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from pandas import DataFrame
from sklearn.pipeline import Pipeline
from sklearn.base import clone
from sklearn.model_selection import KFold
from scipy.stats import pearsonr
from numpy import Inf


def loadings_similarity_simple(
    pipeline: Pipeline, data,

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#!/usr/bin/env python3
import sys
import json
from subprocess import run
from base64 import decodebytes, encodebytes
from tempfile import NamedTemporaryFile

try:
    from tqdm import tqdm
except ImportError:

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# for indvs and symptoms see https://github.com/kjhealy/covid_symptoms
mapping = list(
    'Fatigue'='tired-regular',
    'Anosmia'='socks-solid',
    'Cough'='head-side-cough-solid',
    'Fever'='thermometer-full-solid',
    'Diarrhea'='toilet-solid',
    'Breath'='lungs-solid'
)

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from pandas_explorer import pandas_explorer
from pandas import read_csv

iris = read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')

pandas_explorer(iris, title='Iris')

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Pre-Proposal Checklist

• Briefly outlines the proposal
• Suggests a review team (optional)
• Declares why it should be a JEP (See the “JEP / Not-a-JEP Rubric” below.)
• Identify a Shepherd to see the process through. (Shepherds are assigned on a round-robin basis from a set of interested engaged volunteers).
• Decide if it’s a JEP according to the criteria listed above. The Shepherd decides if the JEP criteria have been met.

Pre-Proposal

The maintainers of the jupyter(lab)-lsp would like to propose its incorporation as an official Project Jupyter project, as signalled by a new, Jupyter-branded GitHub organization. We feel it would benefit Jupyter users through higher velocity in delivering more robust features otherwise missing in the Jupyter interactive computing experience.

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JupyterLab 3.2 on Binder

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JupyterLab 3.2 with jupytext and git

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