# Python for Finance

# useful links

# Python for finance

libraries

jupyterlab
notebook
numpy
pandas
pandas-datareader
beautifulsoup4
scikit-learn / sklearn
Plotly

import plotly.graph_objects as go
import pandas as pd


def create_chart(df):
   fig = go.Figure(data=[go.Candlestick(x=df['Date'],
                   open=df['Open'],
                   high=df['High'],
                   low=df['Low'],
                   close=df['Close'])])
   fig.update_layout(xaxis_rangeslider_visible=False)
   fig.show()


if __name__ == '__main__':
   create_chart(pd.read_csv('Shell.csv'))

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import datetime as dt
import matplotlib.pyplot as plt
from matplotlib import style
import pandas as pd
import pandas_datareader.data as web
import mplfinance as mpf



style.use('ggplot')

start = dt.datetime(2020, 4, 1)
end = dt.datetime(2020, 5, 1)

df1 = web.DataReader('RDS-A', 'yahoo', start, end)      # Royal Dutch Shell plc (RDS-A) - NYSE
df2 = web.DataReader('DAL', 'yahoo', start, end)        # Delta Air Lines, Inc. (DAL) - NYSE
df3 = web.DataReader('HAL', 'yahoo', start, end)        # Halliburton Company (HAL) - NYSE

# df1_csv = pd.read_csv('Shell.csv', parse_dates=True, index_col=0)
# print('From CSV - Royal Dutch Shell plc (RDS-A) - NYSE - NYSE Delayed Price. Currency in USD')
# # df1.to_csv('Shell.csv')
# # df2.to_csv('Delta.csv')
# # df3.to_csv('Halliburton.csv')
# print(df1_csv.head())

print('Royal Dutch Shell plc (RDS-A) - NYSE - NYSE Delayed Price. Currency in USD')
print(df1.head())        # get the first ones
print(df1.head(6))
print(df1.tail())        # get the last ones

# df1.plot()
# plt.show()

mpf.plot(df1, type='candle')

print('Delta Air Lines, Inc. (DAL) - NYSE - NYSE Delayed Price. Currency in USD')
print(df2.head())        # get the first ones
print(df2.tail())        # get the last ones

print('Halliburton Company (HAL) - NYSE - NYSE Delayed Price. Currency in USD')
print(df3.head())        # get the first ones
print(df3.tail())        # get the last ones

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# Python for Finance

# useful links

# Python for finance

# Excluding weekends from the graph

# Numpy

# NumPy Arrays