EXPO

import dash
from dash import html
from dash import dcc
from dash.dependencies import Input, Output
from dash import dash_table
import warnings
import yfinance as yf
import pandas as pd
import plotly.express as px

warnings.filterwarnings('ignore')  # Hide warnings

app = dash.Dash(__name__)

# Setting up the start date and end date
start = '2024-01-01'
end = '2024-07-01'

# Collecting data about Bitcoin from Yahoo Finance
btc = yf.download('BTC-USD', start, end)
btc.reset_index(inplace=True)
crypto = btc[['Date', 'Adj Close']]
crypto = crypto.rename(columns={'Adj Close': 'BTC'})
# Calculating the 7-day moving average for Bitcoin
crypto['BTC_7DAY_MA'] = crypto.BTC.rolling(7).mean()

# Collecting data about Ethereum from Yahoo Finance
eth = yf.download('ETH-USD', start, end)
eth.reset_index(inplace=True)
crypto["ETH"] = eth["Adj Close"]
# Calculating the 7-day moving average for Ethereum
crypto['ETH_7DAY_MA'] = crypto.ETH.rolling(7).mean()

# Collecting data about Dogecoin from Yahoo Finance
doge = yf.download('DOGE-USD', start, end)
doge.reset_index(inplace=True)
crypto["DOGE"] = doge["Adj Close"]
# Calculating the 7-day moving average for Dogecoin
crypto['DOGE_7DAY_MA'] = crypto.DOGE.rolling(7).mean()

# Calculating the correlation between different coins
crypto.set_index("Date", inplace=True)
correlation = crypto[['BTC', 'ETH', 'DOGE']].corr()

app.layout = html.Div([
    html.Div([
        html.H1(children='Analysing Crypto Charts',
                style={'textAlign': 'center', 'color': '#212529'})
    ], className='row'),
    dcc.Dropdown(
        id='dropdown',
        options=[
            {'label': 'Bitcoin', 'value': 'BTC'},
            {'label': 'Bitcoin MA', 'value': 'BTC_7DAY_MA'},
            {'label': 'Ethereum', 'value': 'ETH'},
            {'label': 'Ethereum MA', 'value': 'ETH_7DAY_MA'},
            {'label': 'Dogecoin', 'value': 'DOGE'},
            {'label': 'Dogecoin MA', 'value': 'DOGE_7DAY_MA'},
            {'label': 'ALL coins', 'value': 'ALL'},
            {'label': 'Correlation', 'value': 'CORREL'}
        ],
        value='BTC'),
    dcc.Graph(id='bar_plot'),
    html.Div([
        html.H1(children='Correlation',
                style={'textAlign': 'center', 'color': '#212529'})
    ], className='row'),
    html.Div([
        html.P(
            children="Correlation shows the strength of a relationship between two variables and is expressed numerically by the correlation coefficient. The correlation coefficient's values range between -1.0 and 1.0. A perfect positive correlation means that the correlation coefficient is exactly 1. This implies that as one security moves, either up or down, the other security moves in lockstep, in the same direction. A perfect negative correlation means that two assets move in opposite directions, while a zero correlation implies no linear relationship at all.",
            style={'textAlign': 'center', 'color': '#212529'})
    ], className='row'),
    html.Div([
        dash_table.DataTable(id='table',
                             columns=[{"name": i, "id": i} for i in correlation.columns],
                             data=correlation.to_dict('records'))
    ], className='row')
])


@app.callback(Output(component_id='bar_plot', component_property='figure'),
              [Input(component_id='dropdown', component_property='value')])
def graph_update(dropdown_value):
    print(dropdown_value)
    if dropdown_value == "BTC":
        fig = px.line(crypto, y=['BTC'])
    elif dropdown_value == "BTC_7DAY_MA":
        fig = px.line(crypto, y=['BTC_7DAY_MA'])
    elif dropdown_value == "ETH":
        fig = px.line(crypto, y=['ETH'])
    elif dropdown_value == "ETH_7DAY_MA":
        fig = px.line(crypto, y=['ETH_7DAY_MA'])
    elif dropdown_value == "DOGE":
        fig = px.line(crypto, y=['DOGE'])
    elif dropdown_value == "DOGE_7DAY_MA":
        fig = px.line(crypto, y=['DOGE_7DAY_MA'])
    elif dropdown_value == "ALL":
        fig = px.line(crypto, y=['BTC', 'ETH', 'DOGE'])
    else:
        fig = px.imshow(correlation,
                        text_auto=True,  # Adds text annotations with the correlation values
                        color_continuous_scale='RdBu_r',  # Use a color scale that contrasts well
                        aspect="auto")  # Adjust the aspect ratio for better readability
        fig.update_layout(
            title='Correlation Heatmap',
            xaxis_title='Cryptocurrencies',
            yaxis_title='Cryptocurrencies',
            coloraxis_showscale=True,  # Show color scale
            font=dict(size=12),
            margin=dict(l=40, r=40, t=40, b=40)  # Adjust margins for better layout
        )
    fig.update_layout(title='Crypto Prices Over Time' if dropdown_value != "CORREL" else 'Correlation Heatmap',
                      xaxis_title='Dates' if dropdown_value != "CORREL" else '',
                      yaxis_title='Prices' if dropdown_value != "CORREL" else '')
    return fig


app.run_server(debug=True, host='0.0.0.0')