Python 从 Pandas 中的系列创建一个集合
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Create a set from a series in pandas
提问by Julio Arriaga
I have a dataframe extracted from Kaggle's San Fransico Salaries: https://www.kaggle.com/kaggle/sf-salariesand I wish to create a set of the values of a column, for instance 'Status'.
我有一个从 Kaggle 的 San Fransico Salaries 中提取的数据框：https://www.kaggle.com/kaggle/sf-salaries ，我希望创建一组列的值，例如“状态”。
This is what I have tried but it brings a list of all the records instead of the set (sf is how I name the data frame).
这是我尝试过的，但它带来了所有记录的列表而不是集合（sf 是我命名数据框的方式）。
a=set(sf['Status'])
print a
According to this webpage, this should work. How to construct a set out of list items in python?
根据这个网页，这应该有效。 如何在python中构造一组列表项？
回答by grechut
If you only need to get list of unique values, you can just use uniquemethod.
If you want to have Python's set, then do set(some_series)
如果您只需要获取唯一值列表，则可以使用unique方法。如果您想设置 Python，请执行以下操作set(some_series)
In [1]: s = pd.Series([1, 2, 3, 1, 1, 4])
In [2]: s.unique()
Out[2]: array([1, 2, 3, 4])
In [3]: set(s)
Out[3]: {1, 2, 3, 4}
However, if you have DataFrame, just select series out of it ( some_data_frame['<col_name>']).
但是，如果您有 DataFrame，只需从中选择系列 ( some_data_frame['<col_name>'])。
回答by Adrien Pacifico
With large size serieswith duplicates the set(some_series)execution-time will evolve exponentially with seriessize.
对于series具有重复项的大尺寸，set(some_series)执行时间将随series尺寸呈指数级变化。
Better practice would be to set(some_series.unique()).
更好的做法是将set(some_series.unique()).
