python - 根据条件将 Pandas DataFrame 列从 String 转换为 Int

Question

我有一个看起来像的数据框

df

viz  a1_count  a1_mean     a1_std
n         3        2   0.816497
y         0      NaN        NaN 
n         2       51  50.000000

我想根据条件将“viz”列转换为 0 和 1。我试过了:

df['viz'] = 0 if df['viz'] == "n" else 1

但我明白了:

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

Answer 1

您正在尝试将标量与引发您看到的 ValueError 的整个系列进行比较。一个简单的方法是将 bool 系列转换为 int:

In [84]:
df['viz'] = (df['viz'] !='n').astype(int)
df

Out[84]:
   viz  a1_count  a1_mean     a1_std
0    0         3        2   0.816497
1    1         0      NaN        NaN
2    0         2       51  50.000000

你也可以使用np.where:

In [86]:
df['viz'] = np.where(df['viz'] == 'n', 0, 1)
df

Out[86]:
   viz  a1_count  a1_mean     a1_std
0    0         3        2   0.816497
1    1         0      NaN        NaN
2    0         2       51  50.000000

bool 比较的输出:

In [89]:
df['viz'] !='n'

Out[89]:
0    False
1     True
2    False
Name: viz, dtype: bool

然后转换为 int:

In [90]:
(df['viz'] !='n').astype(int)

Out[90]:
0    0
1    1
2    0
Name: viz, dtype: int32