pandas qcut error:duplicate bins

最新推荐文章于 2024-12-05 14:53:31 发布

Tyanw

最新推荐文章于 2024-12-05 14:53:31 发布

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当遇到pandas qcut的'ValueError: Bin edges must be unique'错误时，可以尝试降低分位数或者使用DataFrame.rank()方法进行数据排名。此外，可以使用自定义的分位数范围，例如[0, .50, .75, 1.]。pandas.cut和pandas.qcut的区别在于：cut根据值本身均匀划分bins，而qcut确保每个bin内的记录数量相等。" 127092780,15043614,C++中cin、cin.getline()与getline()的区别解析,"['C++', '开发语言', '输入输出']

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fix unique bin error:

duplicates='drop'
decrease quantiles
Rank your data with DataFrame.rank(method=‘first’). The ranking assigns a unique value to each element in the dataframe (the rank) while keeping the order of the elements (except for identical values, which will be ranked in order they appear in the array, see method=‘first’)
Example:
pd.qcut(df, nbins) <-- this generates “ValueError: Bin edges must be unique”
Then use this instead:
pd.qcut(df.rank(method='first'), nbins)
Specify a custom quantiles range, e.g. [0, .50, .75, 1.] to get unequal number of items per quantile
Use pandas.cut that chooses the bins to be evenly spaced according to the values themselves, while