有沒有辦法使用 pandas.cut() function 到垃圾箱的上端 select？

Question

我對 pandas 中的垃圾箱有疑問。到目前為止，我的代碼如下所示：

africa_uhc = pd.cut(africa[("Universal health coverage (UHC) service coverage index")]/100, [0, 0.25, 0.50, 0.75, 1])

打印出來

29     (0.5, 0.75]
36     (0.25, 0.5]
111    (0.5, 0.75]
112    (0.5, 0.75]
118    (0.25, 0.5]
140    (0.25, 0.5]
141    (0.5, 0.75]
142      (0, 0.25]
Name: Universal health coverage (UHC) service coverage index, dtype: category
Categories (4, object): [(0, 0.25] < (0.25, 0.5] < (0.5, 0.75] < (0.75, 1]]

我想把第二行的數字拿出來做更多的聚合，有沒有辦法做到這一點？ 或者有沒有辦法通過四舍五入將它們分成垃圾箱？ 例如，索引 29 的值為 0.75 而不是 (0.5, 0.75)。謝謝！

Answer 1

您可以使用labels參數來控制返回的內容。

import pandas as pd

df = pd.DataFrame({'UHC': [60,30,60,70,40,50,70,10]})
bins = [0, 0.25, 0.50, 0.75, 1]

print(pd.cut(df.UHC/100, bins))
#0    (0.5, 0.75]
#1    (0.25, 0.5]
#2    (0.5, 0.75]
#3    (0.5, 0.75]
#4    (0.25, 0.5]
#5    (0.25, 0.5]
#6    (0.5, 0.75]
#7    (0.0, 0.25]
#Name: UHC, dtype: category
#Categories (4, interval[float64]): [(0.0, 0.25] < (0.25, 0.5] < (0.5, 0.75] < (0.75, 1.0]]

print(pd.cut(df.UHC/100, bins, labels=bins[1:]))
#0    0.75
#1    0.50
#2    0.75
#3    0.75
#4    0.50
#5    0.50
#6    0.75
#7    0.25
#Name: UHC, dtype: category
#Categories (4, float64): [0.25 < 0.50 < 0.75 < 1.00]