axis=1表示列（1是竖着的），axis=0表示行

在mean()方法中有所不同，mean(axis=0）返回的是各列的平均值

d = ts.get_hist_data('600848', start='2015-01-05', end='2015-01-09')data = pd.DataFrame(d)print(data)print(data.mean(axis=0))

运行结果是

open   high  close    low    volume  price_change  p_change  \date                                                                       2015-01-09  11.68  11.71  11.23  11.19  44851.56         -0.44     -3.77   2015-01-08  11.70  11.92  11.67  11.64  56845.71         -0.25     -2.10   2015-01-07  11.58  11.99  11.92  11.48  86681.38          0.31      2.67   2015-01-06  11.13  11.66  11.61  11.03  59199.93          0.35      3.11   2015-01-05  11.16  11.39  11.26  10.89  46383.57          0.14      1.26                  ma5    ma10    ma20     v_ma5    v_ma10     v_ma20  turnover  date                                                                         2015-01-09  11.538  11.363  11.682  58792.43  60665.93  107924.27      1.54  2015-01-08  11.516  11.349  11.647  57268.99  61376.00  105823.50      1.95  2015-01-07  11.366  11.251  11.543  55049.74  61628.07  103010.58      2.97  2015-01-06  11.182  11.155  11.382  54854.38  63401.05   98686.98      2.03  2015-01-05  11.156  11.212  11.370  58648.75  68429.87  100765.24      1.59  open                11.4500high                11.7340close               11.5380low                 11.2460volume           58792.4300price_change         0.0220p_change             0.2340ma5                 11.3516ma10                11.2660ma20                11.5248v_ma5            56922.8580v_ma10           63100.1840v_ma20          103242.1140turnover             2.0160dtype: float64

可以理解为对各列的所有行做平均。