熊猫按分位数过滤导致空集

Question

如何pandas.Series通过分位数仓来过滤分位数？我在这里的三种不同方法要么完全失败，要么导致空集。

所需的解决方案将使用 df.query()

df = pd.DataFrame({'my_series':[1,2,3,4,5,6,7]})
df['quantile'] = pd.qcut(df.my_series, [0,0.5,0.6,1])
print(df)
#df[df.quantile == '(4.6, 7.0]'] # fails with key error :false

df['string_quantiles'] = df['quantile'].astype(object)
print(df)
display(df[df['string_quantiles'] == '(4.6, 7.0]']) # no failure, but empty set

df.query("my_series == '(0.999, 4.0]'") # empty set

Answer 1

添加astype转换

yourdf=df[df['string_quantiles'].astype(str)=='(4.6, 7.0]'].copy()
Out[60]: 
   my_series    quantile string_quantiles
4          5  (4.6, 7.0]       (4.6, 7.0]
5          6  (4.6, 7.0]       (4.6, 7.0]
6          7  (4.6, 7.0]       (4.6, 7.0]

要么

df[df['quantile'].map(lambda x : x.left)==4.6].copy()