测试Dataframe内容的真值时如何解决ValueError？ Python

Question

我有一个看起来像这样的数据框。

   done    sentence                        3_tags
0  0       ['What', 'were', 'the', '...]   ['WP', 'VBD', 'DT']
1  0       ['What', 'was', 'the', '...]    ['WP', 'VBD', 'DT']
2  0       ['Why', 'did', 'John', '...]    ['WP', 'VBD', 'NN']
...

对于每一行，我想检查“3_tags”列中的列表是否在列表 temp1 中，如下所示：

a = pd.read_csv('sentences.csv')
temp1 = [ ['WP', 'VBD', 'DT'], ['WRB', 'JJ', 'VBZ'], ['WP', 'VBD', 'DT'] ]
q = a['3_tags'] 
q in temp1

对于第0行的第一个句子，'3_tags'的值=['WP','VBD','DT'] 在 temp1 中，所以我希望上面的结果是：

True

但是，我得到这个错误：

ValueError: Arrays were different lengths: 1 vs 3

我怀疑q的数据类型有问题：

print(type(q))
<class 'pandas.core.series.Series'>

问题是q是一个系列，temp1包含列表吗？我应该怎么做才能得到合乎逻辑的结果 'True' ？

Answer 1

您希望这些列表改为元组。
然后使用 pd.Series.isin

*temp1, = map(tuple, temp1)

q = a['3_tags'].apply(tuple)

q.isin(temp1)

0     True
1     True
2    False
Name: 3_tags, dtype: bool

但是，'3_tags' 列似乎由看起来像列表的字符串组成。在这种情况下，我们想用 ast.literal_eval

来解析它们

from ast import literal_eval

*temp1, = map(tuple, temp1)

q = a['3_tags'].apply(lambda x: tuple(literal_eval(x)))

q.isin(temp1)

0     True
1     True
2    False
Name: 3_tags, dtype: bool

设置 1

a = pd.DataFrame({
    'done': [0, 0, 0],
    'sentence': list(map(str.split, ('What were the', 'What was the', 'Why did John'))),
    '3_tags': list(map(str.split, ('WP VBD DT', 'WP VBD DT', 'WP VBD NN')))
}, columns='done sentence 3_tags'.split())

temp1 = [['WP', 'VBD', 'DT'], ['WRB', 'JJ', 'VBZ'], ['WP', 'VBD', 'DT']]

设置2

a = pd.DataFrame({
    'done': [0, 0, 0],
    'sentence': list(map(str.split, ('What were the', 'What was the', 'Why did John'))),
    '3_tags': list(map(str, map(str.split, ('WP VBD DT', 'WP VBD DT', 'WP VBD NN'))))
}, columns='done sentence 3_tags'.split())

temp1 = [['WP', 'VBD', 'DT'], ['WRB', 'JJ', 'VBZ'], ['WP', 'VBD', 'DT']]

测试Dataframe内容的真值时如何解决ValueError？ Python

How to solve ValueError when testing truth value of Dataframe contents? Python

python-3.x

pandas

valueerror