Pandas：查询字符串，其中列名包含特殊字符
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Pandas: query string where column name contains special characters
提问by Joe
I am working with a data frame that has a structure something like the following:
我正在使用具有如下结构的数据框：
In[75]: df.head(2)
Out[75]:
statusdata participant_id association latency response \
0 complete CLIENT-TEST-1476362617727 seeya 715 dislike
1 complete CLIENT-TEST-1476362617727 welome 800 like
stimuli elementdata statusmetadata demo$gender demo$question2 \
0 Sample B semi_imp complete male 23
1 Sample C semi_imp complete female 23
I want to be able to run a query string against the column demo$gender.
我希望能够对列运行查询字符串demo$gender。
I.e,
IE，
df.query("demo$gender=='male'")
But this has a problem with the $sign. If I replace the $sign with another delimited (like -) then the problem persists. Can I fix up my query string to avoid this problem. I would prefer not to rename the columns as these correspond tightly with other parts of my application.
但是这个$标志有问题。如果我$用另一个分隔符（如-）替换该符号，则问题仍然存在。我可以修复我的查询字符串以避免这个问题。我不想重命名这些列，因为它们与我的应用程序的其他部分紧密对应。
I really want to stick with a query string as it is supplied by another component of our tech stack and creating a parser would be a heavy lift for what seems like a simple problem.
我真的很想坚持使用查询字符串，因为它是由我们技术堆栈的另一个组件提供的，而创建解析器对于看似简单的问题来说将是一项艰巨的任务。
Thanks in advance.
提前致谢。
回答by Joe
For the interested here is a simple proceedure I used to accomplish the task:
对于感兴趣的人，这是我用来完成任务的一个简单程序：
# Identify invalid column names
invalid_column_names = [x for x in list(df.columns.values) if not x.isidentifier() ]
# Make replacements in the query and keep track
# NOTE: This method fails if the frame has columns called REPL_0 etc.
replacements = dict()
for cn in invalid_column_names:
r = 'REPL_'+ str(invalid_column_names.index(cn))
query = query.replace(cn, r)
replacements[cn] = r
inv_replacements = {replacements[k] : k for k in replacements.keys()}
df = df.rename(columns=replacements) # Rename the columns
df = df.query(query) # Carry out query
df = df.rename(columns=inv_replacements)
Which amounts to identifying the invalid column names, transforming the query and renaming the columns. Finally we perform the query and then translate the column names back.
这相当于识别无效的列名，转换查询并重命名列。最后，我们执行查询，然后将列名翻译回来。
Credit to @chrisb for their answer that pointed me in the right direction
感谢@chrisb 的回答，为我指明了正确的方向
回答by chrisb
The current implementation of queryrequires the string to be a valid python expression, so column names must be valid python identifiers. Your two options are renaming the column, or using a plain boolean filter, like this:
的当前实现query要求字符串是有效的 Python 表达式，因此列名必须是有效的 Python 标识符。您的两个选项是重命名列，或使用普通布尔过滤器，如下所示：
df[df['demo$gender'] =='male']
