Git Product home page Git Product logo

autoviz's Introduction

AutoViz

Pepy Downloads Pepy Downloads per week Pepy Downloads per month standard-readme compliant Python Versions PyPI Version PyPI License

Automatically Visualize any dataset, any size with a single line of code.

AutoViz performs automatic visualization of any dataset with one line. Give any input file (CSV, txt or json) and AutoViz will visualize it.

Table of Contents

Install

Prerequsites

To clone AutoViz, it's better to create a new environment, and install the required dependencies:

To install from PyPi:

conda create -n <your_env_name> python=3.7 anaconda
conda activate <your_env_name> # ON WINDOWS: `source activate <your_env_name>`
pip install autoviz

To install from source:

cd <AutoViz_Destination>
git clone [email protected]:AutoViML/AutoViz.git
# or download and unzip https://github.com/AutoViML/AutoViz/archive/master.zip
conda create -n <your_env_name> python=3.7 anaconda
conda activate <your_env_name> # ON WINDOWS: `source activate <your_env_name>`
cd AutoViz
pip install -r requirements.txt

Usage

Read this Medium article to know how to use AutoViz.

In the AutoViz directory, open a Jupyter Notebook and use this line to instantiate the library

from autoviz.AutoViz_Class import AutoViz_Class

AV = AutoViz_Class()

Load a dataset (any CSV or text file) into a Pandas dataframe or give the name of the path and filename you want to visualize. If you don't have a filename, you can simply assign the filename argument "" (empty string).

Call AutoViz using the filename (or dataframe) along with the separator and the name of the target variable in the input. AutoViz will do the rest. You will see charts and plots on your screen.

filename = ""
sep = ","
dft = AV.AutoViz(
    filename,
    sep,
    target,
    df,
    header=0,
    verbose=0,
    lowess=False,
    chart_format="svg",
    max_rows_analyzed=150000,
    max_cols_analyzed=30,
)

This is the main calling program in AV. It will call all the load, display and save programs that are currently outside AV. This program will draw scatter and other plots for the input dataset and then call the correct variable name with the add_plots function and send in the chart created by that plotting program, for example, scatter. You have to make sure that add_plots function has the exact name of the variable defined in the Class AV. If not, this will give an error.

Notes:

  • AutoViz will visualize any sized file using a statistically valid sample.
  • COMMA is assumed as default separator in file. But you can change it.
  • Assumes first row as header in file but you can change it.

API

Arguments

  • max_rows_analyzed - limits the max number of rows that is used to display charts
  • max_cols_analyzed - limits the number of continuous vars that can be analyzed
  • verbose
    • if 0, does not print any messages and goes into silent mode. This is the default.
    • if 1, print messages on the terminal and also display charts on terminal.
    • if 2, print messages but will not display charts, it will simply save them.

Maintainers

Contributing

See the contributing file!

PRs accepted.

License

Apache License, Version 2.0 © 2020 Ram Seshadri

autoviz's People

Contributors

autoviml avatar claretnnamocha avatar emekaborisama avatar hironroy avatar morenoh149 avatar risenw avatar rsesha avatar tqcai avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.