To make sure the Vega charts render correctly, view the notebook not from the Github repo but the published website here: https://walterra.github.io/jupyter2kibana/viz-2c-cars-outlier.html

viz-2c-cars-outlier.ipynb¶

This notebook creates a violin chart to show the distribution of Miles per Gallon over different areas.

import datetime
import altair as alt
import eland as ed
from elasticsearch import Elasticsearch
import elastic_transport
import logging
import json
import numpy as np
import matplotlib.pyplot as plt
import urllib3
import warnings

alt.data_transformers.disable_max_rows()
logging.getLogger("elastic_transport").setLevel(logging.ERROR)

# Suppress insecure SSL connection warnings
# In dev environments with the `verify_certs=False`
# you might want to reduce those warnings.
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
urllib3.disable_warnings(elastic_transport.SecurityWarning)

# For rendering the notebook to HTML hide all warnings
warnings.filterwarnings('ignore')

index_name = 'cars_outlier'

with open('config.json') as config_file:
  es_config = json.load(config_file)

# First instantiate an 'Elasticsearch' instance with the supplied config
es = Elasticsearch(
    hosts=[es_config['es_client']],
    basic_auth=[
        es_config['user'],
        es_config['password']
    ],
    # Only in development environments with self signed certificates fall back to use `verify_certs=False`
    verify_certs=False
)

ed_df = ed.DataFrame(es, index_name)
ed_df.head()

# Note: To create the Vega spec using Altair we reference ES via URL first. This will only work
# for non-secured ES instances. If your ES instance runs using SSL and/or authentication the chart
# in this cell will render empty. You can still save the visualization in Kibana correctly in the
# next cell because there the URL gets replaced with an Elasticsearch query
# to be used via the Kibana Vega plugin.

# WARNING:
# Do the following approach using a proxy only for demo purposes in a development environment.
# It will expose a secured ES instance unsecured!
# To make this work for demo purposes run the nodejs based proxy in a separate terminal like this:
# NODE_TLS_REJECT_UNAUTHORIZED='0' node proxy

# URL as ES endpoint
# url = 'http://localhost:9220/'+index_name+'/_search?size=1000'

# URL static fallback
url = 'https://walterra.github.io/jupyter2kibana/data/cars_outlier.json'

url_data = alt.Data(url=url, format=alt.DataFormat(property='hits.hits',type='json'))

fields = ['Acceleration', 'Cylinders', 'Displacement', 'Horsepower',
       'Miles_per_Gallon', 'Name', 'Origin', 'Weight_in_lbs', 'Year','ml.outlier_score']

rename_dict = dict((a, 'datum._source.'+a) for a in fields)

chart = alt.Chart(url_data).transform_calculate(**rename_dict).transform_density(
    'Miles_per_Gallon',
    as_=['Miles_per_Gallon', 'density'],
    extent=[5, 50],
    groupby=['Origin']
).mark_area(orient='horizontal').encode(
    y='Miles_per_Gallon:Q',
    color='Origin:N',
    x=alt.X(
        'density:Q',
        stack='center',
        impute=None,
        title=None,
        axis=alt.Axis(labels=False, values=[0],grid=False, ticks=True),
    ),
    column=alt.Column(
        'Origin:N',
        header=alt.Header(
            titleOrient='bottom',
            labelOrient='bottom',
            labelPadding=0,
        ),
    )
).properties(
    width=100
).configure_facet(
    spacing=0
).configure_view(
    stroke=None
)

chart

from kibana_vega_util import saveVegaLiteVis

saveVegaLiteVis(
    index_name,
    'def-vega-cars-violin-1',
    chart,
    resultSize=1000,
    # Only in development environments with self signed certificates fall back to use `verify=False`
    verify=False,
    timeField="Year"
)

<Response [409]>

	Acceleration	Cylinders	Displacement	Horsepower	Miles_per_Gallon	Name	Origin	Weight_in_lbs	Year	ml.feature_influence	ml.feature_influence.feature_name	ml.feature_influence.influence	ml.outlier_score	ml__incremental_id
0	12.0	8	307.0	130.0	18.0	chevrolet chevelle malibu	USA	3504	1970-01-01	NaN	NaN	NaN	0.059161	0
1	11.5	8	350.0	165.0	15.0	buick skylark 320	USA	3693	1970-01-01	NaN	NaN	NaN	0.044278	1
2	11.0	8	318.0	150.0	18.0	plymouth satellite	USA	3436	1970-01-01	NaN	NaN	NaN	0.031178	2
3	12.0	8	304.0	150.0	16.0	amc rebel sst	USA	3433	1970-01-01	NaN	NaN	NaN	0.033840	3
4	10.5	8	302.0	140.0	17.0	ford torino	USA	3449	1970-01-01	NaN	NaN	NaN	0.042260	4