Python：结合低频因素类别计数

Python：结合低频因素/类别计数

通过找到占用百分比来遮罩，即：

series = pd.value_counts(df.column)mask = (series/series.sum() * 100).lt(1)# To replace df['column'] use np.where I.e df['column'] = np.where(df['column'].isin(series[mask].index),'Other',df['column'])

要使用sum更改索引：

new = series[~mask]new['Other'] = series[mask].sum()Windows      26083iOS          19711Android      13077Macintosh     5799Other          832Name: 1, dtype: int64

如果要替换索引，则：

series.index = np.where(series.index.isin(series[mask].index),'Other',series.index)Windows      26083iOS          19711Android      13077Macintosh     5799Other          347Other          285Other          167Other22Other11Name: 1, dtype: int64

说明

(series/series.sum() * 100) # This will give you the percentage i.eWindows          39.820158iOS   30.092211Android          19.964276Macintosh         8.853165Chrome OS         0.529755Linux  0.435101Windows Phone     0.254954(not set)         0.033587BlackBerry        0.016793Name: 1, dtype: float64

.lt(1)

等于小于1。这会根据该掩码索引为您提供一个布尔掩码并分配数据