Important dataframe statistics with a single command

Overview

quick_eda

Receiving dataframe statistics with one command


GitHub code size in bytes GitHub top language GitHub PyPI PyPI - Status


Project description

A python package for Data Scientists, Students, ML Engineers and anyone who wants dataframe meta data without the trouble of having to type in numerous commands.

Installation

Use pip to install quick-eda by typing or copying the following command.

pip install quick-eda

License

This package is licensed under BSD Clause 3.

Example usage

Users of the package can import the individual modules from this package, for example:

import quick_eda.df_eda
import quick_eda.column_eda

This loads the submodules quick_eda.df_eda and quick_eda.column_eda. They must be referenced with their full name.

quick_eda.df_eda.df_eda(<df>)
quick_eda.column_eda.column_eda(<column_name>)

An alternative way of importing the submodules is:

from quick_eda import df_eda
from quick_eda import column_eda

This also loads the submodules quick_eda.df_eda and quick_eda.column_eda, and makes them available without their prefix, so they can be used as follows:

df_eda.df_eda(<df>)
column_eda.column_eda(<column_name>)

Yet another variation is to import the desired functions directly:

from quick_eda.df_eda import df_eda
from quick_eda.column_eda import column_eda

Again, this loads the submodules, but makes them directly available:

df_eda(<df>)
column_eda(<column_name>)

Imagine you have a dataframe called pets with the columns name, age and color. You could then run statistics on both the entire dataframe or e.g. the column age with

df_eda(pets)
column_eda(pets, "age")

Source code & further information

The source code is maintained at https://github.com/sveneschlbeck/quick_eda
There are also further information concerning the BSD license model, contributing guidelines and more...

Owner
Sven Eschlbeck
"The more I C, the less I see."
Sven Eschlbeck
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

7.7k Dec 30, 2022
TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data

tedana: TE Dependent ANAlysis TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI)

136 Dec 22, 2022
Data Analysis for First Year Laboratory at Imperial College, London.

Data Analysis for First Year Laboratory at Imperial College, London. For personal reference only, and to reference in lab reports and lab books.

Martin He 0 Aug 29, 2022
High Dimensional Portfolio Selection with Cardinality Constraints

High-Dimensional Portfolio Selecton with Cardinality Constraints This repo contains code for perform proximal gradient descent to solve sample average

Du Jinhong 2 Mar 22, 2022
Feature Detection Based Template Matching

Feature Detection Based Template Matching The classification of the photos was made using the OpenCv template Matching method. Installation Use the pa

Muhammet Erem 2 Nov 18, 2021
Developed for analyzing the covariance for OrcVIO

about This repo is developed for analyzing the covariance for OrcVIO environment setup platform ubuntu 18.04 using conda conda env create --file envir

Sean 1 Dec 08, 2021
Repository created with LinkedIn profile analysis project done

EN/en Repository created with LinkedIn profile analysis project done. The datase

Mayara Canaver 4 Aug 06, 2022
MoRecon - A tool for reconstructing missing frames in motion capture data.

MoRecon - A tool for reconstructing missing frames in motion capture data.

Yuki Nishidate 38 Dec 03, 2022
Integrate bus data from a variety of sources (batch processing and real time processing).

Purpose: This is integrate bus data from a variety of sources such as: csv, json api, sensor data ... into Relational Database (batch processing and r

1 Nov 25, 2021
This module is used to create Convolutional AutoEncoders for Variational Data Assimilation

VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat

Julian Mack 23 Dec 16, 2022
Fitting thermodynamic models with pycalphad

ESPEI ESPEI, or Extensible Self-optimizing Phase Equilibria Infrastructure, is a tool for thermodynamic database development within the CALPHAD method

Phases Research Lab 42 Sep 12, 2022
AptaMat is a simple script which aims to measure differences between DNA or RNA secondary structures.

AptaMAT Purpose AptaMat is a simple script which aims to measure differences between DNA or RNA secondary structures. The method is based on the compa

GEC UTC 3 Nov 03, 2022
A lightweight, hub-and-spoke dashboard for multi-account Data Science projects

A lightweight, hub-and-spoke dashboard for cross-account Data Science Projects Introduction Modern Data Science environments often involve many indepe

AWS Samples 3 Oct 30, 2021
Toolchest provides APIs for scientific and bioinformatic data analysis.

Toolchest Python Client Toolchest provides APIs for scientific and bioinformatic data analysis. It allows you to abstract away the costliness of runni

Toolchest 11 Jun 30, 2022
[CVPR2022] This repository contains code for the paper "Nested Collaborative Learning for Long-Tailed Visual Recognition", published at CVPR 2022

Nested Collaborative Learning for Long-Tailed Visual Recognition This repository is the official PyTorch implementation of the paper in CVPR 2022: Nes

Jun Li 65 Dec 09, 2022
Stream-Kafka-ELK-Stack - Weather data streaming using Apache Kafka and Elastic Stack.

Streaming Data Pipeline - Kafka + ELK Stack Streaming weather data using Apache Kafka and Elastic Stack. Data source: https://openweathermap.org/api O

Felipe Demenech Vasconcelos 2 Jan 20, 2022
Renato 214 Jan 02, 2023
Spaghetti: an open-source Python library for the analysis of network-based spatial data

pysal/spaghetti SPAtial GrapHs: nETworks, Topology, & Inference Spaghetti is an open-source Python library for the analysis of network-based spatial d

Python Spatial Analysis Library 203 Jan 03, 2023
A fast, flexible, and performant feature selection package for python.

linselect A fast, flexible, and performant feature selection package for python. Package in a nutshell It's built on stepwise linear regression When p

88 Dec 06, 2022
Stock Analysis dashboard Using Streamlit and Python

StDashApp Stock Analysis Dashboard Using Streamlit and Python If you found the content useful and want to support my work, you can buy me a coffee! Th

StreamAlpha 27 Dec 09, 2022