Hi Guys,
I am struggling to visualize the number with dot separator for thousands within the body of my cards. Also ,
I dont why but I get parenthesis.
my code is reading data from an excel and pass them to a pandas dataframe. The body of the Cards are calculated.
Thanks for your support.
here my code:
from dash import Dash, dcc, html, Input, Output
import plotly.express as px
import pandas as pd
import plotly.graph_objects as go
import dash_bootstrap_components as dbc
import datetime
import pandas_datareader.data as web
#from openpyxl.workbook import web
#Definizione Variabili (KPI & KRI)
PnL= pd.read_excel(“PnL.xlsx”)
Somma_PnL=PnL[‘PnL’].sum()
Somma_Exposure=PnL[‘Exposure_Mwh’].sum()
Somma_VaR=PnL[‘VaR’].sum()
#CARD
card = dbc.Card(
[
dbc.CardHeader(“PnL”),
dbc.CardBody(
[
html.H1(“”, className=“card-title”),
html.H3(f’{round(Somma_PnL),1 } €’, style={‘font-size’: ‘20px’}),
]
),
],
body=True,
style={"width": "12rem"},
)
card1 = dbc.Card(
[
dbc.CardHeader(“Exposure”),
dbc.CardBody(
[
html.H1(“”, className=“card-title”),
html.H3(f’{round(Somma_Exposure),1 } MWh’, style={‘font-size’: ‘20px’}),
]
),
],
body=True,
style={"width": "12rem"})
card2 = dbc.Card(
[
dbc.CardHeader(“VaR”),
dbc.CardBody(
[
html.H1(“”, className=“card-title”),
html.H3(f’{round(Somma_VaR),1 } €’, style={‘font-size’: ‘20px’}),
]
),
],
body=True,
style={"width": "12rem"},
)
#DATI CAPTURING GAS
df = pd.read_excel(“Gas-prices-728.xlsx”,sheet_name=‘PSV MW’,usecols=[“Data”,“BoM”,“BoW”,“Day ahead”,“WDNW”,“Month ahead”])
dff= pd.read_excel(“Gas-prices-728.xlsx”,sheet_name=‘TTF MW’,usecols=[“Data”,“BoM”,“BoW”,“Day ahead”,“WDNW”,“Month ahead”])
dfff=pd.merge(df,dff[[“Data”,“BoM”,“BoW”,“Day ahead”,“WDNW”,“Month ahead”]],on=‘Data’,how=‘right’)
dfff.head()
dfff.rename(columns={‘BoM_x’: ‘BoM_PSV’, ‘Day ahead_x’: ‘Day ahead_PSV’,‘WDNW_x’:‘WDNW_PSV’,‘Month ahead_x’:‘Month ahead_PSV’,‘BoM_y’: ‘BoM_TTF’, ‘Day ahead_y’: ‘Day ahead_TTF’,‘WDNW_y’:‘WDNW_TTF’,‘Month ahead_y’:‘Month ahead_TTF’}, inplace=True)
DATA E ANNO
data_excel=dfff[‘Data’]
anno=data_excel.dt.year
dfff[“Anno1”]=anno
dfff.rename(columns={‘Anno1’:‘Anno1’,‘BoM_x’: ‘BoM_PSV’, ‘Day ahead_x’: ‘Day ahead_PSV’,‘WDNW_x’:‘WDNW_PSV’,‘Month ahead_x’:‘Month ahead_PSV’,‘BoM_y’: ‘BoM_TTF’, ‘Day ahead_y’: ‘Day ahead_TTF’,‘WDNW_y’:‘WDNW_TTF’,‘Month ahead_y’:‘Month ahead_TTF’}, inplace=True)
Test= dfff.query(‘Anno1==2023’)
Test.info()
print(Test[:10])
app = Dash(name, external_stylesheets=[dbc.themes.SPACELAB,dbc.icons.BOOTSTRAP],
meta_tags=[{'name': 'viewport',
'content': 'width=device-width, initial-scale=1.0'}]
)
server = app.server
app.layout= dbc.Container([
RIGA 0 CARDS
dbc.Row([
dbc.Col(card),
dbc.Col(card1),
dbc.Col(card2),
dbc.Col(html.H1("Market Trend",
className='text-center text-primary mb-4'),
width=10),
]),
#RIGA 1 GRAFICI MERCATO
dbc.Row([
COLONNA 1
dbc.Col([
(html.Div(
[html.H4("Gas Market Spot"),
dcc.Graph(id="time-series-chart"),
html.P("Select Product:"),
dcc.Dropdown(
id="pippo",
options=["BoM_PSV", "Day ahead_PSV","WDNW_PSV","Month ahead_PSV","BoM_TTF", "Day ahead_TTF","WDNW_TTF","Month ahead_TTF"],
multi=True,
value="Day ahead_PSV",
clearable=False,
),
]
)
)]),
COLONNA 2
dbc.Col([
(html.Div(
[html.H4("Power Market Spot"),
dcc.Graph(id="power_mkt"),
html.P("Select Product:"),
dcc.Dropdown(
id="pw",
options=["BoM_PSV", "Day ahead_PSV","WDNW_PSV","Month ahead_PSV","BoM_TTF", "Day ahead_TTF","WDNW_TTF","Month ahead_TTF"],
multi=True,
value="Day ahead_PSV",
clearable=False,
)
])
)])
])
])
@app.callback(
Output(‘time-series-chart’,‘figure’),
Input(‘pippo’, ‘value’)
)
def display_time_series(pippo):
fig = px.line(Test, x=“Data”, y=pippo)
fig.update_xaxes(rangeslider_visible=True)
return fig
@app.callback(
Output(‘power_mkt’,‘figure’),
Input(‘pw’, ‘value’)
)
def display_time_series(pw):
fig2= px.line(Test, x=“Data”, y=pw)
return fig2
if name == “main”:
app.run_server(debug=True)
