Python 如何使用条件索引获取单元格上的标量值
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How to get scalar value on a cell using conditional indexing
提问by user4979733
I have the dataframe shown below. I need to get the scalar value of column B, dependent on the value of A (which is a variable in my script). I'm trying the loc() function but it returns a Series instead of a scalar value. How do I get the scalar value()?
我有如下所示的数据框。我需要获取 B 列的标量值，这取决于 A 的值（这是我脚本中的一个变量）。我正在尝试 loc() 函数，但它返回一个系列而不是一个标量值。我如何获得标量值（）？
>>> x = pd.DataFrame({'A' : [0,1,2], 'B' : [4,5,6]})
>>> x
A B
0 0 4
1 1 5
2 2 6
>>> x.loc[x['A'] == 2]['B']
2 6
Name: B, dtype: int64
>>> type(x.loc[x['A'] == 2]['B'])
<class 'pandas.core.series.Series'>
采纳答案by Noah
First of all, you're better off accessing both the row and column indices from the .loc:
首先，您最好从以下位置访问行和列索引.loc：
x.loc[x['A'] == 2, 'B']
Second, you can always get at the underlying numpy matrix using .valueson a series or dataframe:
其次，您始终可以在.values系列或数据帧上使用底层 numpy 矩阵：
In : x.loc[x['A'] == 2, 'B'].values[0]
Out: 6
Finally, if you're not interested in the original question's "conditional indexing", there are also specific accessors designed to get a single scalar value from a DataFrame: dataframe.at[index, column]or dataframe.iat[i, j](these are similar to .loc[]and .iloc[]but designed for quick access to a single value).
最后，如果你不是在原来的问题的“有条件索引”感兴趣的话，也有设计为从数据帧得到一个标值特定存取：dataframe.at[index, column]或dataframe.iat[i, j]（这些是类似于.loc[]和.iloc[]而设计的，以便快速访问单个值） .
回答by ihadanny
elaborating on @ShineZhang comment:
详细说明@ShineZhang 评论：
x.set_index('A').at[2, 'B']
x.set_index('A').at[2, 'B']
6
6
pd.__version__
pd.__version__
u'0.22.0'
你'0.22.0'
