计算来自 pandas 数据框的不同单词 [英] Count distinct words from a Pandas Data Frame

问题描述

我有一个Pandas数据框，其中一列包含文本.我想获得一列出现在整列中的唯一单词的列表(空格是唯一的拆分).

I've a Pandas data frame, where one column contains text. I'd like to get a list of unique words appearing across the entire column (space being the only split).

import pandas as pd

r1=['My nickname is ft.jgt','Someone is going to my place']

df=pd.DataFrame(r1,columns=['text'])

输出应如下所示:

['my','nickname','is','ft.jgt','someone','going','to','place']

获得计数也没有什么坏处，但这不是必需的.

It wouldn't hurt to get a count as well, but it is not required.

推荐答案

使用set创建唯一元素的序列.

Use a set to create the sequence of unique elements.

对df进行一些清理，以小写并拆分字符串:

Do some clean-up on df to get the strings in lower case and split:

df['text'].str.lower().str.split()
Out[43]: 
0             [my, nickname, is, ft.jgt]
1    [someone, is, going, to, my, place]

此列中的每个列表都可以传递给set.update函数以获取唯一值.使用 apply 进行此操作:

Each list in this column can be passed to set.update function to get unique values. Use apply to do so:

results = set()
df['text'].str.lower().str.split().apply(results.update)
print results

set(['someone', 'ft.jgt', 'my', 'is', 'to', 'going', 'place', 'nickname'])

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