python - 使用条件列表过滤 Pandas 中的 DataFrame

Question

我希望有一个函数接受任意长度的条件列表，并在所有条件之间放置一个符号。下面的示例代码。

df = pd.DataFrame(columns=['Sample', 'DP','GQ', 'AB'],
         data=[
               ['HG_12_34', 200, 35, 0.4],
               ['HG_12_34_2', 50, 45, 0.9],
               ['KD_89_9', 76, 67, 0.7],
               ['KD_98_9_2', 4, 78, 0.02],
               ['LG_3_45', 90, 3, 0.8],
               ['LG_3_45_2', 15, 12, 0.9]
               ])


def some_func(df, cond_list):

    # wrap ampersand between multiple conditions
    all_conds = ?

    return df[all_conds]

cond1 = df['DP'] > 40
cond2 = df['GQ'] > 40
cond3 = df['AB'] < 0.4


some_func(df, [cond1, cond2]) # should return df[cond1 & cond2]
some_func(df, [cond1, cond3, cond2]) # should return df[cond1 & cond3 & cond2]

我将不胜感激。

Answer 1

您可以为此使用 functools.reduce:

<b>from functools import reduce</b>

def some_func(df, cond_list):
    return df[<b>reduce(lambda x,y: x&y</b>, cond_list<b>)</b>]

或者，像 @AryaMcCarthy说，你可以使用 operator 包中的 and_:

from functools import reduce
<b>from operator import and_</b>

def some_func(df, cond_list):
    return df[reduce(<b>and_</b>, cond_list)]

或使用 numpy - 如 @ayhan说 - 这也有一个逻辑和减少:

<b>from numpy import logical_and</b>

def some_func(df, cond_list):
    return df[<b>logical_and.reduce(</b>cond_list<b>)</b>]

对于您的示例输入，所有三个版本都会生成以下输出:

>>> some_func(df, [cond1, cond2])
       Sample  DP  GQ   AB
1  HG_12_34_2  50  45  0.9
2     KD_89_9  76  67  0.7
>>> some_func(df, [cond1, cond2, cond3])
Empty DataFrame
Columns: [Sample, DP, GQ, AB]
Index: []