Question

我想根据dtype选择列。例子：

<TextBox AcceptsReturn="False">
<TextBox.InputBindings>
    <KeyBinding 
        Key="Enter" 
        Command="{Binding SearchCommand}" 
        CommandParameter="{Binding Path=Text, RelativeSource={RelativeSource AncestorType={x:Type TextBox}}}" />
</TextBox.InputBindings>

uints的预期输出为：[10,11,12,13,14,15,16,17,18,19] 问题是当我使用hstack将原始numpy数据（a和b）连接在一起时，无法正确检测到dtype，因为上面的代码返回[]。

Answer 1

我认为pandas可以更好地处理不同的数据类型。试试这个：

# Converting your arrays to dataframes
a = pd.DataFrame(np.random.randn(10, 10).astype('float'))
b = pd.DataFrame(np.random.randn(10, 10).astype('uint8'))

df = pd.concat([a,b],axis=1) # horizontally concatenating a and b
df.columns=[i for i in range(20)] # setting the column names manually
print(df.head())

             0         1         2         3         4         5         6   \
0  0.931404  0.612939 -0.369925 -0.777209  0.776831  1.923639  0.714632   
1  1.002620  0.612617 -0.184530 -0.279565 -0.021436  1.079653  0.299139   
2  0.938141  0.621674  1.723074  0.298568 -0.892739 -1.154118 -2.623486   
3 -1.050390 -1.058590  1.319297 -1.052302 -0.633126 -1.089275  0.796025   
4 -0.312114 -0.045124 -0.094495  0.296262  0.518496  0.068003 -1.247959   

         7         8         9   10   11   12   13   14  15   16   17   18  19  
0  0.710094 -1.465146 -0.009591   0  255    0  255    0   0    0    0    0   1  
1  1.645174 -0.491199  0.961290   0  253    0    1  254   1    0  255    0   0  
2  0.633076 -1.366998 -0.450123   0    1  255  255    0   0  255    0  254   0  
3 -0.650617  1.226741  1.884750   0  255    0    0    0   0  255    0    1   0  
4 -0.774224  0.780239 -1.072834   0  254    3    2    0   0    0    0    0   0  

df.select_dtypes(include=['uint8']).columns.tolist()

[10, 11, 12, 13, 14, 15, 16, 17, 18, 19]

在numpy hstack之后无法选择列dtype

1 个答案: