Question

import csv

import requests
from bs4 import BeautifulSoup

url = 'http://www.showmeboone.com/sheriff/JailResidents/JailResidents.asp'
response = requests.get(url)
html = response.content

soup = BeautifulSoup(html, "html.parser")

fileList = []

# For the table-header cells
tableHeader = soup.find('tr', attrs={'class': 'table-header'})
rowList = []
for cell in tableHeader.findAll('th'):
    cellText = cell.text.replace(' ', '').replace('\n', '')
    rowList.append(cellText)
fileList.append(rowList)

# For the table body cells
table = soup.find('tbody', attrs={'class': 'stripe'})
for row in table.findAll('tr'):
    rowList = []
    for cell in row.findAll('td'):
        cellText = cell.text.replace(' ', '').replace('\n', '')

        if cellText == "Details":
            continue

        rowList.append(cellText)

    fileList.append(rowList)

outfile = open("./prison-inmates.csv", "w")
writer = csv.writer(outfile)
writer.writerows(fileList)

我想为每个A B C D 0 01:00:00 2002-01-16 10 3 1 01:30:00 2002-01-16 10 -12 2 02:00:00 2002-01-16 10 7 3 01:00:00 2002-01-17 20 33 4 01:30:00 2002-01-17 20 -27 5 02:00:00 2002-01-17 20 12 results = {}组选择一行，取第一个行，满足下列条件之一：

D＆gt; = C *（0.5）
D＆lt; = C *（ - 1）
否则，走最后一排。

输出应为：

我试过了：

          A           B   C   D
1  01:30:00  2002-01-16  10 -12
3  01:00:00  2002-01-17  20  33

Answer 1

除了使用groupby.apply之外你或多或少有你所拥有的东西，同样来自你想要的输出它似乎没有优先考虑第一个条件，在这种情况下，你需要将这两个条件与结合起来或 |：

def first_last(g):
    # this is used at multiple places, cache the condition
    cond = g.D.ge(g.C.mul(0.5)) | g.D.le(g.C.mul(-1))

    if cond.any():
        return g[cond].iloc[0]
    else:
        return g.iloc[-1]

df.groupby('B', as_index=False).apply(first_last)

#          A             B   C    D
#0  01:30:00    2002-01-16  10  -12
#1  01:00:00    2002-01-17  20   33

或更短的版本：

def first_last(g):
    cond = g.D.ge(g.C.mul(0.5)) | g.D.le(g.C.mul(-1))

    return g[cond].iloc[0] if cond.any() else g.iloc[-1]

df.groupby('B', as_index=False).apply(first_last)

选择每组迭代的第一个条件

1 个答案: