#Exploratory-data-analysis
Showing 60 of 107 repositories tagged #exploratory-data-analysis, ranked by stars
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Always know what to expect from your data.
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown
Automatically visualize your pandas dataframe via a single print! π π‘
Visualize and compare datasets, target values and associations, with one line of code.
Beautiful visualizations of how language differs among document types.
Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
Interactively explore unstructured datasets from your dataframe.
Automatically find issues in image datasets and practice data-centric computer vision.
Compilation of R and Python programming codes on the Data Professor YouTube channel.
Build 12 Data Apps in Python with Streamlit
Kernel Density Estimation in Python
Complete-Life-Cycle-of-a-Data-Science-Project
Ways of doing Data Science Engineering and Machine Learning in R and Python
skimpy is a light weight tool that provides summary statistics about variables in data frames within the console.
Code review for data in dbt
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
A list of software and papers related to automatic and fast Exploratory Data Analysis
dataβ°describe: Pythonic EDA Accelerator for Data Science
this repository features assignments and projects from the iNeuron full stack data science course, providing valuable resources for learners to enhance their skills and apply their knowledge.
Data Science Feature Engineering and Selection Tutorials
Data Analysis Using Python: A Beginnerβs Guide Featuring NYC Open Data.
Classification of Breast Cancer diagnosis Using Support Vector Machines
Mini Projects on Data Analytics including Exploratory Data Analysis, Recommendation Systems, Association Rule Mining, Sentiment Analysis, Time Series Analysis
π οΈ π Tools for Exploring and Comparing Data Frames
Exploratory data analysis πusing python πof used car π database taken from βπππππ
Functionalities in Excel translated to Python
A day to day plan for this challenge. Covers both theoritical and practical aspects
π This repository hosts a growing collection of AI blueprint projects that run end-to-end using Jupyter notebooks, MLflow deployments, and Streamlit web apps.π οΈ All projects are built using HP AI Studio with β€οΈ If you find this useful, please donβt forget to star the repository β and support our work π
HandySpark - bringing pandas-like capabilities to Spark dataframes
This topic explains about the implementation of exploratory data analysis (EDA). A total of 21 EDA case studies have been implemented using the Malaysian dataset.
Tool for visual exploration of complex data.
Solution of the Titanic Kaggle competition
A 60 days+ streak of daily learning of ML/DL/Maths concepts through projects
R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks
R package for exploratory data analysis
Interactively browse multimodal tabular data
The Google Advanced Data Analytics Certificate contains information on how to use machine learning, predictive modeling, and experimental design to collect and analyze large amounts of data, and prepare for jobs like Senior Data Analyst and Junior Data Scientist.
Python-based Jupyter notebooks, notes, and project solutions from DataCamp courses on data science, machine learning, and statistics.
Football Match prediction using machine learning algorithms in jupyter notebook
A curated list of awesome resources such as books, tutorials, courses, open-source libraries, exercises, and other materials that support Pythonistas in the making, and Pythonistas migrating into Data Science! π
Is there a relationship between popularity of a given technology on Stack Overflow (SO) and Hacker News (HN)? And a few words about causality
In this project, a RFM model is implemented to relate to customers in each segment. Assessed the Data Quality, performed EDA using Python and created Dashboard using Tableau.
Data journalism and easy to replicate notebooks using Python, R, and Web visualisations
An Exhaustive WhatsApp Chat Data Analysis.
breadroll π₯ is a simple lightweight library for data processing operations written in Typescript and powered by Bun.
A collection of scripts written to complete DQLab Data Analyst Career Track π
A New Interactive Approach to Learning Data Analysis
A python package that performs exploratory data analysis for users. Additionally, it generates 3 types of output files (cleaned CSV, plots and a text report).
An R package for calculating and drawing variable trees
A library for Time Series EDA (exploratory data analysis)
A library for detecting problematic data segments in structured and unstructured data with few lines of code.
LibrerΓa para la evaluaciΓ³n de calidad de datos, e interacciΓ³n con el portal de datos.gov.co
An open-source Python library for Data Scientists & Data Analysts designed to simplify the exploratory data analysis process. Using Edvart, you can explore data sets and generate reports with minimal coding.
Exploratory Data Analysis | SQL, Tableau, Python
For all those who're struggling to find a good hands-on resource (with case studies) to master their Data Science skills, Here's all what you need!
OlliePy is a python package which can help data scientists in exploring their data and evaluating and analysing their machine learning experiments by utilising the power and structure of modern web applications. The data scientist only needs to provide the data and any required information and OlliePy will generate the rest.
Powerful rapid automatic EDA and feature engineering library with a very easy to use API π