将每个值放在百分位数的 pandas 中 [英] Placing every value in its percentile in Pandas

问题描述

考虑具有以下百分位数的系列:

Consider a Series with the following percentiles:

> df['col_1'].describe(percentiles=np.linspace(0, 1, 20))

count      13859.000000
mean         421.772842
std        14665.298998
min            1.201755
0%             1.201755
5.3%           1.430695
10.5%          1.438417
15.8%          1.466462
21.1%          1.473050
26.3%          1.500834
31.6%          1.512218
36.8%          1.542935
42.1%          1.579845
47.4%          1.647162
50%            1.690612
52.6%          1.749047
57.9%          1.955589
63.2%          2.344475
68.4%          3.075641
73.7%          4.466094
78.9%          8.410964
84.2%         14.998738
89.5%         41.363612
94.7%        162.865079
100%     1511013.790233
max      1511013.790233
Name: col_1, dtype: float64

我想获得另一列col_2，其中在上述计算中将每一行分配给该百分比.

I would like to get another column col_2 with the percentile each row was assigned to in the calculation made above.

如何在熊猫中做到这一点?

How can I do that in Pandas?

推荐答案

df2 = pd.DataFrame(range(1000))
df2.columns = ['a1']
df2['percentile'] = pd.qcut(df2.a1,100, labels=False)

或省略标签以查看范围

请注意，在Pandas 0.16.2(截至今天的最新版本)的Python 3中，您需要使用list(range(1000))而不是range(1000)才能使上述内容起作用.

Note that in Python 3, with Pandas 0.16.2 (latest version as of today), you need to use list(range(1000)) instead of range(1000) for the above to work.

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