Python 如何在API中使用*和*
我尝试在Python 如何在API中使用*和*,python,pandas,Python,Pandas,我尝试在.locAPI:中使用and: df = pd.DataFrame(dict(age=[99, 33, 33, 22, 33, 44], aa2=[199, 3, 43, 22, 23, 54], nom=['a', 'z', 'f', 'b', 'p', 'a'],)) df.loc[df.age>30] # aa2 age nom # 0 199 99 a # 1
.loc
API:中使用and:
df = pd.DataFrame(dict(age=[99, 33, 33, 22, 33, 44],
aa2=[199, 3, 43, 22, 23, 54],
nom=['a', 'z', 'f', 'b', 'p', 'a'],))
df.loc[df.age>30]
# aa2 age nom
# 0 199 99 a
# 1 3 33 z
# 2 43 33 f
# 4 23 33 p
# 5 54 44 a
但我得到了这个错误::
df.loc[df.age>30 and (df.age > df.aa2)]
# ---------------------------------------------------------------------------
# ValueError Traceback (most recent call last)
# <ipython-input-13-930dff789922> in <module>()
# ----> 1 df.loc[df.age>30 and (df.age > df.aa2)]
#
# /site-packages/pandas/core/generic.pyc in __nonzero__(self)
# 729 raise ValueError("The truth value of a {0} is ambiguous. "
# 730 "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
# --> 731 .format(self.__class__.__name__))
# 732
# 733 __bool__ = __nonzero__
#
# ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
我更喜欢一种更好、可读性更强的方法: PS好吧,它不会直接回答你的问题(@M.Klugerford),但它给了你一个更好的选择(在我个人看来)
df.loc[df.age>30].loc[(df.age > df.aa2)]
# aa2 age nom
# 1 3 33 z
# 4 23 33 p
>>> df.loc[(df.age>30) & (df.age > df.aa2)]
aa2 age nom
1 3 33 z
4 23 33 p
In [3]: df.query('age > 30 and age > aa2')
Out[3]:
aa2 age nom
1 3 33 z
4 23 33 p