def recap_world(dt, previous):
previous = (pd.to_datetime(dt, dayfirst=True) -
pd.to_datetime(previous, dayfirst=True)).days
if dt == time.strftime('%d/%m/%Y'):
dt = (datetime.now() - timedelta(1)).strftime('%d/%m/%Y')
df_recap = GetData.get_recap_by_country(dt, previous=int(previous))
df_confirmed = GetData.get_world('confirmed')
confirmed = df_confirmed.iloc[:, -1].sum()
confirmedp = df_recap['Cases (+)'].sum(axis=0)
df_deaths = GetData.get_world('deaths')
deaths = df_deaths.iloc[:, -1].sum()
deathsp = df_recap['Deaths (+)'].sum(axis=0)
df_recovered = GetData.get_world('recovered')
recovered = df_recovered.iloc[:, -1].sum()
recoveredp = df_recap['Recovered (+)'].sum(axis=0)
france_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="France"]):,}'
france_casesp2 = "{0}".format(france_casesp)
us_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="US"]):,}'
us_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="US"]):,}'
france_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="France"]):,}'
italy_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="Italy"]):,}'
italy_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="Italy"]):,}'
germany_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="Germany"]):,}'
germany_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="Germany"]):,}'
china_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="China"]):,}'
china_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="China"]):,}'
spain_cases = f'{int(df_recap["Cases"][df_recap["Country/Region"]=="Spain"]):,}'
spain_casesp = f'{int(df_recap["Cases (+)"][df_recap["Country/Region"]=="Spain"]):,}'
return '{:,}'.format(confirmed),'(+ {:,})'.format(confirmedp),'{:,}'.format(deaths),'(+ {:,})'.format(deathsp),'{:,}'.format(recovered),'(+ {:,})'.format(recoveredp),\
'Mise à jour le {} (+ Variations sur les {} derniers jours)'.format(pd.to_datetime(dt).strftime('%d/%m/%Y'),previous),'{:,}'.format(previous),'{:,}'.format(recoveredp),'{}'.format(france_casesp2),\
'{}'.format(china_cases),'(+ {})'.format(china_casesp),'{}'.format(italy_cases),'(+ {})'.format(italy_casesp),'{}'.format(germany_cases),'(+ {})'.format(germany_casesp),\
'{}'.format(spain_cases),'(+ {})'.format(spain_casesp),'{}'.format(us_cases),'(+ {})'.format(us_casesp),'{}'.format(france_cases),'(+ {})'.format(france_casesp2)
def get_top3_country(name):
index_top3 = GetData.get_world(name).groupby('Country/Region').sum().iloc[:,2:].T.iloc[-1].sort_values(ascending = False).index[0:3].values
df_confirmed_world = GetData.get_world('confirmed').groupby('Country/Region').sum().iloc[:,2:].T
df_deaths_world = GetData.get_world('deaths').groupby('Country/Region').sum().iloc[:,2:].T
df_recovered_world = GetData.get_world('recovered').groupby('Country/Region').sum().iloc[:,2:].T
df = pd.DataFrame()
df['Confirmed'] = df_confirmed_world[index_top3].iloc[-1,:]
df['Recovered'] = df_recovered_world[index_top3].iloc[-1,:]
df['Deaths'] = df_deaths_world[index_top3].iloc[-1,:]
return df
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
from apps import GetData
from apps import graph
import dash_bootstrap_components as dbc
import numpy as np
import pandas as pd
import plotly.graph_objects as go
import time
from app import app
from dash.dependencies import Input, Output
from datetime import datetime, timedelta
app.title = 'CoronaRecap'
df = GetData.get_world('confirmed')
def make_bars(country, df=df):
t = df[(df['Country/Region'] == country)].groupby('Country/Region').sum()
lst = [
list(t[col].values)[0] for col in t.columns if col not in
['Continent', 'Country/Region', 'Province/State', 'Lat', 'Long']
]
variation = [lst[i] - lst[i - 1] for i in range(1, len(lst))]
color = {
'0': {
'border-right': '1px solid rgba(255,255,255,0.5)',
'width': '3px',
},
).iloc[:, 2:].T.iloc[-1].sort_values(ascending=False).index[0:3].values
df_confirmed_world = GetData.get_world('confirmed').groupby(
'Country/Region').sum().iloc[:, 2:].T
df_deaths_world = GetData.get_world('deaths').groupby(
'Country/Region').sum().iloc[:, 2:].T
df_recovered_world = GetData.get_world('recovered').groupby(
'Country/Region').sum().iloc[:, 2:].T
df = pd.DataFrame()
df['Confirmed'] = df_confirmed_world[index_top3].iloc[-1, :]
df['Recovered'] = df_recovered_world[index_top3].iloc[-1, :]
df['Deaths'] = df_deaths_world[index_top3].iloc[-1, :]
return df
top3 = get_top3_country('confirmed')
df = GetData.get_world('confirmed')
def make_bars(country, df=df):
t = df[(df['Country/Region'] == country)].groupby('Country/Region').sum()
lst = [
list(t[col].values)[0] for col in t.columns if col not in
['Continent', 'Country/Region', 'Province/State', 'Lat', 'Long']
]
variation = [lst[i] - lst[i - 1] for i in range(1, len(lst))]
color = {
'0': {
'border-right': '1px solid rgba(255,255,255,0.5)',
'width': '3px',
},
from dash.dependencies import Input, Output, State
import numpy as np
import pandas as pd
from datetime import datetime
from pytrends.request import TrendReq
import plotly.graph_objects as go
from plotly.offline import plot
from app import app
from apps import GetData
from apps import sidebar
import yfinance as yf
import plotly.express as px
df_confirmed_world = GetData.get_world('confirmed')
df_deaths_world = GetData.get_world('deaths')
df = pd.DataFrame()
df['Date'] = pd.to_datetime(df_confirmed_world.iloc[:,5:].columns)
df['Confirmed'] = df_confirmed_world.iloc[:,5:].sum().values
df['Deaths'] = df_deaths_world.iloc[:,5:].sum().values
df.set_index('Date', inplace = True)
list_tickers = ['^FCHI', '^GSPC', '^DJI', '^GDAXI', '^IXIC', '^N225', '^HSI', '^IBEX', 'BTC-USD', 'ETHUSD=X', 'EURUSD=X', 'EURGBP=X', 'EURJPY=X', 'EURCNY=X', 'EURCHF=X',
'HG=F', 'EH=F', 'GC=F', 'NG=F', 'CL=F', 'PL=F', 'SI=F']
title = ['CAC40', 'SP500', 'Dow Jones', 'Dax', 'Nasdaq', 'Nikkei', 'Hangseng', 'Ibex', 'BTC/USD', 'ETH/USD', 'EUR/USD', 'EUR/GBP', 'EUR/JPY', 'EUR/CNY', 'EUR/CHF', 'Copper', 'Ethanol',
'Gold', 'Natural Gas', 'Oil', 'Platinum', 'Silver']
title = np.array(title)
def updatefigure1(valued,valuep):
previous=int(valuep)
date=valued
df_recap=GetData.get_recap_by_country(date,previous=previous)
#Récupération des cas confirmés
df_confirmed=GetData.get_world('confirmed')
confirmed=df_confirmed.iloc[:,5:].sum(axis=1).sum(axis=0)
confirmedp=df_recap['Cases (+)'].sum(axis=0)
#Récupération des cas morts
df_deaths=GetData.get_world('deaths')
deaths=df_deaths.iloc[:,5:].sum(axis=1).sum(axis=0)
deathsp=df_recap['Deaths (+)'].sum(axis=0)
#Récupération des cas guéris
df_recovered=GetData.get_world('recovered')
recovered=df_recovered.iloc[:,5:].sum(axis=1).sum(axis=0)
recoveredp=df_recap['Recovered (+)'].sum(axis=0)
confirmed=f'{confirmed:,}'
deaths=f'{deaths:,}'
recovered=f'{recovered:,}'
confirmedp=f'{confirmedp:,}'
deathsp=f'{deathsp:,}'
recoveredp=f'{recoveredp:,}'
a="<b>{0}</b>".format(confirmed)
b="<b>{0}</b>".format(deaths)
c="<b>{0}</b>".format(recovered)
e="<b>(+{0})</b>".format(confirmedp)
f="<b>(+{0})</b>".format(deathsp)
g="<b>(+{0})</b>".format(recoveredp)
#CSS
fill_color_H2='lightgray'
line_color_H2='lightgray'
font_color_H2=[['black','red']]
font_size_H2=[15]
#layout = go.Layout( autosize=True, **margin={'l': 0, 'r': 0, 't': 20, 'b': 0}**)
fig_H2= go.Figure(data=[go.Table(
header=dict(values=["Confirmed Cases","Deaths", "Recovered"]
,
line_color=line_color_H2,fill_color=fill_color_H2,
align='center',font=dict(color='black', size=10)
),
cells=dict(
values=[[a,e],[b,f], [c,g]],align='center',
line_color=line_color_H2,
fill_color=fill_color_H2, font_color=font_color_H2,
font_size=font_size_H2
))
])
fig_H2.update_layout(
autosize=False,
width=500,
height=170,
margin=dict(
l=20,
r=20,
b=20,
t=50,
pad=10
),
title_text="<b>WORLD</b>",title_x=0.5,
title_font_color='black'
)
return fig_H2
import pandas as pd
from apps import GetData
from apps import graph
import dash_bootstrap_components as dbc
import numpy as np
import pandas as pd
import plotly.graph_objects as go
import plotly.express as px
import time
from app import app
from dash.dependencies import Input, Output
from datetime import datetime, timedelta
import yfinance as yf
### PLOT
df_confirmed_world = GetData.get_world('confirmed')
df = pd.DataFrame()
df['Date'] = pd.to_datetime(df_confirmed_world.iloc[:, 5:].columns)
df['Confirmed_World'] = df_confirmed_world.iloc[:, 5:].sum().values
df.set_index('Date', inplace=True)
list_tickers = [
'^FCHI', '^GSPC', '^DJI', '^GDAXI', '^IXIC', '^N225', '^HSI', '^IBEX',
'BTC-USD', 'ETHUSD=X', 'EURUSD=X', 'EURGBP=X', 'EURJPY=X', 'EURCNY=X',
'EURCHF=X', 'HG=F', 'EH=F', 'GC=F', 'NG=F', 'CL=F', 'PL=F', 'SI=F'
]
title = [
'CAC40', 'SP500', 'Dow Jones', 'Dax', 'Nasdaq', 'Nikkei', 'Hangseng',
'Ibex', 'BTC/USD', 'ETH/USD', 'EUR/USD', 'EUR/GBP', 'EUR/JPY', 'EUR/CNY',
'EUR/CHF', 'Copper', 'Ethanol', 'Gold', 'Natural Gas', 'Oil', 'Platinum',
'Silver'
}
}
#FCT
def get_top3_country(name):
index_top3 = GetData.get_world(name).groupby('Country/Region').sum().iloc[:,2:].T.iloc[-1].sort_values(ascending = False).index[0:3].values
df_confirmed_world = GetData.get_world('confirmed').groupby('Country/Region').sum().iloc[:,2:].T
df_deaths_world = GetData.get_world('deaths').groupby('Country/Region').sum().iloc[:,2:].T
df_recovered_world = GetData.get_world('recovered').groupby('Country/Region').sum().iloc[:,2:].T
df = pd.DataFrame()
df['Confirmed'] = df_confirmed_world[index_top3].iloc[-1,:]
df['Recovered'] = df_recovered_world[index_top3].iloc[-1,:]
df['Deaths'] = df_deaths_world[index_top3].iloc[-1,:]
return df
top3 = get_top3_country('confirmed')
df =GetData.get_world('confirmed')
def make_bars(country,df = df):
t =df[(df['Country/Region'] == country)].groupby('Country/Region').sum()
lst= [list(t[col].values)[0] for col in t.columns if col not in ['Continent','Country/Region','Province/State','Lat','Long']]
variation = [lst[i] - lst[i-1] for i in range(1,len(lst))]
color = {
'0':{
'border-right':'1px solid rgba(255,255,255,0.5)',
'width':'3px',
},
'1-10':{
'background':'rgba(255, 152, 0, 0.1)',
'border-right':'1px solid rgba(255,255,255,0.5)',
'width':'3px',
},
import plotly.graph_objects as go
from apps import GetData
import pandas as pd
import plotly.graph_objects as go
from plotly.colors import n_colors
import numpy as np
import chart_studio.plotly as py
#Récupération du récap
date = "20/03/2020"
previous = 5
df_recap = GetData.get_recap_by_country(date, previous=previous)
#Récupération des cas confirmés
df_confirmed = GetData.get_world('confirmed')
confirmed = df_confirmed.iloc[:, 5:].sum(axis=1).sum(axis=0)
confirmedp = df_recap['Cases (+)'].sum(axis=0)
#Récupération des cas morts
df_deaths = GetData.get_world('deaths')
deaths = df_deaths.iloc[:, 5:].sum(axis=1).sum(axis=0)
deathsp = df_recap['Deaths (+)'].sum(axis=0)
#Récupération des cas guéris
df_recovered = GetData.get_world('recovered')
recovered = df_recovered.iloc[:, 5:].sum(axis=1).sum(axis=0)
recoveredp = df_recap['Recovered (+)'].sum(axis=0)
df_H2 = pd.DataFrame([[confirmed, deaths, recovered]],
columns=["Confirmed Cases", "Deaths", "Recovered"])
confirmed = f'{confirmed:,}'
deaths = f'{deaths:,}'