您会收到此错误，因为JavaScript表达式中的scale是undefined。
您必须在javascript expression中将CSS作为字符串编写。
例如这样的：

  transform: ${props => props.display === 'none' ? `scale(0.7)` : `scale(1,1)`};

我在代码沙箱中为您提供了一个简单的代码： https://codesandbox.io/s/musing-dirac-tb08v
更多资源：
https://www.styled-components.com/docs/basics#adapting-based-on-props

与此问题相关，在像这样的规模内使用道具。

m = df.groupby(['id','y',df['y'].cumsum()]).cumcount() + 1                 ########## setup you base getting cumcount
df['num_month'] = np.where((m == 1) & (m.shift() > 1),m.shift() + 1,m).astype(int)  # extend cumcount one further row per group for first line of code
s1 = df.groupby('id').transform('idxmin').iloc[:,0]                      ############## get index location of first value per group and return as series with same length
s2 = df.groupby(['id',(df['y'] > 0).cumsum()]).transform('idxmin').iloc[:,0] ######### get index location of first non-zero value per group and return as series with same length
df['num_month'] = df['num_month'].mask((s1 == s2) | (s1 == s2.shift()),-1) ########### using s1 and s2 conditions,update the necessary rows to -1
df
Out[1]: 
    id  year  month  y  sinx  num_month
0    1  2019      1  0     1         -1
1    1  2019      2  0     2         -1
2    1  2019      3  1     3         -1
3    1  2019      4  0     4          1
4    1  2019      5  0     5          2
5    1  2019      6  0     6          3
6    1  2019      7  0     7          4
7    1  2019      8  2     8          5
8    1  2019      9  0     9          1
9    1  2019     10  0    10          2
10   1  2019     11  0    11          3
11   1  2019     12  0    11          4
12   1  2020      1  0    12          5
13   1  2020      2  0    13          6
14   1  2020      3  2    14          7
15   1  2020      4  0    15          1
16   2  2019      1  0     1         -1
17   2  2019      2  0     2         -1
18   2  2019      3  1     3         -1
19   2  2019      4  0     4          1