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import flag
import pandas as pd
import numpy as np
from countryinfo import CountryInfo
from stocksymbol import StockSymbol
import yfinance as yf
import plotly.graph_objects as go
from dash import Dash, dcc, html, Input, Output, dash_table, callback
import dash
from dash.dependencies import Input, Output
from dash.exceptions import PreventUpdate
dash.register_page(__name__)
api_key = '724b3358-1685-4659-92ea-1e445f283e30'
ss = StockSymbol(api_key)
market_list = ss.market_list
df = pd.DataFrame.from_dict(market_list)
df = df[['abbreviation', 'index']].copy()
df = df[df['index'].map(lambda x: len(x)) > 0]
df['country'] = df['abbreviation'].apply(lambda x: CountryInfo(x).name().title() if x != 'eu' else 'Europe')
df['iso3'] = df['abbreviation'].apply(lambda x: CountryInfo(x).iso(3) if x != 'eu' else 'EUR')
df['iso2'] = df['abbreviation'].apply(lambda x: CountryInfo(x).iso(2) if x != 'eu' else 'EU')
df['flags'] = df['iso2'].apply(lambda x: flag.flag(x))
df['lat'] = df['abbreviation'].apply(lambda x: CountryInfo(x).capital_latlng()[0] if x != 'eu' else 49.845556)
df['long'] = df['abbreviation'].apply(lambda x:CountryInfo(x).capital_latlng()[1] if x != 'eu' else 9.906111)
df.loc[df['iso3'] == 'HKG', 'lat'] = 22.278333
df.loc[df['iso3'] == 'HKG', 'long'] = 114.174444
customdata = [df['country'], df['flags']]
hovertemplate = ('<br>' + customdata[0] + ' ' + customdata[1] + '<br>' + '<extra></extra>')
fig = go.Figure(data=go.Scattergeo(
lon = df['long'],
lat = df['lat'],
text = df['flags'] + '<br>' + '<b>' + df['iso3'] + '</b>',
mode = 'text+markers',
marker = dict(size=40, color='darkorange', opacity=0.8)
))
fig.update_traces(textfont_size=13, customdata=customdata, hovertemplate=hovertemplate)
fig.update_geos(projection=dict(type = 'orthographic'), visible=False, resolution=110, showcountries=True, countrycolor='darkorange')
fig.update_layout(title=dict(text='EXPLORE LISTED COMPANIES BY INDEX', font=dict(color='darkorange')), title_x=0.5, font=dict(color='White'), clickmode='event+select', height=900)
country = 'us'
df2 = df.loc[df['abbreviation'] == country].copy()
df3 = pd.DataFrame.from_dict(df2['index'].values[0])
df3['country'] = df2['iso3'].iloc[0] + ' ' + df2['flags'].iloc[0]
df3 = df3.rename({'id': 'id_index'}, axis=1)
df3 = df3[['country', 'id_index' , 'name']]
df3 = df3.sort_values(['id_index', 'name'], ascending = [True, True])
ticker = 'MMM'
index = 'DJA'
comp = yf.Ticker(ticker)
hist = comp.history(period='1y')
symbol_list = ss.get_symbol_list(index=index)
df_inx = pd.DataFrame.from_dict(symbol_list)
df_inx.drop(['shortName', 'market'], axis=1, inplace=True, errors='ignore')
df_inx = df_inx.sort_values(['longName', 'symbol'], ascending = [True, True])
df_inx = df_inx.reset_index(drop=True)
df_inx['id'] = df_inx.index
@callback([Output(component_id='table-index', component_property='data'),
Output(component_id='table-index', component_property='columns')],
[Output('table-company', 'data'), Output('table-company', 'columns')], [Output('company-evolution', 'figure')],
[Input('map-flags', 'selectedData')], [Input('table-index', 'selected_rows')], [Input('table-company', 'selected_row_ids')])
def display_selected_data(selectedData, selected_rows, selected_row_ids):
global df
if selectedData:
index = selectedData['points'][0]['pointIndex']
country = df.iloc[index]['abbreviation']
else:
country = 'us'
df2 = df.loc[df['abbreviation'] == country].copy()
df3 = pd.DataFrame.from_dict(df2['index'].values[0])
df3['country'] = df2['iso3'].iloc[0] + ' ' + df2['flags'].iloc[0]
df3 = df3.rename({'id': 'id_index'}, axis=1)
df3 = df3[['country', 'id_index' , 'name']]
df3 = df3[df3['id_index'] != 'HSI:HSI']
df3 = df3.sort_values(['id_index', 'name'], ascending = [True, True])
columns = [{'name': col, 'id': col} for col in df3.columns]
data = df3.to_dict(orient='records')
if selected_rows:
#index = selected_rows
if selected_rows[0] > len(df3)-1:
selected_rows = [0]
index = df3['id_index'].iloc[selected_rows[0]].split(':')[1]
else:
index = df3['id_index'].iloc[0].split(':')[1]
symbol_list = ss.get_symbol_list(index=index)
df_inx = pd.DataFrame.from_dict(symbol_list)
if not df_inx.empty:
df_inx.drop(['shortName', 'market'], axis=1, inplace=True, errors='ignore')
df_inx = df_inx.sort_values(['longName', 'symbol'], ascending = [True, True])
df_inx = df_inx.reset_index(drop=True)
df_inx['id'] = df_inx.index
columns2 = [{'name': col, 'id': col} for col in df_inx.columns[:-1]]
data2 = df_inx.to_dict(orient='records')
if selected_row_ids:
if selected_row_ids[0] > len(df_inx)-1:
selected_row_ids = [0]
ticker = df_inx['symbol'].iloc[selected_row_ids[0]]
comp_name = df_inx['longName'].iloc[selected_row_ids[0]]
else:
ticker = df_inx['symbol'].iloc[0]
comp_name = df_inx['longName'].iloc[0]
comp = yf.Ticker(ticker)
hist = comp.history(period='1y')
fig2 = go.Figure(data=go.Scatter(
x = hist.index,
y = hist['Close'],
mode = 'lines',
line = dict(color='firebrick', width=3)
))
fig2.update_layout(
xaxis=dict(
showline=False,
showgrid=True,
showticklabels=True,
gridcolor='WhiteSmoke',
tickfont=dict(
size=12,
color='darkorange',
),
),
yaxis=dict(
showline=False,
showgrid=True,
showticklabels=True,
gridcolor='WhiteSmoke',
tickfont=dict(
size=12,
color='darkorange',
),
),
showlegend=False,
plot_bgcolor='white',
title=comp_name,
font=dict(
size=12,
color='darkorange'
)
)
else:
raise PreventUpdate
return data, columns, data2, columns2, fig2
layout = html.Div([
html.Div([
dcc.Graph(id='map-flags',
figure=fig, style={'width': '900px', 'height': '900px'})], style={'display': 'inline-block'}),
html.Div([
dcc.Graph(id='company-evolution',
figure=fig, style={'width': '900px', 'height': '600px'})], style={'display': 'inline-block'}),
html.Div([
html.Label('INDEXES', style={'fontWeight': 'bold', 'color': 'darkorange', 'fontSize': 12, 'fontFamily': 'Arial, Helvetica, sans-serif'}),
dash_table.DataTable(id='table-index',
style_header={'backgroundColor': 'darkorange',
'color': 'white',
'fontWeight': 'bold', 'fontFamily': 'Arial, Helvetica, sans-serif', 'fontSize': 12
},
style_data={'backgroundColor': 'white',
'color': 'grey'
},
fill_width=False,
editable=True,
filter_action='native',
filter_options={'case': 'insensitive'},
sort_action='native',
sort_mode='multi',
#column_selectable='single',
row_selectable='single',
#selected_columns=[],
selected_rows=[],
#selected_row_ids=[],
#fixed_rows={'headers':True, 'data':1},
page_action='none',
style_table={'height': '900px', 'width': '700px', 'overflowY': 'auto'}
#page_current=0,
#page_size=10
)], style={'display': 'inline-block'}),
html.Div([
html.Label('COMPANIES', style={'fontWeight': 'bold', 'color': 'darkorange', 'fontSize': 12, 'fontFamily': 'Arial, Helvetica, sans-serif'}),
dash_table.DataTable(id='table-company',
style_header={'backgroundColor': 'darkorange',
'color': 'white',
'fontWeight': 'bold', 'fontFamily': 'Arial, Helvetica, sans-serif', 'fontSize': 12
},
style_data={'backgroundColor': 'white',
'color': 'grey'
},
fill_width=False,
editable=True,
filter_action='native',
filter_options={'case': 'insensitive'},
sort_action='native',
sort_mode='multi',
#column_selectable='single',
row_selectable='single',
#selected_columns=[],
selected_rows=[],
selected_row_ids=[],
#fixed_rows={'headers': True},
page_action='none',
style_table={'height': '900px', 'width': '900px', 'overflowY': 'auto'}
#page_current=0,
#page_size=10
)], style={'display': 'inline-block'}),
])
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