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:,}'