将函数应用于Pandas数据框中的成对的行 [英] Apply function on pairs of rows in Pandas dataframe

问题描述

我是pandas数据框的新手，我想应用一个函数在同一列中包含几行.就像当您应用函数diff()时一样，但是我想计算文本之间的距离.所以我定义了一个测量距离的函数，我尝试使用apply，但是我不知道如何挑选几行.在下面，我显示了一个我尝试做过的例子以及我的期望:

I'm a newbie to pandas dataframe, and I wanted to apply a function taking couple of rows in the same column. Like when you apply the function diff(), but i want to calculate the distance between text. so i defined a function which measure the distance, and i tried to use apply but i don't know how can i pick couple of rows. Below i show an example that i'have tried to do and what i expected:

def my_measure_function(x,y):
   return some_distance_calculus(x,y)

>>> from pandas import DataFrame
>>> df = DataFrame({"text": ['hello','hella','hel'], "B": [3,4,4]})
>>> df['dist'] = df.apply(lambda x, y: my_measure_function(x, y), axis=0)

但是它不起作用. 我想获得的是:

but it doesn't work. What i want to obtain is:

>>> df
      text  B  dist
0    hello  3    0
1    hella  4    1
2    hel    4    2

在此先感谢您能为我提供的任何帮助.

Thanks in advance for any help that you can provide me.

推荐答案

您可能希望避免性能创建新列可能会受到影响.相反，您可以将map与 pd.Series.shift结合使用:

You may wish to avoid pd.DataFrame.apply, as performance may suffer. Instead, you can use map with pd.Series.shift:

df['dist'] = list(map(my_measure_function, df['text'], df['text'].shift()))

或通过列表理解:

zipper = zip(df['text'], df['text'].shift())
df['dist'] = [my_measure_function(val1, val2) for val1, val2 in zipper]

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