"ValueError: The truth value of a Series is ambiguous" when passing pandas columns to a function

"ValueError: The truth value of a Series is ambiguous" when passing pandas columns to a function

我想根据其他 4 个列的值创建一个 boolean 类型的新列。我有一个函数 is_proximal 需要两个 2 元组(4 个值)和 returns 一个布尔值。

我正在将 pandas DataFrame 中的列传递给此函数。 is_proximal 函数依次使用参数调用 geopy.distance.distance

def is_proximal(p1, p2, exact=True):
    dist = distance(p1, p2)

    if exact:
        return dist.miles < 0.75  # mile threshold

    return dist.m < 100  # meter threshold



airbnb_coords = (df.loc[:, "lat_airbnb"], df.loc[:, "long_airbnb"])
homeaway_coords = (df.loc[:, "lat_homeaway"], df.loc[:, "long_homeaway"])
exacts.loc[:, "proximal"] = is_proximal(airbnb_coords, homeaway_coords)

这会导致以下错误:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

我无法理解为什么会出现此错误。我需要做出哪些改变才能完成我想要做的事情?

预期输出是 boolean 类型的附加列。输入数据框 df 在所有列中包含整数值。

完整的回溯:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-663-435de26b3cfa> in <module>
----> 1 m = filter_geographic_proximity(beds)

~/src/exemption_project/src/match.py in filter_geographic_proximity(df)
     53     airbnb_coords = (exacts.loc[:, "lat_airbnb"], exacts.loc[:, "long_airbnb"])
     54     homeaway_coords = (exacts.loc[:, "lat_homeaway"], exacts.loc[:, "long_homeaway"])
---> 55     exacts.loc[:, "proximal"] = is_proximal(airbnb_coords, homeaway_coords)
     56 
     57     airbnb_coords = (inexacts.loc[:, "lat_airbnb"], inexacts.loc[:, "long_airbnb"])

~/src/exemption_project/src/match.py in is_proximal(p1, p2, exact)
     29 def filter_geographic_proximity(df):
     30     def is_proximal(p1, p2, exact=True):
---> 31         dist = distance(p1, p2)
     32 
     33         if exact:

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in __init__(self, *args, **kwargs)
    387         kwargs.pop('iterations', 0)
    388         major, minor, f = self.ELLIPSOID
--> 389         super(geodesic, self).__init__(*args, **kwargs)
    390 
    391     def set_ellipsoid(self, ellipsoid):

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in __init__(self, *args, **kwargs)
    162         elif len(args) > 1:
    163             for a, b in util.pairwise(args):
--> 164                 kilometers += self.measure(a, b)
    165 
    166         kilometers += units.kilometers(**kwargs)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in measure(self, a, b)
    408     # Call geographiclib routines for measure and destination
    409     def measure(self, a, b):
--> 410         a, b = Point(a), Point(b)
    411         lat1, lon1 = a.latitude, a.longitude
    412         lat2, lon2 = b.latitude, b.longitude

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in __new__(cls, latitude, longitude, altitude)
    163                     )
    164                 else:
--> 165                     return cls.from_sequence(seq)
    166 
    167         if single_arg:

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in from_sequence(cls, seq)
    403             raise ValueError('When creating a Point from sequence, it '
    404                              'must not have more than 3 items.')
--> 405         return cls(*args)
    406 
    407     @classmethod

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in __new__(cls, latitude, longitude, altitude)
    176 
    177         latitude, longitude, altitude = \
--> 178             _normalize_coordinates(latitude, longitude, altitude)
    179 
    180         self = super(Point, cls).__new__(cls)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in _normalize_coordinates(latitude, longitude, altitude)
     57 
     58 def _normalize_coordinates(latitude, longitude, altitude):
---> 59     latitude = float(latitude or 0.0)
     60     longitude = float(longitude or 0.0)
     61     altitude = float(altitude or 0.0)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/pandas/core/generic.py in __nonzero__(self)
   1476         raise ValueError("The truth value of a {0} is ambiguous. "
   1477                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
-> 1478                          .format(self.__class__.__name__))
   1479 
   1480     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

从回溯中可以清楚地看出,错误是在 is_proximal 内部调用的 distance 函数中引发的。这使我相信当该函数旨在处理标量数据时,您正在传递 Series 对象。

请参阅 中的讨论,其中在 pandas 系列上使用 python 逻辑运算符会导致相同的错误。

对于您的情况,解决方案是遍历您的数据,并将每组 co-ordinates 一次一个地传递给您的函数。

df['proximal'] = [
    is_proximal((a, b), (c, d)) 
    for a, b, c, d in df[['lat_x', 'long_x', 'lat_y', 'long_y']].values
]