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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{"name": "legend_pointselection_0_store"}, | |
{"name": "legend_pointhover_0_store"}, | |
{"name": "dataframe_2"}, | |
{"name": "data_0"}, | |
{ |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"autosize": {"type": "fit", "contains": "padding"}, | |
"background": "white", | |
"padding": 5, | |
"style": "cell", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{"name": "legend_pointselection_0_store"}, |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"autosize": {"type": "fit", "contains": "padding"}, | |
"background": "white", | |
"padding": 5, | |
"style": "cell", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{ |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{"name": "df"}, | |
{ | |
"name": "data_0", | |
"values": [ | |
{"date": 946702800000, "sum_price": 230.82999999999998}, |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{"name": "df"}, | |
{ | |
"name": "data_0", | |
"values": [ | |
{ |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"autosize": {"type": "fit", "contains": "padding"}, | |
"background": "white", | |
"padding": 5, | |
"style": "cell", | |
"data": [ | |
{"name": "interval_intervalselection_0_store"}, | |
{"name": "click_pointselection_0_store"}, | |
{ |
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{ | |
"$schema": "https://vega.github.io/schema/vega/v5.json", | |
"background": "white", | |
"padding": 5, | |
"width": 200, | |
"height": 200, | |
"style": "cell", | |
"data": [ | |
{"name": "pivot_hover_862a830d_f0c0_47d5_9ac9_eb7216fb8ddf_store"}, | |
{ |
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import dash | |
from dash.dependencies import Input, Output | |
import dash_core_components as dcc | |
import dash_html_components as html | |
import plotly.express as px | |
gapminder = px.data.gapminder().query("year == 2007") | |
input_figure = px.scatter(gapminder, x="gdpPercap", y="lifeExp", size="pop", | |
custom_data=[gapminder.index], # this is the special bit! |
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