pandas 错误，“只允许将类似列表的对象传递给 isin()，您传递了一个 [int]”
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Error, 'only list-like objects are allowed to be passed to isin(), you passed a [int]'
提问by John
Following adopted code is just used for example purposes:
以下采用的代码仅用于示例目的：
data = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
'year': [2012, 2012, 2013, 2014, 2014],
'reports': [4, 24, 31, 2, 3]}
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
value_list = ['Tina', 'Molly', 'Jason']
value_list = ['Tina', 'Molly', 'Jason']
df[df.name.isin(value_list)]
Here, it can be seen that a list (i.e., value_list) has been passed. If i don't want to pass a list and just want to pass an integer (i.e, 24 in the reports column to find its corresponding row), what would be the ideal way. I tried to do this, but it actually doesn't works:
到这里，可以看出传入了一个列表（即value_list）。如果我不想传递列表而只想传递一个整数（即，报告列中的 24 以找到其对应的行），那么理想的方法是什么。我试图这样做，但它实际上不起作用：
df[df.reports.isin(24)]
The error comes as: only list-like objects are allowed to be passed to isin(), you passed a [int].
错误是：只允许将类似列表的对象传递给 isin()，您传递了一个 [int]。
Also, how can i find the corresponding 'name' against reports 24, (i.e., Molly)
另外，我如何才能根据报告 24（即 Molly）找到相应的“姓名”
采纳答案by juanpa.arrivillaga
Just use boolean-indexing:
只需使用布尔索引：
>>> df
name reports year
Cochice Jason 4 2012
Pima Molly 24 2012
Santa Cruz Tina 31 2013
Maricopa Jake 2 2014
Yuma Amy 3 2014
>>> df[df.reports == 24]
name reports year
Pima Molly 24 2012
You coulduse .isinwith a single-element list:
您可以使用.isin单元素列表：
>>> df[df.reports.isin([24])]
name reports year
Pima Molly 24 2012
But the boolean-indexing option is what you would typically see.
但是布尔索引选项是您通常会看到的。
If you have a largedata-frame (over 10,000 rows, let's say) and a more complex boolean-expression, you can do this efficiently with df.query:
如果您有一个大型数据框（比方说超过 10,000 行）和一个更复杂的布尔表达式，您可以使用以下命令有效地执行此操作df.query：
>>> df.query("reports==24 or name == 'Jason'")
name reports year
Cochice Jason 4 2012
Pima Molly 24 2012
And this will be fast and memory-efficient if you have the numexprengine available.
如果您有numexpr可用的引擎，这将是快速且节省内存的。
