Question

我有两个数据帧，

DF1，

 Names
 one two three
 Sri is a good player
 Ravi is a mentor
 Kumar is a cricketer

DF2，

 values
 sri
 NaN
 sri, is
 kumar,cricketer

我想在df1中获取包含df2

中所有项目的行

我的预期输出是，

 values             Names
 sri                Sri is a good player
 NaN
 sri, is            Sri is a good player
 kumar,cricketer    Kumar is a cricketer

我试过，df1["Names"].str.contains("|".join(df2["values"].values.tolist()))

但是我无法实现我的预期输出（“，”）。请帮忙

Answer 1

使用集合

s1 = df1.Names.dropna()
s1.loc[:] = [set(x.lower().split()) for x in s1.values.tolist()]
a1 = s1.values

s2 = df2['values'].dropna()
s2.loc[:] = [set(x.replace(' ', '').lower().split(',')) for x in s2.values.tolist()]
a2 = s2.values

i = np.column_stack([a1 >= a2[:, None], [True] * len(a2)]).argmax(1)

df2.assign(Names=pd.Series(
    np.append(df1.Names.values, np.nan)[i], s2.index
))

            values                 Names
0              sri  Sri is a good player
1              NaN                   NaN
2          sri, is  Sri is a good player
3  kumar,cricketer  Kumar is a cricketer

Answer 2

import pandas as pd
names =  [
    'one two three',
    'Sri is a good player',
    'Ravi is a mentor',
    'Kumar is a cricketer'
]
values = [
    'sri',
    'NaN',
    'sri, is',
    'kumar,cricketer',
]

names = pd.Series(names)
values = pd.DataFrame(values, columns=['values'])

def foo(words):
    names_copy = names.copy()

    for word in words.split(','):
        names_copy = names_copy[names_copy.str.contains(word, case=False)]

    return names_copy.values

 values['names'] = values['values'].map(foo)
 values


    values          names
0   sri             [Sri is a good player]
1   NaN             []
2   sri, is         [Sri is a good player]
3   kumar,cricketer [Kumar is a cricketer]

匹配python中pandas中数据帧之间的行

2 个答案: