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juspy

Maintenance MIT license Open Source? Yes! GitHub followers Twitter URL Discord

juspy is a library for making EDA and Modelling in Python quick and convinient. It's built on top of:

  • pandas
  • numpy
  • seaborn
  • and many such great libraries

Our reccomended path of getting started with juspy

  • Download & install Anaconda
  • Open Anaconda Prompt
  • In Anaconda Prompt type
conda install -c conda-forge jupyterlab
  • and then
pip install juspy
jupyterlab

Incase if you're having any trouble regarding installation or dependencies, kindly make sure you're using updated versions

conda update conda
conda update pip
conda update python

And now try the above steps again

Demo Notebooks:

  1. To test library's proper installation and working:

    import juspy
    print(juspy.__version__)
    
    from juspy import greet
    print(greet.namastey())

    Or, try greeting

    print(greet.hello())
    print(greet.ni_hao())
    print(greet.hola())
    print(greet.bonjour())
    print(greet.schatz())
    print(greet.ahlan())
    print(greet.privet())


  2. If they're producing some output, we're good to go
  3. jpplot.confusion_matrix()

    import numpy as np
    import seaborn as sns
    from sklearn.metrics import confusion_matrix
    
    y_true = [0, 1, 0, 1, 0, 1, 0]
    y_pred = [1, 1, 1, 0, 1, 0, 1]
    cf_matrix = confusion_matrix(y_true, y_pred)
    
    from juspy import plot as jpplot
    jpplot.confusion_matrix(cf_matrix)



  4. jpplot.piechart()

    import pandas as pd
    df_name = pd.read_csv("https://raw.githubusercontent.com/juspreet51/juspy/main/src/juspy/datasets/default.csv")
    
    from juspy import plot as jpplot
    jpplot.piechart(df_name["student"])



  5. Future Release:

  6. from juspy.linear_models import LinearRegression

    from juspy.linear_models import LinearRegression as lin_reg