使用查找表确定值的范围

Question

我有一个带有数字的 df：

numbers = pd.DataFrame(columns=['number'], data=[
50,
65,
75,
85,
90
])

和一个带有范围的 df （查找表）：

ranges = pd.DataFrame(
columns=['range','range_min','range_max'],
data=[
['A',90,100],
['B',85,95],
['C',70,80]
]
)

我想确定值（在第一个表中）落在什么范围（在第二个表中）。请注意范围重叠，并且限制包括在内。另请注意，上面的普通数据框有 3 个范围，但该数据框是动态生成的。它可以有 2 到 7 个范围。

期望的结果：

numbers = pd.DataFrame(columns=['number','detected_range'], data=[
[50,'out_of_range'],
[65, 'out_of_range'],
[75,'C'],
[85,'B'],
[90,'overlap'] * could be A or B *
])

我用 for 循环解决了这个问题，但这不能很好地扩展到我正在使用的大数据集。而且代码过于广泛且不优雅。见下文：

numbers['detected_range'] = nan
for i, row1 in number.iterrows():
    for j, row2 in ranges.iterrows():
        if row1.number<row2.range_min and row1.number>row2.range_max:
             numbers.loc[i,'detected_range'] = row1.loc[j,'range']
        else if (other cases...):
              ...and so on...

我怎么能这样做呢？

Answer 1

您可以使用一些numpy向量运算来生成掩码，并将它们用于select标签：

import numpy as np

a = numbers['number'].values   # numpy array of numbers
r = ranges.set_index('range')  # dataframe of min/max with labels as index

m1 = (a>=r['range_min'].values[:,None]).T  # is number above each min
m2 = (a<r['range_max'].values[:,None]).T   # is number below each max
m3 = (m1&m2)                               # combine both conditions above
# NB. the two operations could be done without the intermediate variables m1/m2

m4 = m3.sum(1)                             # how many matches?
                                           # 0 -> out_of_range
                                           # 2 -> overlap
                                           # 1 -> get column name

# now we select the label according to the conditions
numbers['detected_range'] = np.select([m4==0, m4==2], # out_of_range and overlap
                                      ['out_of_range', 'overlap'],
                                      # otherwise get column name
                                      default=np.take(r.index, m3.argmax(1))
                                     )

输出：

   number detected_range
0      50   out_of_range
1      65   out_of_range
2      75              C
3      85              B
4      90        overlap

编辑：

它适用于范围内任意数量的间隔

带有额外内容的示例输出['D',50,51]：

   number detected_range
0      50              D
1      65   out_of_range
2      75              C
3      85              B
4      90        overlap