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TickerMe.py
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TickerMe.py
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import streamlit as st
#
try:
import datetime
import matplotlib.pyplot as plt
import plotly.express as px
import yfinance as yf
from yahoo_fin import stock_info
from PIL import Image
import pandas as pd
from pandas_datareader import data as pdr
import plotly.graph_objs as ago
except ModuleNotFoundError as e:
st.error(
f"Looks like requirements are not installed: '{e}'. Run the following command to install requirements"
)
st.code(
"pip install streamlit matplotlib yfinance yahoo_fin pillow pandas"
)
else:
def Nifty50():
with st.sidebar:
st.write("Nifty50 Inputs")
symbol = st.selectbox("Select Symbol",stock_info.tickers_nifty50())
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol, start=a, end=b)
tickerData = yf.Ticker(symbol)
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title=' live share price evolution',yaxis_title='Stock Price (INR per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def DOW():
with st.sidebar:
st.write("DOW Inputs")
symbol = st.selectbox("Select Symbol",stock_info.tickers_dow())
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol, start=a, end=b)
tickerData = yf.Ticker(symbol)
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title=' live share price evolution',yaxis_title='Stock Price (USD per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def NSE():
with st.sidebar:
st.write("NSE Inputs")
tickers = pd.read_html('https://ournifty.com/stock-list-in-nse-fo-futures-and-options.html#:~:text=NSE%20F%26O%20Stock%20List%3A%20%20%20%20SL,%20%201000%20%2052%20more%20rows%20')[0]
tickers = tickers.SYMBOL.to_list()
for count in range(len(tickers)):
tickers[count] = tickers[count]
symbol = st.selectbox("Select Symbol", tickers)
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
# from_date = st.date_input(
# "From date", datetime.date.today() - datetime.timedelta(30)
# )
# to_date = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol + ".NS", start=a, end=b)
# Ticker information
tickerData = yf.Ticker(symbol + ".ns")
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title='live share price evolution',yaxis_title='Stock Price (INR per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def NASDAQ():
with st.sidebar:
st.write("NASDAQ Inputs")
symbol = st.selectbox("Select Symbol",stock_info.tickers_nasdaq())
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
# from_date = st.date_input(
# "From date", datetime.date.today() - datetime.timedelta(30)
# )
# to_date = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol, start=a, end=b)
tickerData = yf.Ticker(symbol)
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title='live share price evolution',yaxis_title='Stock Price (USD per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def SNP500():
with st.sidebar:
st.write("SNP500 Inputs")
symbol = st.selectbox("Select Symbol",stock_info.tickers_sp500())
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
# from_date = st.date_input(
# "From date", datetime.date.today() - datetime.timedelta(30)
# )
# to_date = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol, start=a, end=b)
tickerData = yf.Ticker(symbol)
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title='live share price evolution',yaxis_title='Stock Price (USD per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def DIV():
with st.sidebar:
st.write("DIV Inputs")
symbol = "NASDAQ"
segment = st.selectbox("Select Stock exchange", ["NASDAQ", "SNP500","DOW","NSE"])
if segment == "NASDAQ":
symbol = st.selectbox("Select Symbol",stock_info.tickers_nasdaq())
dd=stock_info.get_dividends(symbol)
elif segment == "SNP500":
symbol = st.selectbox("Select Symbol",stock_info.tickers_sp500())
dd=stock_info.get_dividends(symbol)
elif segment == "DOW":
symbol = st.selectbox("Select Symbol",stock_info.tickers_dow())
dd=stock_info.get_dividends(symbol)
else:
tickers = pd.read_html('https://ournifty.com/stock-list-in-nse-fo-futures-and-options.html#:~:text=NSE%20F%26O%20Stock%20List%3A%20%20%20%20SL,%20%201000%20%2052%20more%20rows%20')[0]
tickers = tickers.SYMBOL.to_list()
for count in range(len(tickers)):
tickers[count] = tickers[count]
symbol = st.selectbox("Select Symbol", tickers)
symbol = symbol + '.ns'
tickerDdd = yf.Ticker(symbol)
dd=tickerDdd.dividends
tickerData = yf.Ticker(symbol)
string_logo = '<img src=%s>' % tickerData.info['logo_url']
st.markdown(string_logo, unsafe_allow_html=True)
string_name = tickerData.info['longName']
st.header('**%s**' % string_name)
st.write(dd)
string_summary = tickerData.info['longBusinessSummary']
st.info(string_summary)
def crypto_display():
Cry = ['BTC-USD','ETH-USD','XMR-USD','USDT-USD','BNB-USD','USDC-USD','XRP-USD','SOL-USD','ADA-USD','LUNA1-USD','HEX-USD','AVAX-USD','DOGE-USD','UST-USD','BUSD-USD','SHIB-USD','WBTC-USD','NEAR-USD','MATIC-USE','CRO-USD','DAI-USD','LTC-USD','ATOM-USD','LINK-USD','UNI1-USD']
with st.sidebar:
st.write("Crypto Inputs")
# symbol = st.selectbox("Select Symbol",stock_info.get_top_crypto())
symbol = st.selectbox("Select Symbol",Cry)
a = st.date_input("From date", datetime.date.today() - datetime.timedelta(30))
b = st.date_input("To Date", datetime.date.today())
# from_date = st.date_input(
# "From date", datetime.date.today() - datetime.timedelta(30)
# )
# to_date = st.date_input("To Date", datetime.date.today())
cdata = yf.download(tickers=symbol, start=a, end=b)
tickerData = yf.Ticker(symbol)
string_name = tickerData.info['shortName']
st.header('**%s**' % string_name)
fig = ago.Figure()
fig.add_trace(ago.Candlestick(x=cdata.index,open=cdata['Open'],high=cdata['High'],low=cdata['Low'],close=cdata['Close'], name = 'market data'))
fig.update_layout(title=f'{symbol} live share price evolution',yaxis_title='Stock Price (USD per Shares)')
fig.update_xaxes(
rangeslider_visible=True,
rangeselector=dict(
buttons=list([
dict(count=15, label="15m", step="minute", stepmode="backward"),
dict(count=45, label="45m", step="minute", stepmode="backward"),
dict(count=1, label="HTD", step="hour", stepmode="todate"),
dict(count=3, label="3h", step="hour", stepmode="backward"),
dict(step="all")])))
st.write(fig)
string_summary = tickerData.info['description']
st.info(string_summary)
analysis_dict = {
"Nifty50": Nifty50,
"NSE Stock Delivery": NSE,
# __________________
"Crypto": crypto_display,
"NASDAQ": NASDAQ,
"SNP500": SNP500,
"DOW": DOW,
"DIVIDENDS": DIV,
}
with st.sidebar:
image = Image.open('logo.jpg')
st.image(image, caption='By TickerMe financial solutions')
st.markdown('<h1 style="float: left;">WITH LOVE :)</h1>',unsafe_allow_html=True,)
selected_analysis = st.radio("Select Analysis", list(analysis_dict.keys()))
st.write("---")
st.header(selected_analysis)
analysis_dict[selected_analysis]()