基于值 (Pandas) 过滤列：TypeError: 无法将 ['a'] 与块值进行比较
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Filter columns based on a value (Pandas): TypeError: Could not compare ['a'] with block values
提问by ramesh
I'm trying filter a DataFrame columns based on a value.
我正在尝试根据值过滤 DataFrame 列。
In[41]: df = pd.DataFrame({'A':['a',2,3,4,5], 'B':[6,7,8,9,10]})
In[42]: df
Out[42]:
A B
0 a 6
1 2 7
2 3 8
3 4 9
4 5 10
Filtering columns:
过滤列：
In[43]: df.loc[:, (df != 6).iloc[0]]
Out[43]:
A
0 a
1 2
2 3
3 4
4 5
It works! But, When I used strings,
有用！但是，当我使用字符串时，
In[44]: df.loc[:, (df != 'a').iloc[0]]
I'm getting this error: TypeError: Could not compare ['a'] with block values
我收到此错误： TypeError: Could not compare ['a'] with block values
回答by SivaTP
You are trying to compare string 'a' with numeric values in column B.
您正在尝试将字符串 'a' 与 B 列中的数值进行比较。
If you want your code to work, first promote dtype of column B as numpy.object, It will work.
如果你想让你的代码工作，首先将 B 列的 dtype 提升为 numpy.object，它会工作。
df.B = df.B.astype(np.object)
Always check data types of the columns before performing the operations using
在执行操作之前总是检查列的数据类型使用
df.info()
回答by AlexG
You could do this with masks instead, for example:
你可以用面具来代替，例如：
df[df.A!='a'].A
and to filter from any column:
并从任何列中过滤：
df[df.apply(lambda x: sum([x_=='a' for x_ in x])==0, axis=1)]
回答by M.R.VaaN
The problem is due to the fact that there are numeric and string objects in the dataframe. You can loop through each column and check each column as a series for a specific value using
问题是由于数据框中存在数字和字符串对象。您可以遍历每一列并使用以下命令将每一列检查为特定值的系列
(Series=='a').any()
(系列=='a').any()
