获取大 pandas 应用功能中的一行的索引 [英] getting the index of a row in a pandas apply function

问题描述

我正在尝试访问在Panda中整个 DataFrame 中应用的函数中的一行的索引。我有这样的东西：

I am trying to access the index of a row in a function applied across an entire DataFrame in Pandas. I have something like this:

df = pandas.DataFrame([[1,2,3],[4,5,6]], columns=['a','b','c'])
>>> df
   a  b  c
0  1  2  3
1  4  5  6

我将定义一个函数来访问给定行的元素

and I'll define a function that access elements with a given row

def rowFunc(row):
    return row['a'] + row['b'] * row['c']

应用它像这样：

df['d'] = df.apply(rowFunc, axis=1)
>>> df
   a  b  c   d
0  1  2  3   7
1  4  5  6  34

真棒！现在如果我想将索引并入我的函数呢？
在添加 d 之前， DataFrame 中任何给定行的索引将为索引（[u'a'，u'b'，u'c'，u'd']，dtype ='object'），但我想要0和1.所以我可以'我只需访问 row.index 。

Awesome! Now what if I want to incorporate the index into my function? The index of any given row in this DataFrame before adding d would be Index([u'a', u'b', u'c', u'd'], dtype='object'), but I want the 0 and 1. So I can't just access row.index.

我知道我可以在表中创建一个临时列，索引，但我想知道它是否在某个地方的行对象中被放置。

I know I could create a temporary column in the table where I store the index, but I"m wondering if it is sotred in the row object somewhere.

推荐答案

在这种情况下访问索引访问名称属性：

To access the index in this case you access the name attribute:

In [182]:

df = pd.DataFrame([[1,2,3],[4,5,6]], columns=['a','b','c'])
def rowFunc(row):
    return row['a'] + row['b'] * row['c']

def rowIndex(row):
    return row.name
df['d'] = df.apply(rowFunc, axis=1)
df['rowIndex'] = df.apply(rowIndex, axis=1)
df
Out[182]:
   a  b  c   d  rowIndex
0  1  2  3   7         0
1  4  5  6  34         1

请注意，如果这是真的你想要做的，以下工作，是很多更快：

Note that if this is really what you are trying to do that the following works and is much faster:

In [198]:

df['d'] = df['a'] + df['b'] * df['c']
df
Out[198]:
   a  b  c   d
0  1  2  3   7
1  4  5  6  34

In [199]:

%timeit df['a'] + df['b'] * df['c']
%timeit df.apply(rowIndex, axis=1)
10000 loops, best of 3: 163 µs per loop
1000 loops, best of 3: 286 µs per loop

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