Homework for exploring function dependencies in data sets
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Updated
Apr 24, 2017 - Python
Homework for exploring function dependencies in data sets
Python function to generate a mask analysis
The program compares two files at a time and does the following 1.Gathering metadata on the individual tables(column count,record count,list of columns with datatype etc) 2.Identifying matching columns between tables based on names as well as data. Using machine learning, we are handling syntactic as well as semantic variations of column names f…
Data profiler is an attempt to model the behavior of a given operator for a set of datasets.
Map naturally-occurring inter-subreddit content sharing patterns on Reddit by analyzing how posts are “cross-posted" between subreddits based on 2.5 million posts across the top 2,500 subreddits. Uses ECL and HPCC Systems.
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
🚚 Agile Data Science Workflows made easy with Pyspark
Distributable UCC Discovery Algorithm based on Akka
MetricDoc is an interactive visual exploration environment for assessing data quality
Identified data types for each distinct column value on 1900 data sets. For each column, summarized semantic types present in the column, using Fuzzy Logic, Levenshtein distance. Identified & derived inference the 3 most frequent 311 complaint types by borough.
Analysis of forex exchange rate dataset, covering the historical aspects over the period of time, in short doing Timeseries Analysis ,Data Cleansing and Transformation of Forex Exchange Dataset in order to transform it in format or structure required during Timeseries Analysis and Machine Learning ,Visualization of Forex Exchange Dataset based …
Open Data Profiling, Quality and Analysis on NYC OpenData dataset with semantic profiling using fuzzy ratio, Levenshtein distance and regex
Fork of Sato for easy deployment as a Python package
Data cleaning tool.
A R Notebook to perform basic data profiling and exploratory data analysis on the FIFA19 players dataset and create a dream-team of the top 11 players considering various player attributes.
Demo on Data Engineering using Great Expectations API
Data Analyst Capstone Project in Coursera
DISTOD algorithm: Distributed discovery of bidirectional order dependencies
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