[英]Extract and count unique hashtags per row from a pandas dataframe
我有一個帶有字符串列Posts
的pandas dataframe df
,如下所示:
df['Posts']
0 "This is an example #tag1"
1 "This too is an example #tag1 #tag2"
2 "Yup, still an example #tag1 #tag1 #tag3"
當我嘗試使用以下代碼來計算主題標簽的數量時,
count_hashtags = df['Posts'].str.extractall(r'(\#\w+)')[0].value_counts()
我明白了
#tag1 4
#tag2 1
#tag3 1
但是我需要將結果計算為每行唯一的標簽,如下所示:
#tag1 3
#tag2 1
#tag3 1
使用drop_duplicates
刪除每個帖子的重復標簽,然后你可以使用value_counts
df.Posts.str.extractall(
r'(\#\w+)'
).reset_index().drop_duplicates(['level_0', 0])[0].value_counts()
將level=0
傳遞給reset_index
較短替代
df.Posts.str.extractall(
r'(\#\w+)'
).reset_index(level=0).drop_duplicates()[0].value_counts()
兩者都會輸出:
#tag1 3
#tag3 1
#tag2 1
Name: 0, dtype: int64
這是使用itertools.chain
和collections.Counter
一個解決方案:
import pandas as pd
from collections import Counter
from itertools import chain
s = pd.Series(['This is an example #tag1',
'This too is an example #tag1 #tag2',
'Yup, still an example #tag1 #tag1 #tag3'])
tags = s.map(lambda x: {i[1:] for i in x.split() if i.startswith('#')})
res = Counter(chain.from_iterable(tags))
print(res)
Counter({'tag1': 3, 'tag2': 1, 'tag3': 1})
績效基准
collections.Counter
是大型系列的pd.Series.str.extractall
2 pd.Series.str.extractall
〜:
import pandas as pd
from collections import Counter
from itertools import chain
s = pd.Series(['This is an example #tag1',
'This too is an example #tag1 #tag2',
'Yup, still an example #tag1 #tag1 #tag3'])
def hal(s):
return s.str.extractall(r'(\#\w+)')\
.reset_index(level=0)\
.drop_duplicates()[0]\
.value_counts()
def jp(s):
tags = s.map(lambda x: {i[1:] for i in x.split() if i.startswith('#')})
return Counter(chain.from_iterable(tags))
s = pd.concat([s]*100000, ignore_index=True)
%timeit hal(s) # 2.76 s per loop
%timeit jp(s) # 1.25 s per loop
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