如何在 python/pandas 中的 DataFrame 中添加另一个类别，仅包括缺失值？

Question

我有一个包含两列的数据框：'TotalCharges' 和 'Churn'，有 7043 行。在 'TotalCharges' 列的 11 个单元格中，我有一个缺失值。我想要的是创建 10 个类别的 TotalCharges 加上一个名为 "MissingValues" 的类别，但我找不到实现它的方法。我的 DataFrame 如下所示：

        TotalCharges Churn
0           29.85    No
1          1889.5    No
2          108.15   Yes
3         1840.75    No
4          151.65   Yes
5           820.5   Yes
6          1949.4    No
7           301.9    No
8         3046.05   Yes
9         3487.95    No
10         587.45    No
11          326.8    No
12         5681.1    No
13         5036.3   Yes
14        2686.05    No
15        7895.15    No
16        missing    No
17        7382.25    No
18         528.35   Yes
.... ....
.... ....

我想得到这样的东西：

        TotalCharges Churn TotalChargesCategories
0           29.85    No    (18.799, 84.61]
1          1889.5    No    (947.38, 1400.55]
2          108.15   Yes    (84.61, 267.37]
3         1840.75    No    (1400.55, 2065.52]
4          151.65   Yes    (84.61, 267.37]
5           820.5   Yes    (552.82, 947.38]
6          1949.4    No    (1400.55, 2065.52]
7           301.9    No    (267.37, 552.82]
8         3046.05   Yes    (2065.52, 3132.75]
9         3487.95    No    (3132.75, 4471.44]
10         587.45    No    (552.82, 947.38]
11          326.8    No    (267.37, 552.82]
12         5681.1    No    (4471.44, 5973.69]
13         5036.3   Yes    (4471.44, 5973.69]
14        2686.05    No    (2065.52, 3132.75]
15        7895.15    No    (5973.69, 8684.8]
16        missing    No     MissingValues
17        7382.25    No    (5973.69, 8684.8]
18         528.35   Yes    (267.37, 552.82]
.... ....
.... ....

如果没有缺失值，使用此代码会很容易：

width_bin = (pd.qcut(df.TotalCharges,10))
df = df.assign(TotalChargesCat=width_bin)
df

但是由于有 11 个缺失值，我在创建类别时遇到问题，并且此代码导致错误消息：

TypeError: unsupported operand type(s) for -: 'str' and 'str'

Answer 1

只需将 missing 强制为 NaN（通过显式替换或强制为数字数据类型），然后像以前一样使用 cut：

df['TotalChargesCategories'] = pd.cut(pd.to_numeric(df['TotalCharges'], errors='coerce'),10)

>>> df
   TotalCharges Churn TotalChargesCategories
0         29.85    No       (21.985, 816.38]
1        1889.5    No     (1602.91, 2389.44]
2        108.15   Yes       (21.985, 816.38]
3       1840.75    No     (1602.91, 2389.44]
4        151.65   Yes       (21.985, 816.38]
5         820.5   Yes      (816.38, 1602.91]
6        1949.4    No     (1602.91, 2389.44]
7         301.9    No       (21.985, 816.38]
8       3046.05   Yes     (2389.44, 3175.97]
9       3487.95    No      (3175.97, 3962.5]
10       587.45    No       (21.985, 816.38]
11        326.8    No       (21.985, 816.38]
12       5681.1    No     (5535.56, 6322.09]
13       5036.3   Yes     (4749.03, 5535.56]
14      2686.05    No     (2389.44, 3175.97]
15      7895.15    No     (7108.62, 7895.15]
16      missing    No                    NaN
17      7382.25    No     (7108.62, 7895.15]
18       528.35   Yes       (21.985, 816.38]

如何在 python/pandas 中的 DataFrame 中添加另一个类别，仅包括缺失值？

How to add another category in a DataFrame in python/pandas including only missing values?

python

numpy

categories

pandas

data-science