GitHub仓库：https://github.com/krishnaik06/Stock-Price-Prediction-using-Keras-and-Recurrent-Neural-...
fromprophet.plotimportplot_plotly fromplotlyimportgraph_objsasgo START ="2015-01-01" TODAY = date.today().strftime("%Y-%m-%d") st.title('Stock Forecast App') stocks = ('MSFT',"TSLA",'GOOG','AAPL',"NVDA") selected_stock = st.selectbox...
代码改进示范 我们可以使用Plotly库将股票数据绘制成动态图表。 importplotly.graph_objectsasgofrombsedata.bseimportBSE b=BSE(update_codes=True)data=b.topGainers()fig=go.Figure(data=[go.Table(header=dict(values=["Stock Code","Company Name","Current Price","Change","Pct Change"]),cells=dict(val...
Stock-Prediction-Models - Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations. tda-api - Gather data and trade equities, options, and ETFs via TDAmeritrade. 风险分析Risk Analysis pyfolio - 计算投资组合和交易策略的业绩指标 empyrical - 计算常...
pynance - PyNance is open-source software for retrieving, analysing and visualizing data from stock and derivatives markets. tia - Toolkit for integration and analysis. hasura/base-python-dash - Hasura quickstart to deploy Dash framework. Written on top of Flask, Plotly.js, and React.js, Dash...
例如,再用plotly 可视化引擎,可以实时做出漂亮的波动率曲面。 参见:阿岛格:基于人工智能的量化投资系统(9)数据指标及可视化 的第3, 以及本文最后的视频。 四、其他的库 还有上百个好的工具和库,请参见:阿岛格:当前国内的程序化交易量化交易,有哪些好的框架和工具?,里面有链接, 可以自己试验和选择。 五、特别...
from prophet.plotimportplot_plotly from plotlyimportgraph_objsasgoSTART="2015-01-01"TODAY=date.today().strftime("%Y-%m-%d")st.title('Stock Forecast App')stocks=('MSFT',"TSLA",'GOOG','AAPL',"NVDA")selected_stock=st.selectbox('Select dataset for prediction',stocks)n_years=st.slider('Ye...
fromprophet.plotimportplot_plotly fromplotlyimportgraph_objsasgo START="2015-01-01" TODAY=date.today.strftime("%Y-%m-%d") st.title('StockForecastApp') stocks=('MSFT',"TSLA",'GOOG','AAPL',"NVDA") selected_stock=st.selectbox('Selectdatasetforprediction',stocks) ...
fromprophet.plotimportplot_plotly fromplotlyimportgraph_objsasgo START ='2015-01-01' TODAY = date.today().strftime('%Y-%m-%d') st.title('Stock Forecast App') stocks = ('MSFT','TSLA','GOOG','AAPL','NVDA') selected_stock = st.selectbox('Select dataset for prediction', stocks) ...
prophet import Prophet# 导入Prophet的Plotly绘图接口和Plotly图形对象from prophet.plot import plot_plotlyfrom plotly import graph_objs as go# 设置预测的起始日期和当前日期START = "2015-01-01"TODAY = date.today().strftime("%Y-%m-%d")# 使用Streamlit创建应用标题st.title('Stock Forecast App')# ...