在python中为csv的数据添加新行

时间：2016-03-16 13:27:39

标签： python excel csv beautifulsoup python-requests

我试图从http://www.hoopsstats.com/basketball/fantasy/nba/opponentstats/16/12/eff/1-1抓取数据以使用Python 3.5创建CSV文件。我已经知道如何操作，但是当我在excel中打开文件时，所有数据都在同一行。

    import sys
import requests
from bs4 import BeautifulSoup
import csv

r = requests.get('http://www.hoopsstats.com/basketball/fantasy/nba/opponentstats/16/12/eff/1-1')


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

stats = soup.find_all('table', 'statscontent')

pgFile = open ('C:\\Users\\James\\Documents\\testpoop.csv', 'w')

for table in soup.find_all('table', 'statscontent','a'):
    stats = [ stat.text for stat in table.find_all('center') ]
    team = [team for team in table.find('a')]


    p = (team,stats)

    z = str(p)



    a = z.replace("]",'') 
    b = a.replace("'", "")
    c = b.replace(")", "")   #Only way I knew how to clean up extra characters
    d = c.replace("(", "")
    e = d.replace("[", "")

    print(e)                 #printing while testing

    pgFile.writelines(e)
pgFile.close()

数据在python shell中很好用：

   Boston, 1, 67, 47.9, 19.6, 5.2, 7.2, 1.8, 0.5, 4.3, 4.1, 4.3, 0.9, 6.8-16.1, .421, 1.6-4.9, .324, 4.4-5.4, .816, 19.7, -6.8
San Antonio, 2, 67, 47.8, 19.7, 5.0, 8.7, 1.9, 0.3, 3.5, 3.3, 4.2, 0.8, 7.4-18.0, .411, 1.5-4.6, .317, 3.4-4.2, .819, 20.7, -2.4
Atlanta, 3, 67, 48.7, 19.2, 5.6, 8.4, 2.3, 0.6, 4.1, 3.7, 4.6, 1.0, 7.1-17.6, .401, 2.0-5.8, .338, 3.2-3.8, .828, 20.8, -5.6
Miami, 4, 67, 49.8, 20.6, 5.2, 8.0, 1.9, 0.3, 3.2, 3.6, 4.3, 0.9, 7.6-18.5, .407, 1.9-5.3, .348, 3.7-4.5, .814, 21.0, 2.1
L.A.Clippers, 5, 66, 48.2, 21.0, 5.7, 8.7, 1.9, 0.2, 4.1, 4.5, 4.6, 1.1, 7.6-18.7, .405, 1.9-5.4, .346, 3.9-4.9, .799, 21.1, -7.0
Toronto, 6, 66, 48.0, 20.5, 5.3, 8.8, 1.7, 0.6, 3.8, 3.7, 4.4, 0.9, 7.4-18.0, .412, 2.1-5.9, .349, 3.6-4.4, .826, 21.6, -4.3
Charlotte, 7, 66, 48.1, 19.3, 6.0, 9.1, 1.6, 0.6, 3.4, 4.1, 5.1, 0.9, 7.1-17.8, .399, 2.0-6.4, .321, 3.0-3.7, .802, 21.7, -4.5
Milwaukee, 8, 68, 48.8, 19.3, 5.4, 9.1, 1.9, 0.3, 4.2, 3.5, 4.6, 0.8, 6.8-15.9, .425, 1.9-6.0, .311, 3.9-5.0, .788, 21.7, 2.1
Utah, 9, 67, 49.3, 21.9, 5.5, 8.1, 2.3, 0.4, 3.7, 3.4, 4.5, 1.0, 7.8-18.3, .424, 2.2-5.7, .382, 4.1-5.3, .787, 22.7, 5.8
Memphis, 10, 67, 48.7, 22.4, 5.1, 8.3, 1.6, 0.4, 3.9, 4.1, 4.3, 0.8, 7.7-17.7, .434, 2.5-7.0, .358, 4.6-5.7, .813, 22.9, -2.0
Detroit, 11, 67, 49.1, 22.3, 5.8, 8.4, 1.6, 0.3, 3.7, 4.2, 4.9, 0.9, 8.4-19.1, .441, 2.0-5.5, .362, 3.5-4.4, .801, 23.2, -0.1
Minnesota, 12, 67, 47.1, 21.9, 5.3, 8.7, 2.0, 0.3, 3.6, 3.9, 4.3, 1.0, 8.1-18.7, .434, 2.2-6.5, .336, 3.5-4.2, .826, 23.3, -2.8
Portland, 13, 68, 47.8, 22.5, 5.1, 8.1, 1.8, 0.5, 3.1, 3.7, 4.1, 1.0, 8.2-18.8, .438, 2.1-5.7, .370, 4.0-5.1, .777, 23.3, -1.0
New York, 14, 68, 47.5, 21.2, 6.0, 8.5, 1.9, 0.2, 3.0, 2.6, 4.9, 1.1, 7.7-18.3, .419, 1.8-5.2, .342, 4.1-5.0, .819, 23.3, 6.4
Houston, 15, 67, 50.9, 21.3, 6.2, 9.8, 2.3, 0.3, 5.0, 4.3, 5.3, 0.9, 7.7-18.4, .417, 2.3-6.7, .351, 3.6-4.4, .809, 23.3, 6.1
Indiana, 16, 67, 49.3, 23.3, 5.9, 8.3, 1.8, 0.4, 4.6, 3.9, 5.0, 0.9, 8.3-18.8, .443, 2.3-5.8, .387, 4.3-5.3, .813, 23.7, 5.4
Chicago, 17, 65, 48.9, 22.2, 6.4, 8.6, 2.1, 0.6, 2.9, 2.8, 5.2, 1.2, 8.2-20.3, .407, 1.8-5.6, .323, 3.9-5.2, .764, 23.8, 4.7
Golden State, 18, 66, 49.3, 24.5, 5.1, 8.4, 2.4, 0.2, 3.7, 4.1, 4.0, 1.2, 9.1-21.3, .427, 2.3-6.6, .350, 4.0-5.0, .802, 23.8, -14.7
Dallas, 19, 67, 49.5, 22.1, 6.0, 8.3, 2.0, 0.4, 3.3, 4.0, 5.1, 0.9, 8.3-18.7, .440, 2.1-6.1, .347, 3.4-4.4, .778, 24.0, 2.0
Washington, 20, 66, 49.5, 23.8, 5.8, 8.2, 2.0, 0.3, 4.4, 3.9, 5.0, 0.9, 8.9-20.1, .444, 2.5-6.4, .398, 3.5-4.1, .851, 24.1, -4.6
Cleveland, 21, 66, 49.3, 22.9, 5.7, 9.1, 1.9, 0.3, 3.5, 3.3, 4.9, 0.8, 8.3-19.4, .428, 2.0-5.5, .360, 4.3-5.1, .837, 24.3, 1.0
Denver, 22, 68, 48.6, 21.8, 5.9, 8.8, 1.9, 0.5, 3.3, 3.8, 4.9, 1.0, 7.8-17.9, .436, 2.4-6.5, .369, 3.9-4.9, .783, 24.5, 5.8
Philadelphia, 23, 67, 48.6, 21.9, 6.0, 8.8, 2.3, 0.5, 4.1, 3.4, 5.0, 0.9, 8.0-17.8, .447, 1.7-4.7, .366, 4.2-5.0, .837, 24.7, 2.8
Oklahoma City, 24, 67, 48.1, 22.6, 6.1, 8.5, 2.1, 0.3, 3.1, 3.8, 5.0, 1.1, 8.2-18.7, .440, 2.4-5.9, .405, 3.8-5.0, .750, 24.8, -10.4
Orlando, 25, 66, 49.6, 22.9, 6.7, 9.2, 1.9, 0.6, 4.3, 3.5, 5.7, 1.0, 8.2-18.5, .444, 2.3-6.1, .385, 4.2-5.2, .794, 25.6, 5.7
Brooklyn, 26, 67, 48.5, 23.0, 5.5, 9.0, 2.4, 0.3, 3.5, 3.2, 4.5, 1.0, 8.6-18.6, .463, 2.6-6.6, .390, 3.3-4.3, .768, 25.8, 3.4
Sacramento, 27, 66, 49.7, 23.7, 5.9, 9.5, 2.3, 0.4, 4.0, 3.6, 4.8, 1.0, 8.6-19.8, .436, 2.6-7.5, .346, 3.9-4.7, .834, 25.9, -0.3
New Orleans, 28, 66, 49.9, 24.3, 5.7, 8.9, 1.6, 0.4, 3.5, 3.6, 4.8, 0.9, 8.7-18.2, .475, 2.6-6.3, .415, 4.4-5.3, .821, 26.9, 0.8
L.A.Lakers, 29, 68, 49.5, 24.5, 6.0, 9.8, 1.9, 0.4, 3.4, 3.3, 4.9, 1.1, 9.3-20.6, .449, 2.3-6.7, .349, 3.6-4.5, .818, 26.9, 4.8
Phoenix, 30, 67, 49.0, 25.3, 5.8, 9.5, 2.3, 0.4, 4.1, 4.0, 4.7, 1.1, 9.2-20.3, .452, 2.6-6.6, .388, 4.4-5.6, .788, 27.0, 7.1

但是当在excel中打开时，每个值都在其自己的单元格中，但它们都在第一行中。我想为每个团队换一个新行。

1 个答案:

答案 0 :(得分：2)

使用csv.writer将CSV数据写入CSV文件：

import csv

import requests
from bs4 import BeautifulSoup

r = requests.get('http://www.hoopsstats.com/basketball/fantasy/nba/opponentstats/16/12/eff/1-1')
soup = BeautifulSoup(r.text, "html.parser")

with open("output.csv", "w") as f:
    writer = csv.writer(f)

    for table in soup.find_all('table', class_='statscontent'):
        team = table.find('a').text
        stats = [team] + [stat.text for stat in table.find_all('center')]

        writer.writerow(stats)

现在，在output.csv中将写入以下内容：

Boston,1,67,47.9,19.6,5.2,7.2,1.8,0.5,4.3,4.1,4.3,0.9,6.8-16.1,.421,1.6-4.9,.324,4.4-5.4,.816,19.7,-6.8
San Antonio,2,67,47.8,19.7,5.0,8.7,1.9,0.3,3.5,3.3,4.2,0.8,7.4-18.0,.411,1.5-4.6,.317,3.4-4.2,.819,20.7,-2.4
Atlanta,3,67,48.7,19.2,5.6,8.4,2.3,0.6,4.1,3.7,4.6,1.0,7.1-17.6,.401,2.0-5.8,.338,3.2-3.8,.828,20.8,-5.6
Miami,4,67,49.8,20.6,5.2,8.0,1.9,0.3,3.2,3.6,4.3,0.9,7.6-18.5,.407,1.9-5.3,.348,3.7-4.5,.814,21.0,2.1
L.A.Clippers,5,66,48.2,21.0,5.7,8.7,1.9,0.2,4.1,4.5,4.6,1.1,7.6-18.7,.405,1.9-5.4,.346,3.9-4.9,.799,21.1,-7.0
Toronto,6,66,48.0,20.5,5.3,8.8,1.7,0.6,3.8,3.7,4.4,0.9,7.4-18.0,.412,2.1-5.9,.349,3.6-4.4,.826,21.6,-4.3
Charlotte,7,66,48.1,19.3,6.0,9.1,1.6,0.6,3.4,4.1,5.1,0.9,7.1-17.8,.399,2.0-6.4,.321,3.0-3.7,.802,21.7,-4.5
Milwaukee,8,68,48.8,19.3,5.4,9.1,1.9,0.3,4.2,3.5,4.6,0.8,6.8-15.9,.425,1.9-6.0,.311,3.9-5.0,.788,21.7,2.1
...
Sacramento,27,66,49.7,23.7,5.9,9.5,2.3,0.4,4.0,3.6,4.8,1.0,8.6-19.8,.436,2.6-7.5,.346,3.9-4.7,.834,25.9,-0.3
New Orleans,28,66,49.9,24.3,5.7,8.9,1.6,0.4,3.5,3.6,4.8,0.9,8.7-18.2,.475,2.6-6.3,.415,4.4-5.3,.821,26.9,0.8
L.A.Lakers,29,68,49.5,24.5,6.0,9.8,1.9,0.4,3.4,3.3,4.9,1.1,9.3-20.6,.449,2.3-6.7,.349,3.6-4.5,.818,26.9,4.8
Phoenix,30,67,49.0,25.3,5.8,9.5,2.3,0.4,4.1,4.0,4.7,1.1,9.2-20.3,.452,2.6-6.6,.388,4.4-5.6,.788,27.0,7.1
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