ExempleYfinanceChargementDonnees.py

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 11 08:19:02 2021

@author: vango
"""

import yfinance as yf

msft = yf.Ticker("MSFT")

# get stock info
msft.info

# get historical market data
hist = msft.history(period="max")

print(hist.head())

# show actions (dividends, splits)
msft.actions

# show dividends
msft.dividends

# show splits
msft.splits

# show financials
msft.financials
msft.quarterly_financials

# show major holders
msft.major_holders

# show institutional holders
msft.institutional_holders

# show balance sheet
msft.balance_sheet
msft.quarterly_balance_sheet

# show cashflow
msft.cashflow
msft.quarterly_cashflow

# show earnings
msft.earnings
msft.quarterly_earnings

# show sustainability
msft.sustainability

# show analysts recommendations
msft.recommendations

# show next event (earnings, etc)
msft.calendar

# show ISIN code - *experimental*
# ISIN = International Securities Identification Number
msft.isin

# show options expirations
msft.options

# get option chain for specific expiration
opt = msft.option_chain('2021-08-27')
# data available via: opt.calls, opt.puts


# Import yfinance package
import yfinance as yf

# Set the start and end date
start_date = '1990-01-01'
end_date = '2021-07-12'

# Set the ticker
ticker = 'AMZN'

# Get the data
data = yf.download(ticker, start_date, end_date)

# Print 5 rows
print(data.tail())

# Import matplotlib for plotting
import matplotlib.pyplot as plt

# Plot adjusted close price data
data['Adj Close'].plot()
plt.show()

# Plot the adjusted close price
data['Adj Close'].plot(figsize=(10, 7))

# Define the label for the title of the figure
plt.title("Adjusted Close Price of %s" % ticker, fontsize=16)

# Define the labels for x-axis and y-axis
plt.ylabel('Price', fontsize=14)
plt.xlabel('Year', fontsize=14)

# Plot the grid lines
plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5)

# Show the plot
plt.show()

import pandas as pd

# Set the start and end date
start_date = '1990-01-01'
end_date = '2021-07-12'

# Define the ticker list
tickers_list = ['AAPL', 'IBM', 'MSFT', 'WMT']

# Create placeholder for data
data = pd.DataFrame(columns=tickers_list)

# Fetch the data
for ticker in tickers_list:
    data[ticker] = yf.download(ticker, 
                               start_date,
                               end_date)['Adj Close']
    
# Print first 5 rows of the data
print(data.head())

# Plot all the close prices
data.plot(figsize=(10, 7))

# Show the legend
plt.legend()

# Define the label for the title of the figure
plt.title("Adjusted Close Price", fontsize=16)

# Define the labels for x-axis and y-axis
plt.ylabel('Price', fontsize=14)
plt.xlabel('Year', fontsize=14)

# Plot the grid lines
plt.grid(which="major", color='k', linestyle='-.', linewidth=0.5)
plt.show()


intraday_data = yf.download(tickers="MSFT",
                            period="5d",
                            interval="1m",
                            auto_adjust=True)
intraday_data.head()