@Article{jbd.2019.08274,
AUTHOR = {Yue Cai, Zeying Song, Guang Sun, Jing Wang, Ziyi Guo, Yi Zuo, Xiaoping Fan, Jianjun Zhang, Lin Lang},
TITLE = {On Visualization Analysis of Stock Data},
JOURNAL = {Journal on Big Data},
VOLUME = {1},
YEAR = {2019},
NUMBER = {3},
PAGES = {135--144},
URL = {http://www.techscience.com/jbd/v1n3/38304},
ISSN = {2579-0056},
ABSTRACT = {Big data technology is changing with each passing day, generating massive 
amounts of data every day. These data have large capacity, many types, fast growth, and 
valuable features. The same is true for the stock investment market. The growth of the 
amount of stock data generated every day is difficult to predict. The price trend in the 
stock market is uncertain, and the valuable information hidden in the stock data is 
difficult to detect. For example, the price trend of stocks, profit trends, how to make a 
reasonable speculation on the price trend of stocks and profit trends is a major problem 
that needs to be solved at this stage. This article uses the Python language to visually 
analyze, calculate, and predict each stock. Realize the integration and calculation of stock 
data to help people find out the valuable information hidden in stocks. The method 
proposed in this paper has been tested and proved to be feasible. It can reasonably extract, 
analyze and calculate the stock data, and predict the stock price trend to a certain extent.},
DOI = {10.32604/jbd.2019.08274}
}