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dashboard.py
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dashboard.py
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#data visualization
import plotting as plt
#data retrieval
import Market_Data as md
#Create Dashboard
import dash
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from datetime import date
today = date.today().strftime("%Y-%m-%d")
import datetime
last_year = datetime.datetime.now().year - 1
this_month = datetime.datetime.now().month
this_day = datetime.datetime.now().day
today_last_year = datetime.datetime(last_year, this_month, this_day).strftime("%Y-%m-%d")
Dark_Mode = dbc.themes.CYBORG
Light_Mode = dbc.themes.LITERA
#Dashborad Layout
app = dash.Dash(external_stylesheets=[Dark_Mode], suppress_callback_exceptions=True)
app.title = "SIG Application"
app.layout = html.Div(
[
html.H1("SIG Application", style={'text-align': 'center'}),
dbc.Row(
[
dbc.Col(
className="Input",
children=[
dbc.InputGroup([
dbc.Input(
id="asset_input",
placeholder="name of asset here...",
value="avy"
),
dbc.InputGroupAddon(
dbc.Button("Enter",
id="asset_input_submit_btn"),
addon_type="append",
)
]),
],
width=10,
),
dbc.Col(
className="DatePicker",
children = [
dbc.Button(
"Dates",
id="Choose_Dates_Collapse_Btn",
block=True
),
dbc.Collapse(
dbc.Card(
dcc.DatePickerRange(
id="date_range",
is_RTL=True,
display_format="MMMM DD, YYYY",
start_date=today_last_year,
end_date=today,
with_portal=True,
)
),
id="date_range_collapse"
)
],
width=2,
)
],
justify="center",
style={'padding': '25px'}
),
html.Div(
children = [
dbc.Tabs(
id="tabs",
active_tab="candlesticks_plot",
children=[
dbc.Tab(label="Candlesticks Plot", tab_id="candlesticks_plot"),
dbc.Tab(label="Stats Plot", tab_id="stats_plot")
]
),
html.Div(id='tabs-content'),
],
style={'padding': '25px'}
),
html.Div(id='volume_and_adj_close_section', style={'padding': '25px'}),
html.Div(id='stats-table', style={'padding': '25px'}),
html.Footer("Created By Tyler Adam Martinez and Svenn Mivedor", style={'text-align':'center'})
]
)
#This will change the asset, therefore, changing the data on the plot, and depending on which tab is selected it will show you a different type of graph
@app.callback(
[
Output('tabs-content', 'children'),
Output('volume_and_adj_close_section', 'children'),
Output('stats-table', 'children'),
],
[
Input('asset_input_submit_btn', 'n_clicks'),
Input('asset_input', 'value'),
Input('date_range', 'start_date'),
Input('date_range', 'end_date'),
Input('tabs', 'active_tab')
]
)
def render_tabs_content(asset_input_submit_btn, asset_input, start_date, end_date, tab):
#If stock will retrive data from the stock API, if crypto then retrive data from the crypto API
asset_dataframe = md.get_stockData(asset_input, start_date, end_date)
asset_financial_dataframe = md.get_stockFinancials(asset_input)
if tab == 'candlesticks_plot':
fig_candlestick = plt.candlesticks_plot(asset_dataframe, plottitle=f"Price of {asset_input} over time")
volume_and_adj_close_section = [
dbc.Row(
[
dbc.Col(
dcc.Graph(figure=plt.volume_plot(asset_dataframe, plottitle=f"Trading volume of {asset_input} over time"))
),
dbc.Col(
dcc.Graph(figure=plt.plot(asset_dataframe.index, asset_dataframe['Adj Close'], plottitle=f"Adjusted Close Price of {asset_input} over time"))
)
]
)
]
stats_tables = [
html.Div (
children = [
dcc.Graph(figure=plt.stats_table(asset_dataframe, tabletitle=f"Stock stats table of {asset_input}"))
]
),
html.Br(),
html.Div (
children = [
dcc.Graph(figure=plt.financials_table(asset_financial_dataframe, tabletitle=f"Financial stats table of {asset_input}"))
]
)
]
return dcc.Graph(figure=fig_candlestick), volume_and_adj_close_section, stats_tables
elif tab == 'stats_plot':
fig_stock_plot = plt.stock_plot(asset_dataframe.index, asset_dataframe, plottitle=f"Price of {asset_input} over time")
stats_plot_div = [
html.Div(
id="stats_plot_div",
children=[
dcc.Graph(figure=fig_stock_plot),
]
)
]
stats_tables = [
html.Div (
children = [
dcc.Graph(figure=plt.stats_table(asset_dataframe, tabletitle=f"Stats table of {asset_input}"))
]
),
html.Br(),
html.Div (
children = [
dcc.Graph(figure=plt.financials_table(asset_financial_dataframe, tabletitle=f"Financial stats table of {asset_input}"))
]
)
]
return stats_plot_div, dcc.Graph(figure=plt.volume_plot(asset_dataframe, plottitle=f"Trading volume of {asset_input} over time")), stats_tables
#This will toggle the date picker from showing to hidden
@app.callback(
Output('date_range_collapse', 'is_open'),
Input('Choose_Dates_Collapse_Btn', 'n_clicks'),
State('date_range_collapse', 'is_open'),
)
def toggle_date_picker(n, is_open):
if n:
return not is_open
return is_open