我发现前面答案的语法是多余的,很难记住。熊猫介绍了
query()
我更喜欢v0.13中的方法。对于你的问题,你可以
df.query('col == val')
复制自
http://pandas.pydata.org/pandas-docs/version/0.17.0/indexing.html#indexing-query
In [167]: n = 10
In [168]: df = pd.DataFrame(np.random.rand(n, 3), columns=list('abc'))
In [169]: df
Out[169]:
a b c
0 0.687704 0.582314 0.281645
1 0.250846 0.610021 0.420121
2 0.624328 0.401816 0.932146
3 0.011763 0.022921 0.244186
4 0.590198 0.325680 0.890392
5 0.598892 0.296424 0.007312
6 0.634625 0.803069 0.123872
7 0.924168 0.325076 0.303746
8 0.116822 0.364564 0.454607
9 0.986142 0.751953 0.561512
# pure python
In [170]: df[(df.a < df.b) & (df.b < df.c)]
Out[170]:
a b c
3 0.011763 0.022921 0.244186
8 0.116822 0.364564 0.454607
# query
In [171]: df.query('(a < b) & (b < c)')
Out[171]:
a b c
3 0.011763 0.022921 0.244186
8 0.116822 0.364564 0.454607
您还可以通过预先设置
@
.
exclude = ('red', 'orange')
df.query('color not in @exclude')
