如何使用 Python、Pandas 创建一个 Decile 和 Quintile 列以根据大小对另一个变量进行排名？
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How to create a Decile and Quintile columns to rank another variable based on size using Python, Pandas?
提问by finstats
I have a data frame with a column containing Investmentwhich represents the amount invested by a trader. I would like to create 2 new columns in the data frame; one giving a decile rank and the other a quintile rank based on the Investmentsize. I want 1 to represent the decile with the largest Investments and 10 representing the smallest. Smilarly, I want 1 to represent the quintile with the largest investments and 5 representing the smallest.
我有一个数据框，其中一列包含Investment代表交易者投资的金额。我想在数据框中创建 2 个新列；一个根据Investment大小给出十分位数排名，另一个给出五分位数排名。我希望 1 代表投资最大的十分位数，10 代表最小的十分位数。类似地，我希望 1 代表投资最大的五分之一，而 5 代表投资最少的五分之一。
I am new to Pandas, so is there a way that I can easily do this? Thanks!
我是 Pandas 的新手，有什么方法可以轻松做到这一点吗？谢谢！
采纳答案by Dan Frank
The functionality you're looking for is in pandas.qcuthttp://pandas.pydata.org/pandas-docs/stable/generated/pandas.qcut.html
您正在寻找的功能在pandas.qcuthttp://pandas.pydata.org/pandas-docs/stable/generated/pandas.qcut.html
In [51]: import numpy as np
In [52]: import pandas as pd
In [53]: investment_df = pd.DataFrame(np.arange(10), columns=['investment'])
In [54]: investment_df['decile'] = pd.qcut(investment_df['investment'], 10, labels=False)
In [55]: investment_df['quintile'] = pd.qcut(investment_df['investment'], 5, labels=False)
In [56]: investment_df
Out[56]:
investment decile quintile
0 0 0 0
1 1 1 0
2 2 2 1
3 3 3 1
4 4 4 2
5 5 5 2
6 6 6 3
7 7 7 3
8 8 8 4
9 9 9 4
It's nonstandard to label the largest percentile with the smallest number but you can do this by
用最小的数字标记最大的百分位数是不标准的，但您可以通过
In [60]: investment_df['quintile'] = pd.qcut(investment_df['investment'], 5, labels=np.arange(5, 0, -1))
In [61]: investment_df['decile'] = pd.qcut(investment_df['investment'], 10, labels=np.arange(10, 0, -1))
In [62]: investment_df
Out[62]:
investment decile quintile
0 0 10 5
1 1 9 5
2 2 8 4
3 3 7 4
4 4 6 3
5 5 5 3
6 6 4 2
7 7 3 2
8 8 2 1
9 9 1 1
