marketwatchdata

retrieve data from MarketWatch.com


Keywords
stock, option, futures, fund, bond, index, air, finance, spider, quant, quantitative, investment, trading, algotrading, data
License
MIT
Install
pip install marketwatchdata==0.0.16

Documentation

marketwatchdata

pypi downloads documentation status code style: black actions status mit licence

overview

marketwathdata retrieve datas from marketwatch.com.

installation

general

pip install marketwatchdata --upgrade

china

pip install marketwatchdata -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com  --upgrade

test

import marketwatchdata as mw

print(mw.__version__)

usage

data

code

import marketwatchdata as mw

df = mw.ohlc('stock/us/xnas/aapl', 'p1d', 'p1y')
print(df)

output

                open     high      low   close       volume
date
2022-07-25  154.010  155.040  152.280  152.95   53623953.0
2022-07-26  152.265  153.085  150.800  151.60   55138688.0
2022-07-27  152.580  157.330  152.160  156.79   78620688.0
2022-07-28  156.980  157.640  154.410  157.35   81378727.0
2022-07-29  161.240  163.630  159.500  162.51  101786898.0
...             ...      ...      ...     ...          ...
2023-07-17  191.900  194.320  191.810  193.99   50520160.0
2023-07-18  193.350  194.330  192.415  193.73   48353770.0
2023-07-19  193.100  198.230  192.650  195.10   80507320.0
2023-07-20  195.090  196.470  192.495  193.13   59581199.0
2023-07-21  194.100  194.970  191.230  191.94   71951683.0

[250 rows x 5 columns]

plot

code

import marketwatchdata as mw
import mplfinance as mpf  # please install mplfinance as follows: pip install mplfinance

df = mw.ohlc('stock/us/xnas/aapl', 'p1d', 'p1y')
mpf.plot(df, type='candle', mav=(3, 6, 9), volume=true, show_nontrading=false)

output

acknowledgement

thanks for the data provided by marketwatch;