spark
merkle-tree-solidity - JS - Solidity sha3 merkle tree bridge. Generate proofs in JS; verify in Solidity.
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.
diffable-sql
data-diff - Compare tables within or across databases
dbt-audit-helper - Useful macros when performing data audits
handy_sql_queries
visualiza - A general-purpose dynamic data visualizer.
popmon - Monitor the stability of a Pandas or Spark dataframe ⚙︎
datacompy vs koalas
blog vs merkle-tree-solidity
datacompy vs data-science-ipython-notebooks
blog vs diffable-sql
datacompy vs data-diff
blog vs dbt-audit-helper
datacompy vs dbt-audit-helper
blog vs handy_sql_queries
datacompy vs visualiza
datacompy vs popmon
datacompy vs diffable-sql
datacompy vs merkle-tree-solidity