我有一個(gè)包含一列列表的數(shù)據(jù)框，如下所示：df pos_tag0 ['Noun','verb','adjective']1 ['Noun','verb']2 ['verb','adjective']3 ['Noun','adverb']...我想得到的是每個(gè)唯一元素作為字典出現(xiàn)在整個(gè)列中的次數(shù)：desired output:my_dict = {'Noun':3, 'verb':3, 'adjective':2, 'adverb':1}
2 回答
慕運(yùn)維8079593
TA貢獻(xiàn)1876條經(jīng)驗(yàn) 獲得超5個(gè)贊
與和Series.explode一起使用：Series.value_countsSeries.to_dict
freq = df['pos_tag'].explode().value_counts().to_dict()
結(jié)果：
# print(freq)
{'Noun':3, 'verb':3, 'adjective':2, 'adverb':1}
ABOUTYOU
TA貢獻(xiàn)1812條經(jīng)驗(yàn) 獲得超5個(gè)贊
為了提高性能，請(qǐng)使用Counter嵌套列表的展平值：
from collections import Counter
my_dict = dict(Counter([y for x in df['pos_tag'] for y in x]))
print (my_dict)
{'Noun': 3, 'verb': 3, 'adjective': 2, 'adverb': 1}
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