Question

我有一个这样的数据框：

import requests
from bs4 import BeautifulSoup
import csv

def get_page(url):
    response = requests.get(url)
    if not response.ok:
        print('server responded:', response.status_code)
    else:
        soup = BeautifulSoup(response.text, 'html.parser') # 1. html , 2. parser
    return soup

def get_detail_page(soup):

     try:
        title = (soup.find('h1',class_="cdm_style",id=False).text)
     except:
         title = 'Empty Title'
     try:
         collection = (soup.find('td',id="metadata_collec").find('a').text)
     except:
         collection = "Empty Collection"
     try:
         author = (soup.find('td',id="metadata_creato").text)
     except:
         author = "Empty Author"
     try:
         abstract = (soup.find('td',id="metadata_descri").text)
     except:
         abstract = "Empty Abstract"
     try:
         keywords = (soup.find('td',id="metadata_keywor").text)
     except:
         keywords = "Empty Keywords"
     try:
         publishers = (soup.find('td',id="metadata_publis").text)
     except:
         publishers = "Empty Publishers"
     try:
         date_original = (soup.find('td',id="metadata_contri").text)
     except:
         date_original = "Empty Date original"
     try:
        date_digital = (soup.find('td',id="metadata_date").text)
     except:
        date_digital = "Empty Date digital"
     try:
        formatt = (soup.find('td',id="metadata_source").text)
     except:
        formatt = "Empty Format"
     try:
        release_statement = (soup.find('td',id="metadata_rights").text)
     except:
        release_statement = "Empty Realease Statement"
     try:
        library = (soup.find('td',id="metadata_librar").text)
     except:
        library = "Empty Library"
     try:
        date_created = (soup.find('td',id="metadata_dmcreated").text)
     except:
        date_created = "Empty date Created"
     data = {
         'Title'        : title.strip(),
         'Collection'   : collection.strip(),
         'Author'       : author.strip(),
         'Abstract'     : abstract.strip(),
         'Keywords'     : keywords.strip(),
         'Publishers'   : publishers.strip(),
         'Date_original': date_original.strip(),
         'Date_digital' : date_digital.strip(),
         'Format'       : formatt.strip(),
         'Release-st'   : release_statement.strip(),
         'Library'      : library.strip(),
         'Date_created' : date_created.strip()


     }
     return data
def get_index_data(soup):
    try:
        titles_link = soup.find_all('a',class_="body_link_11")
    except:
        titles_link = []
    else:
        titles_link_output = []
        for link in titles_link:
            try:
                item_id = link.attrs.get('item_id', None) #All titles with valid links will have an item_id
                if item_id:
                    titles_link_output.append("{}{}".format("http://cgsc.cdmhost.com",link.attrs.get('href', None)))
            except:
                continue
    return titles_link_output
def write_csv(data,url):
    with open('1111_to_5555.csv','a') as csvfile:
        writer = csv.writer(csvfile)
        row = [data['Title'], data['Collection'], data['Author'],
        data['Abstract'], data['Keywords'], data['Publishers'], data['Date_original'],
        data['Date_digital'], data['Format'], data['Release-st'], data['Library'],
        data['Date_created'], url]
        writer.writerow(row)
def main():
    for x in range(2,4):
        mainurl = ("http://cgsc.cdmhost.com/cdm/search/collection/p4013coll8/searchterm/1/field/all/mode/all/conn/and/order/nosort/page/")
        print(x)
        url = f"{mainurl}{x}"
        products = get_index_data(get_page(url))
        for product in products:
            data1 = get_detail_page(get_page(product))
            write_csv(data1,product)


if __name__ == '__main__':
    main()

我想按大小分组，然后减去然后取平均值

df = pd.DataFrame({'size':['A','A','B','B','B','C','C','C','C'],
                   'value': [2,3,1,4,5,1,0,2,3,]})
size value
A    2
A    3
B    1
B    4
B    5
C    1
C    0
C    2
C    3

我希望我的输出看起来像这样：

df.groupby('size').agg({'value':'mean'})

      mean value
size          
A     2.5000
B     3.3333
C     1.5000

Answer 1

您可以先Groupby+transform，然后再subtract：

df['value'] = df['value'].sub(df.groupby('size')['value'].transform('mean'))
#or df.groupby('size')['value'].transform(lambda x: x - x.mean()) as sammywemmy suggests
print(df)

  size     value
0    A -0.500000
1    A  0.500000
2    B -2.333333
3    B  0.666667
4    B  1.666667
5    C -0.500000
6    C -1.500000
7    C  0.500000
8    C  1.500000

大熊猫按均值减去后

1 个答案: