FetchingData
yfinance
Fetch historical prices and fundamentals from Yahoo Finance
pip install yfinance
yf.download(""AAPL"", start=""2022-01-01"", end=""2022-12-31"")
ts.get_daily(symbol='AAPL', outputsize='full')
web.DataReader(""AAPL"", ""yahoo"", start, end)
Fetch historical prices, fundamentals, and technical indicators
pip install alpha_vantage
Fetch historical and alternative financial data (FRED, World Bank, etc.)
pip install pandas-datareader
Connect to Interactive Brokers for data fetching and live trading
Perform mathematical operations on multi-dimensional arrays
Manipulate tabular and time-series data
Use technical indicators (RSI, Bollinger Bands, MACD, etc.)
Plot graphs, charts, and histograms
Create interactive visualizations
Apply ML algorithms like classification, clustering, and regression
model =sklearn.linear_model.LinearRegression()
Backtest and visualize trading strategies
Build and deploy machine learning models (e.g., neural networks)
tf.keras.Sequential([...])
High-performance backtesting and optimization using NumPy and Pandas
Build deep learning models (simplified interface for TensorFlow)
keras.Sequential([...])
Manual setup from
pip install numpy
np.mean(np.array([1, 2, 3]))
pd.DataFrame({'A': [1, 2, 3]})
pd.DataFrame({'A': [1, 2, 3]})
plt.plot([1, 2, 3], [4, 5, 6])
px.line(data_frame, x='x_col', y='y_col')
cerebro.addstrategy(MyStrategy)
portfolio = vbt.Portfolio.from_signals(close, entries, exits)
pip install pandas
pip install pandas
pip install matplotlib
pip install plotly
pip install scikit-learn
pip install backtrader
pip install tensorflow
pip install vectorbt
pip install keras
Pandas-DataReader
Pandas
AlphaVantage
IBridgePy
TA-Lib
Backtrader
NumPy
Matplotlib
Vectorbt
TensorFlow
Plotly
Scikit-learn
Keras
Category
Library
Purpose
Example Usage
Installation
DataManipulation
TechnicalAnalysis
Plotting & Visualization
Backtesting
MachineLearning