A股涨跌幅直方图

import tushare as ts

%pylab inline

import numpy as np
import holoviews as hv
hv.extension('matplotlib')

def get_hist(date,attr):
    df = ts.get_day_all(date)
    start = df[attr].describe()['min']
    stop = df[attr].describe()['max']
    bin_array = np.linspace(start=start, stop=stop, num=50)
    return df[attr].hist(bins=bin_array)

get_hist('2018-12-03','p_change')

df = ts.get_day_all('2018-12-03')
df1 = ts.get_day_all('2018-12-04')
df2 = ts.get_day_all('2018-12-05')

df = df.query('-10.01<p_change<10.01')
df1 = df1.query('-10.01<p_change<10.01')
df2 = df2.query('-10.01<p_change<10.01')

df['real_change'] = (df.price-df.open)/df.price*100
df = df.query('real_change<30')
df1['real_change'] = (df1.price-df1.open)/df1.price*100
df1 = df1.query('real_change<30')
df2['real_change'] = (df2.price-df2.open)/df2.price*100
df2 = df2.query('real_change<30')

points = hv.Points(df[['p_change','real_change']]).redim.range(x=(-5, 5), y=(-5, 5))
points1 = hv.Points(df1[['p_change','real_change']]).redim.range(x=(-5, 5), y=(-5, 5))
points2 = hv.Points(df2[['p_change','real_change']]).redim.range(x=(-5, 5), y=(-5, 5))

%%opts Histogram [height=750 ] 
%%opts Histogram (alpha=0.3)
%%opts Points (alpha=0.6)


from holoviews.operation import histogram

xhist, yhist = (histogram(points, bin_range=(-5, 5), dimension=dim) *
                histogram(points1,  bin_range=(-5, 5), dimension=dim) *
                 histogram(points2,  bin_range=(-5, 5), dimension=dim) 
                for dim in ['p_change','real_change'])
(points2 * points1 * points) << yhist(plot=dict(width=125)) << xhist(plot=dict(height=125))

points2 + points1 + points