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DataProfiler Alternatives
Similar projects and alternatives to DataProfiler
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ydata-profiling
Create HTML profiling reports from pandas DataFrame objects
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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usaddress
:us: a python library for parsing unstructured United States address strings into address components
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miller
Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
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superset
Apache Superset is a Data Visualization and Data Exploration Platform
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pyWhat
🐸 Identify anything. pyWhat easily lets you identify emails, IP addresses, and more. Feed it a .pcap file or some text and it'll tell you what it is! 🧙♀️
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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vtuber-livechat-dataset
📊 VTuber 1B: Billion-scale Live Chat and Moderation Event Dataset
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better DataProfiler alternative or higher similarity.
DataProfiler reviews and mentions
Posts with mentions or reviews of DataProfiler.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-19.
- FLiPN-FLaNK Stack Weekly for 20 March 2023
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Miller – tool for querying, shaping, reformatting data in CSV, TSV, and JSON
My team built a similar tool in Python to load any delimited file, json, parquet and Avro with one command:
https://github.com/capitalone/DataProfiler
Effectively loads anything into a dataframe
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PyTorch vs. TensorFlow in 2022
The thing is, tensorflow has more ability to run cross platform.
I help maintain https://github.com/capitalone/DataProfiler
Our sensitive data detection library is exported to iOS, android, and Java; in addition to Python. We also run distributed and federated use cases with custom layers. All of which are improved in tensorflow.
That said, I’d use pytorch if I could. Simply put, it has a better user experience.
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Fast CSV Processing with SIMD
I really should write up how we did delimiter and quote detection in this library:
https://github.com/capitalone/DataProfiler
It turns out delimited files IMO are much harder to parse than say, JSON. Largely because they have so many different permutations. The article covers CSVs, but many files are tab or null separated. We’ve even seen @ separated with ‘ for quotes.
Given the above, it should still be possible to use the method described. I’m guessing you’d have to detect the separators and quote chars first, however. You’d have to also handle empty rows and corrupted rows (which happen often enough).
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Dask – a flexible library for parallel computing in Python
Having used both ray, dask, and writing custom threads, my personal view is that while there are advantages I wouldn’t want to use any of these unless absolutely necessary.
My personal approach for most of these tasks are to try to break down the problem to be as asynchronous as possible. Then you can create threads.
The nice thing about dask is really the way you can effectively use it as a pandas dataframe.
Having said that, we opted to write our own parallelization for this library:
https://github.com/capitalone/DataProfiler
As opposed to using the dask frame. Effectively, it’s a high overhead and easier to maintain the threading ourselves given the particular approaches taken.
That said, if I was working with large pandas dataframes, id likely use dask. For large datasets which couldn’t be stored in memory of use ray.io
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Launch HN: Metaplane (YC W20) – Datadog for Data
My team has worked on a library for a similar purpose:
https://github.com/capitalone/DataProfiler
Load any document, profile and monitor the profiles for changes that would impact downstream applications.
Very common problem, you all are in a great space! Very interested and will check out!
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Show HN: Graphsignal – Production Model Monitoring
We built a very similar application internally with our open source library: https://github.com/capitalone/dataprofiler
Effectively, you can monitor changes between profiles:
# Load a CSV file
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Miller CLI – Like Awk, sed, cut, join, and sort for CSV, TSV and JSON
Not exactly the same, but we wrote a library to easily load any delimited type of file and finds header (even if not first row). It also works to load JSON, Parquet, AVRO and loads it into a dataframe. Not CLI exactly, but pretty easy:
https://github.com/capitalone/dataprofiler
Anyway, pretty interesting Miller CLI
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Launch HN: Lightly (YC S21): Label only the data which improves your ML model
Having built a model to identify sensitive data having a solid data labeling solution would be awesome.
https://github.com/capitalone/DataProfiler
In this space, Prodigy really dominates:
We actually built our own internal system which integrates and can export the labels (does predictive labeling, etc). Of course, we only focused on text data at the moment.
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DataProfiler - What's in your data? Extract schema, stats and entities
We made a library called DataProfiler - designed to replace pandas-profiling.
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A note from our sponsor - Sonar
www.sonarsource.com | 22 Mar 2023
Stats
Basic DataProfiler repo stats
54
1,116
9.0
15 days ago
capitalone/DataProfiler is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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SaaSHub helps you find the best software and product alternatives
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