基于另一个数据帧 Python 和 Pandas 从数据帧中采样

Posted 2023-03-12

【中文标题】基于另一个数据帧 Python 和 Pandas 从数据帧中采样

【英文标题】：Sampling from dataframe based on another dataframe Python and Pandas

【发布时间】：2021-05-27 09:33:52

【问题描述】：

希望你们一切都好。

我有两个不同的数据框，如下所示。

主表：

Car	type	year	condition	price	No.users	No.seats
BZ	SV	2000-2010	old	10000	2	7
BM	SD	2000-2010	new	8000	3	2
BM	SV	2000-2010	old	9000	1	4
BZ	SD	2000-2010	new	7000	3	5
BM	SV	2000-2010	new	5000	5	2
BM	SD	2000-2010	old	3000	6	2
BZ	SV	2010-2020	old	20000	2	4
BZ	SV	2010-2020	new	1000	8	4
BZ	SV	2000-2010	new	5000	0	5
BZ	SD	2000-2010	old	4000	1	7

样本表 我想根据这张表进行抽样

city	type	year	No.sample
BZ	SV	2000-2010	1
BZ	SV	2010-2020	1
BZ	SD	2000-2010	1
BM	SV	2000-2010	1
BM	SD	2000-2010	1

我尝试了不同的方法，但我想知道如何根据 SampleTable 随机抽样行。

【参考方案1】：

看看this answer:

import pandas as pd

data = pd.DataFrame('cols1':[4, 5, 5, 4, 321, 32, 5],
                     'clol2':[45, 66, 6, 6, 1, 432, 3],
                     'class':['A', 'B', 'C', 'C', 'A', 'B', 'B'])

freq = pd.DataFrame('class':['A', 'B', 'C'],
                     'nostoextract':[2, 2, 2], )

def bootstrap(data, freq):
    freq = freq.set_index('class')

    # This function will be applied on each group of instances of the same
    # class in `data`.
    def sampleClass(classgroup):
        cls = classgroup['class'].iloc[0]
        nDesired = freq.nostoextract[cls]
        nRows = len(classgroup)

        nSamples = min(nRows, nDesired)
        return classgroup.sample(nSamples)

    samples = data.groupby('class').apply(sampleClass)

    # If you want a new index with ascending values
    # samples.index = range(len(samples))

    # If you want an index which is equal to the row in `data` where the sample
    # came from
    samples.index = samples.index.get_level_values(1)

    # If you don't change it then you'll have a multiindex with level 0
    # being the class and level 1 being the row in `data` where
    # the sample came from.

    return samples

print(bootstrap(data,freq))

您可以将“城市”、“类型”和“年份”列合并为一个新列：

准备MainTable:

MainTable["combination"] = MainTable["city"] + MainTable["type"] + MainTable["year"]

准备SampleTable:

SampleTable["combination"] = SampleTable["city"] + SampleTable["type"] + SampleTable["year"]

然后您根据链接答案中的SampleTable["combination"].value_counts() 而不是freq["class"] 进行抽样。