pandas 在熊猫数据框中查找元素
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Finding elements in a pandas dataframe
提问by ahajib
I have a pandas dataframe which looks like the following:
我有一个如下所示的 Pandas 数据框：
0 1
0 2
2 3
1 4
What I want to do is the following: if I get 2 as input my code is supposed to search for 2 in the dataframe and when it finds it returns the value of the other column. In the above example my code would return 0 and 3. I know that I can simply look at each row and check if any of the elements is equal to 2 but I was wondering if there is one-liner for such a problem.
我想要做的是：如果我得到 2 作为输入，我的代码应该在数据框中搜索 2，当它找到时返回另一列的值。在上面的示例中，我的代码将返回 0 和 3。我知道我可以简单地查看每一行并检查是否有任何元素等于 2，但我想知道是否有针对此类问题的单行代码。
UPDATE: None of the columns are index columns.
更新：所有列都不是索引列。
Thanks
谢谢
采纳答案by Psidom
You may need this:
你可能需要这个：
n_input = 2
df[(df == n_input).any(1)].stack()[lambda x: x != n_input].unique()
# array([0, 3])
回答by blacksite
>>> df = pd.DataFrame({'A': [0, 0, 2, 1], 'B': [1,2,3,4]})
>>> df
A B
0 0 1
1 0 2
2 2 3
3 1 4
The following pandas syntax is equivalent to the SQL SELECT B FROM df WHERE A = 2
以下 Pandas 语法等价于 SQL SELECT B FROM df WHERE A = 2
>>> df[df['A'] == 2]['B']
2 3
Name: B, dtype: int64
There's also pandas.DataFrame.query:
还有pandas.DataFrame.query：
>>> df.query('A == 2')['B']
2 3
Name: B, dtype: int64
