Question

我的数据在列表中。

data = [['Biz_Innovations', '#socialmedia'],
 ['ChantalGrange', '#aws'],
 ['beyonddevops', '#aws'],
 ['beyonddevops', '#socialmedia'],
 ['IBMNetezza', '#ibm'],
 ['IBMNetezza', '#analytics'],
 ['SandraFeinsmith', '#ibm'],
 ['SandraFeinsmith', '#analytics'],
 ['fleejack', '#healhcare'],
 ['bigdataweek', '#socialmedia'],
 ['sabumjung', '#aws']]

我想计算第二列中单词的频率（例如#socialmedia，＃aws），然后根据该频率选择行。如果单词在数据集中出现三次或更多次，我想保留相应的行（并删除其他行）。所以结果看起来像这样：

data = [['Biz_Innovations', '#socialmedia'],
 ['ChantalGrange', '#aws'],
 ['beyonddevops', '#aws'],
 ['beyonddevops', '#socialmedia'],
 ['bigdataweek', '#socialmedia'],
 ['sabumjung', '#aws']]

有什么建议吗？

Answer 1

>>> import collections, operator
>>> words = collections.Counter(map(operator.itemgetter(1), data))
>>> populars = [p for p in data if words[p[1]] >= 3]

Answer 2

In [16]: from collections import Counter

In [17]: keepers = [a[0] for a in Counter(d[1] for d in data).items() if a[1]>=3]

In [18]: [d for d in data if d[1] in keepers]
Out[18]: 
[['Biz_Innovations', '#socialmedia'],
 ['ChantalGrange', '#aws'],
 ['beyonddevops', '#aws'],
 ['beyonddevops', '#socialmedia'],
 ['bigdataweek', '#socialmedia'],
 ['sabumjung', '#aws']]

Answer 3

您可以使用collections.Counter：

import collections
counts = collections.Counter(tag for (_, tag) in data)
data = [[val, tag] for (val, tag) in data if counts[tag] >= 3]

计算列表中单词的频率并删除不受欢迎的单词

3 个答案: