Question

我有一个较大的url数据框和一个较小的第二个数据框，其中包含要用于将两个数据框合并在一起的字符串列。来自第二个df的数据将用于填充较大的第一个df。

匹配的字符串可以包含*通配符（以及多个通配符），但是分组的顺序仍然很重要；因此“ path / * path2”将与“ exsample.com/eg_path/extrapath2.html”匹配，但不与“ exsample.com/eg_path2/path/test.html”匹配。如何使用第二个数据框中的字符串将两个数据框合并在一起在第二个数据帧中可以有多个匹配的字符串。

import pandas as pd

urls = {'url':['https://stackoverflow.com/questions/56318782/','https://www.google.com/','https://en.wikipedia.org/wiki/Python_(programming_language)','https://stackoverflow.com/questions/'],
        'hits':[1000,500,300,7]}
metadata = {'group':['group1','group2'],
            'matching_string_1':['google','wikipedia*Python_'],
            'matching_string_2':['stackoverflow*questions*56318782','']}
result = {'url':['https://stackoverflow.com/questions/56318782/','https://www.google.com/','https://en.wikipedia.org/wiki/Python_(programming_language)','https://stackoverflow.com/questions/'],
        'hits':[1000,500,300,7],
        'group':['group2','group1','group1','']}

df1 = pd.DataFrame(urls)
df2 = pd.DataFrame(metadata)

what_I_am_after = pd.DataFrame(result)

Answer 1

不够健壮，但可以为我的示例提供正确答案。

import pandas as pd

urls = {'url':['https://stackoverflow.com/questions/56318782/','https://www.google.com/','https://en.wikipedia.org/wiki/Python_(programming_language)','https://stackoverflow.com/questions/'],
        'hits':[1000,500,300,7]}
metadata = {'group':['group1','group2'],
            'matching_string_1':['google','wikipedia*Python_'],
            'matching_string_2':['stackoverflow*questions*56318782','']}
result = {'url':['https://stackoverflow.com/questions/56318782/','https://www.google.com/','https://en.wikipedia.org/wiki/Python_(programming_language)','https://stackoverflow.com/questions/'],
        'hits':[1000,500,300,7],
        'group':['group2','group1','group1','']}

df1 = pd.DataFrame(urls)
df2 = pd.DataFrame(metadata)
results = pd.DataFrame(columns=['url','hits','group'])

for index,row in df2.iterrows():
    for x in row[1:]:
        group = x.split('*')
        rx = "".join([str(x)+".*"  if len(x) > 0 else '' for x in group])
        if rx == "":
            continue
        filter = df1['url'].str.contains(rx,na=False, regex=True)
        if filter.any():
            temp = df1[filter]
            temp['group'] = row[0]
            results = results.append(temp)

d3 = df1.merge(results,how='outer',on=['url','hits'])

如何动态匹配两个熊猫数据帧中的行

1 个答案: