tycselen 0.0.1

download data of tycselen

• easy to use as most of the data returned are pandas DataFrame objects

• can be easily saved as csv, excel or json files

• can be inserted into MySQL or Mongodb

Target Users

• financial market analyst of China

• learners of financial data analysis with pandas/NumPy

• people who are interested in China financial data

Installation

pip install tycselen

Upgrade

pip install tycselen –upgrade

Quick Start

gn=crawl.BaiduNews()
gn.update_info()
print(gn.author_wx)
df_search = gn.search_news('中国银行 电子银行',day=-3, pn=None)
print(df_search)
df_search.to_excel('./search.xlsx')
df_detail = gn.news_detail(top=5)
print(df_detail)
df_detail.to_excel('./detail.xlsx')

return:

            open    high   close     low     volume    p_change  ma5
date
2012-01-11   6.880   7.380   7.060   6.880   14129.96     2.62   7.060
2012-01-12   7.050   7.100   6.980   6.900    7895.19    -1.13   7.020
2012-01-13   6.950   7.000   6.700   6.690    6611.87    -4.01   6.913
2012-01-16   6.680   6.750   6.510   6.480    2941.63    -2.84   6.813
2012-01-17   6.660   6.880   6.860   6.460    8642.57     5.38   6.822
2012-01-18   7.000   7.300   6.890   6.880   13075.40     0.44   6.788
2012-01-19   6.690   6.950   6.890   6.680    6117.32     0.00   6.770
2012-01-20   6.870   7.080   7.010   6.870    6813.09     1.74   6.832