Question

我知道如何append a column counting the number of elements in a group，但我需要这样做只是为了满足某个条件的群组中的数字。

例如，如果我有以下数据：

import numpy as np
import pandas as pd

columns=['group1', 'value1']

data = np.array([np.arange(5)]*2).T
mydf = pd.DataFrame(data, columns=columns)

mydf.group1 = [0,0,1,1,2]
mydf.value1 = ['P','F',100,10,0]

valueslist={'50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','96','97','98','99','100','A','B','C','D','P','S'}

因此我的数据框如下所示：

mydf

   group1 value1
0       0      P
1       0      F
2       1    100
3       1     10
4       2      0

然后，我想计算group1中value1所在的每个valuelist值内的行数。

我想要的输出是：

   group1 value1 count
0       0      P     1
1       0      F     1
2       1    100     1
3       1     10     1
4       2      0     0

Answer 1

更改value1列的类型以匹配您的valueslist（或相反）后，您可以使用isin获取True / False列，并使用{{1将其转换为1和0 }}。然后我们可以应用普通的groupby变换：

astype(int)

Answer 2

您可以对每个group1进行分组，然后使用transform查找值是否在列表中的最大值。

mydf['count'] = mydf.groupby('group1').transform(lambda x: x.astype(str).isin(valueslist).sum())

   group1 value1  count
0       0      P      1
1       0      F      1
2       1    100      1
3       1     10      1
4       2      0      0

Answer 3

mydf.value1=mydf.value1.astype(str)
mydf['count']=mydf.group1.map(mydf.groupby('group1').apply(lambda x : sum(x.value1.isin(valueslist))))
mydf
Out[412]: 
   group1 value1  count
0       0      P      1
1       0      F      1
2       1    100      1
3       1     10      1
4       2      0      0

数据输入：

valueslist=['50','51','52','53','54','55','56','57','58','59','60','61','62','63','64','65','66','67','68','69','70','71','72','73','74','75','76','77','78','79','80','81','82','83','84','85','86','87','88','89','90','91','92','93','94','95','96','97','98','99','100','A','B','C','D','P','S']

Answer 4

这是一种方法，尽管是单行：

import * as React from 'react';
import { LeftNavigation } from "../src/components/LeftNavigation";
import { mount } from 'enzyme';
import { MemoryRouter } from 'react-router-dom'

describe("<LeftNavigation />", () => {
    const wrapper;
    // Testing components that renders a <Link> or a <Route>, may cause 
    // errors and warnings about context. It is recommended to wrap your
    // tests in a <StaticRouter> or <MemoryRouter>

    beforeEach(() => {
        wrapper = mount(
            <MemoryRouter><LeftNavigation title="Protocol Vantage Points" path="/hello"/></MemoryRouter>
        );
    });

    it("renders the title", () => {
        expect(wrapper.find(".uk-h3 span").text()).toBe("Protocol Vantage Points");
    });

    it("renders first menu item 'On demand tests'", () => {
        expect(wrapper.find("#synth-left-nav .uk-nav li a").at(0).text()).toEqual("On demand tests");
    });

    it("renders second menu item 'Feel status'", () => {
        expect(wrapper.find("#synth-left-nav .uk-nav li a").at(1).text()).toBe("Fleet status");
    });
});

将满足组内条件的行数附加到Pandas数据帧

4 个答案: