6. 观察股价

  1. #  读取Schlumberger stock数据集，行索引设为Date列，并将其转变为DatetimeIndex
  2.  In[43]: slb = pd.read_csv('data/slb_stock.csv', index_col='Date', parse_dates=['Date'])
  3.          slb.head()
  4. Out[43]:

6. 观察股价 - 图1

  1. #  选取Close这列，用describe返回统计信息
  2.  In[44]: slb_close = slb['Close']
  3.          slb_summary = slb_close.describe(percentiles=[.1, .9])
  4.          slb_summary
  5. Out[44]: count    1895.000000
  6.          mean       79.121905
  7.          std        11.767802
  8.          min        51.750000
  9.          10%        64.892000
  10.          50%        78.000000
  11.          90%        93.248000
  12.          max       117.950000
  13.          Name: Close, dtype: float64
  1. #  用布尔索引选取最高和最低10%的收盘价
  2.  In[45]: upper_10 = slb_summary.loc['90%']
  3.          lower_10 = slb_summary.loc['10%']
  4.          criteria = (slb_close < lower_10) | (slb_close > upper_10)
  5.          slb_top_bottom_10 = slb_close[criteria]
  6. #  过滤出的数据使用灰色，所有的收盘价使用黑色，用matplotlib在十分之一和十分之九分位数位置画横线
  7.  In[46]: slb_close.plot(color='black', figsize=(12,6))
  8.          slb_top_bottom_10.plot(marker='o', style=' ', ms=4, color='lightgray')
  10.          xmin = criteria.index[0]
  11.          xmax = criteria.index[-1]
  12.          plt.hlines(y=[lower_10, upper_10], xmin=xmin, xmax=xmax,color='black')
  13. Out[46]: <matplotlib.collections.LineCollection at 0x1174b3278>

6. 观察股价 - 图2

更多

  1. #  使用fill_between可以在两条线之间填充颜色
  2.  In[47]: slb_close.plot(color='black', figsize=(12,6))
  3.          plt.hlines(y=[lower_10, upper_10], 
  4.                     xmin=xmin, xmax=xmax,color='lightgray')
  5.          plt.fill_between(x=criteria.index, y1=lower_10,
  6.                           y2=slb_close.values, color='black')
  7.          plt.fill_between(x=criteria.index,y1=lower_10,
  8.                           y2=slb_close.values, where=slb_close < lower_10,
  9.                           color='lightgray')
  10.          plt.fill_between(x=criteria.index, y1=upper_10, 
  11.                           y2=slb_close.values, where=slb_close > upper_10,
  12.                           color='lightgray')
  13. Out[47]:

6. 观察股价 - 图3