我鼓励您在邮件列表中提出这些问题，但是无论如何，与底层NumPy数组一起工作仍然是一件非常底层的事情。例如，要选择任何列中的值超过例如1.5的行，在此示例中：
In [11]: dfOut[11]: A B C D 2000-01-03 -0.59885 -0.18141 -0.68828 -0.775722000-01-04 0.83935 0.15993 0.95911 -1.129592000-01-05 2.80215 -0.10858 -1.62114 -0.201702000-01-06 0.71670 -0.26707 1.36029 1.742542000-01-07 -0.45749 0.22750 0.46291 -0.584312000-01-10 -0.78702 0.44006 -0.36881 -0.138842000-01-11 0.79577 -0.09198 0.14119 0.026682000-01-12 -0.32297 0.62332 1.93595 0.780242000-01-13 1.74683 -1.57738 -0.02134 0.115962000-01-14 -0.55613 0.92145 -0.22832 1.566312000-01-17 -0.55233 -0.28859 -1.18190 -0.807232000-01-18 0.73274 0.24387 0.88146 -0.944902000-01-19 0.56644 -0.49321 1.17584 -0.175852000-01-20 1.56441 0.62331 -0.26904 0.119522000-01-21 0.61834 0.17463 -1.62439 0.991032000-01-24 0.86378 -0.68111 -0.15788 -0.166702000-01-25 -1.12230 -0.16128 1.20401 1.089452000-01-26 -0.63115 0.76077 -0.92795 -2.171182000-01-27 1.37620 -1.10618 -0.37411 0.737802000-01-28 -1.40276 1.98372 1.47096 -1.380432000-01-31 0.54769 0.44100 -0.52775 0.844972000-02-01 0.12443 0.32880 -0.71361 1.317782000-02-02 -0.28986 -0.63931 0.88333 -2.589432000-02-03 0.54408 1.17928 -0.26795 -0.516812000-02-04 -0.07068 -1.29168 -0.59877 -1.456392000-02-07 -0.65483 -0.29584 -0.02722 0.312702000-02-08 -0.18529 -0.18701 -0.59132 -1.152392000-02-09 -2.28496 0.36352 1.11596 0.022932000-02-10 0.51054 0.97249 1.74501 0.205252000-02-11 0.10100 0.27722 0.65843 1.73591In [12]: df[(df.values > 1.5).any(1)]Out[12]: A B C D 2000-01-05 2.8021 -0.1086 -1.62114 -0.20172000-01-06 0.7167 -0.2671 1.36029 1.74252000-01-12 -0.3230 0.6233 1.93595 0.78022000-01-13 1.7468 -1.5774 -0.02134 0.11602000-01-14 -0.5561 0.9215 -0.22832 1.56632000-01-20 1.5644 0.6233 -0.26904 0.11952000-01-28 -1.4028 1.9837 1.47096 -1.38042000-02-10 0.5105 0.9725 1.74501 0.20522000-02-11 0.1010 0.2772 0.65843 1.7359
必须使用
&或
|（和括号！）组合多个条件：
In [13]: df[(df['A'] > 1) | (df['B'] < -1)]Out[13]: A B C D 2000-01-05 2.80215 -0.1086 -1.62114 -0.20172000-01-13 1.74683 -1.5774 -0.02134 0.11602000-01-20 1.56441 0.6233 -0.26904 0.11952000-01-27 1.37620 -1.1062 -0.37411 0.73782000-02-04 -0.07068 -1.2917 -0.59877 -1.4564
我很想拥有某种查询API来简化这些事情
