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import dash | |
from dash.dependencies import Output, Input | |
import dash_core_components as dcc | |
import dash_html_components as html | |
import plotly.express as px | |
import pandas as pd | |
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] | |
app = dash.Dash(__name__, external_stylesheets=external_stylesheets) | |
colors = { | |
'background': '#FFFFFF', | |
'text': '#7FDBFF' | |
} | |
# Reading The Dataset | |
data = pd.read_csv('https://gist.githubusercontent.com/ThiagoFPMR/' + | |
'fea32b8082a54889ba7470ac63252299/raw/' + | |
'aea145700257ffa89d924073189a0e3804bd987c/' + | |
'covid_worldwide.csv') | |
# Defining App Layout | |
app.layout = html.Div(style={'backgroundColor': colors['background']}, children=[ | |
html.H1('Studying The Pandemic Worldwide', style={'textAlign':'center'}), | |
html.Div([ | |
html.Div([ | |
html.Label('Population'), | |
dcc.Slider( | |
id='population-slider', | |
min=data.population.min(), | |
max=data.population.max(), | |
marks={ | |
72037 : '72K', | |
80000000 : '80M', | |
150000000 : '150M', | |
300000000 : '300M', | |
700000000 : '700M', | |
1000000000 : '1B', | |
1439323776 : '1.4B' | |
}, | |
value=data.population.min(), | |
step=100000000, | |
updatemode='drag' | |
) | |
]), | |
html.Div([ | |
html.Label('Interest Variable'), | |
dcc.Dropdown( | |
id='interest-variable', | |
options=[{'label':'Total Cases', 'value':'total_cases'}, | |
{'label': 'Total Tests', 'value':'total_tests'}, | |
{'label': 'Total Deaths', 'value':'total_deaths'}, | |
{'label': 'Total Recovered', 'value':'total_recovered'}], | |
value='total_cases' | |
) | |
]) | |
], style = {'width':'90%','margin':'auto'}), | |
html.Div([ | |
dcc.Graph( | |
id='covid-vs-edu', | |
), | |
html.Div( | |
dcc.Graph( | |
id='covid-vs-income', | |
) | |
, style = {'width': '50%', 'display': 'inline-block'}), | |
html.Div( | |
dcc.Graph( | |
id='covid-vs-income2', | |
) | |
, style = {'width': '50%', 'display': 'inline-block'}) | |
], style = {'width':'90%','margin':'auto'}) | |
]) |
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