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gauges working

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This commit is contained in:
Alagris 2021-06-21 11:37:44 +02:00
parent 13a51f0365
commit e5df1f30ac
1 changed files with 56 additions and 9 deletions
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65
finance.py
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@ -6,7 +6,11 @@ import plotly.express as px
import yfinance as yf
from dash.dependencies import Input, Output
import plotly.graph_objects as go
import numpy as np
import pandas as pd
import datetime
import time
# Load data
stock_list = ['MMM', 'ABT', 'ABBV', 'ABMD', 'ACN', 'ATVI', 'ADBE', 'AMD', 'AAP', 'AES', 'AFL', 'A', 'APD', 'AKAM',
'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'LNT', 'ALL', 'GOOGL', 'GOOG', 'MO', 'AMZN', 'AMCR', 'AEE',
@ -57,6 +61,7 @@ to_time = None
# Initialize the app
app = dash.Dash(__name__)
app.config.suppress_callback_exceptions = True
stock_info_in_time_period_df = pd.DataFrame(columns=stock_list, index=["średnia", "cena", "dywidenda", "wolatylność"])
def make_gauge(title, min_v, value, max_v):
@ -116,7 +121,15 @@ app.layout = html.Div(
style={'color': '#1E1E1E'}),
html.P('Wybierz przedział czasu by policzyć średnie i wachania'),
dcc.Graph(id='average_gauge'),
dcc.Graph(id='volatility_gauge')
dcc.Graph(id='volatility_gauge'),
dash_table.DataTable(
id='info_in_time_period',
style_header={'backgroundColor': 'rgb(30, 30, 30)'},
style_cell={
'backgroundColor': 'rgb(50, 50, 50)',
'color': 'white'
},
)
]),
html.Div(className='eight columns div-for-charts bg-grey',
children=[
@ -159,21 +172,55 @@ def update_table(selected_dropdown_value):
return data, columns
@app.callback([Output('average_gauge', 'figure'), Output('volatility_gauge', 'figure')],
average_gauge = make_gauge('średnia', 0, 0, 400)
volatility_gauge = make_gauge('wolatylność', 0, 0, 400)
def round_to_nearest_weekday(date):
if isinstance(date,pd.Timestamp):
if date.dayofweek > 5:
date += datetime.timedelta(days=8-date.dayofweek)
assert date.dayofweek <= 5
return date
elif isinstance(date, str):
if '.' in date:
date = datetime.datetime.strptime(date, "%Y-%m-%d %H:%M:%S.%f")
elif ':' in date:
date = datetime.datetime.strptime(date, "%Y-%m-%d %H:%M:%S")
else:
date = datetime.datetime.strptime(date, "%Y-%m-%d")
if date.isoweekday() > 5:
date += datetime.timedelta(days=8-date.isoweekday())
assert date.isoweekday() <= 5
return date
@app.callback([Output('average_gauge', 'figure'),
Output('volatility_gauge', 'figure'),
Output('info_in_time_period', 'data')],
Input('timeseries', 'relayoutData'))
def change_time_period(selectedData):
global from_time
global to_time
global average_gauge
global volatility_gauge
global stock_info_in_time_period_df
if selectedData is not None:
if selectedData.get('autosize'):
from_time = selected_stock_in_table_df.index.min()
to_time = selected_stock_in_table_df.index.max()
else:
if "xaxis.range[0]" in selectedData and "xaxis.range[1]" in selectedData:
from_time = selectedData["xaxis.range[0]"]
to_time = selectedData["xaxis.range[1]"]
average_gauge = make_gauge('średnia', 0, 290, 400)
volatility_gauge = make_gauge('wolatylność', 0, 133, 400)
return average_gauge, volatility_gauge
else:
from_time = selected_stock_in_table_df.index.min()
to_time = selected_stock_in_table_df.index.max()
from_time = round_to_nearest_weekday(from_time)
to_time = round_to_nearest_weekday(to_time)
time_period = selected_stock_in_table_df.loc[from_time:to_time]
mean = time_period.mean(axis=0)
std = time_period.std(axis=0)
# TODO: oblicz stock_info_in_time_period_df tutuaj !!!
average_gauge = make_gauge('średnia', 0, mean['Close'], 400)
volatility_gauge = make_gauge('wolatylność', 0, std['Close'], 400)
return average_gauge, volatility_gauge, stock_info_in_time_period_df.T.to_dict('records')
if __name__ == '__main__':