Python-如何计算列表中的特定部分

我是python的新手，我正在努力在python中添加cvs文件的某些部分。我不允许使用“导入CV” 我正在从导入TipJoke CVS文件

这是我迄今为止唯一有效的代码，我完全不知道从这里该怎么走

if __name__ == '__main__':
from pprint import pprint
from string import punctuation
f = open("TipJoke.csv", "r")
tipList = []
for line in f:
    #deletes the quotes
    line = line.replace('"', '')
    tipList.append(line)
pprint(tipList[])

输出：

 [',Card,Tip,Ad,Joke,None\n',
 '1,None,1,0,0,1\n',
 '2,Joke,1,0,1,0\n',
 '3,Ad,0,1,0,0\n',
 '4,None,0,0,0,1\n',
 '5,None,1,0,0,1\n',
 '6,None,0,0,0,1\n',
 '7,Ad,0,1,0,0\n',
 '8,Ad,0,1,0,0\n',
 '9,None,0,0,0,1\n',
 '10,None,0,0,0,1\n',
 '11,None,1,0,0,1\n',
 '12,Ad,0,1,0,0\n',
 '13,None,0,0,0,1\n',
 '14,Ad,1,1,0,0\n',
 '15,Joke,1,0,1,0\n',
 '16,Joke,0,0,1,0\n',
 '17,Joke,1,0,1,0\n',
 '18,None,0,0,0,1\n',
 '19,Joke,0,0,1,0\n',
 '20,None,0,0,0,1\n',
 '21,Ad,1,1,0,0\n',
 '22,Ad,1,1,0,0\n',
 '23,Ad,0,1,0,0\n',
 '24,Joke,0,0,1,0\n',
 '25,Joke,1,0,1,0\n',
 '26,Joke,0,0,1,0\n',
 '27,None,1,0,0,1\n',
 '28,Joke,1,0,1,0\n',
 '29,Joke,1,0,1,0\n',
 '30,None,1,0,0,1\n',
 '31,Joke,0,0,1,0\n',
 '32,None,1,0,0,1\n',
 '33,Joke,1,0,1,0\n',
 '34,Ad,0,1,0,0\n',
 '35,Joke,0,0,1,0\n',
 '36,Ad,1,1,0,0\n',
 '37,Joke,0,0,1,0\n',
 '38,Ad,0,1,0,0\n',
 '39,Joke,0,0,1,0\n',
 '40,Joke,0,0,1,0\n',
 '41,Joke,1,0,1,0\n',
 '42,None,0,0,0,1\n',
 '43,None,0,0,0,1\n',
 '44,Ad,0,1,0,0\n',
 '45,None,0,0,0,1\n',
 '46,None,0,0,0,1\n',
 '47,Ad,0,1,0,0\n',
 '48,Joke,0,0,1,0\n',
 '49,Joke,1,0,1,0\n',
 '50,None,1,0,0,1\n',
 '51,None,0,0,0,1\n',
 '52,Joke,1,0,1,0\n',
 '53,Joke,1,0,1,0\n',
 '54,Joke,0,0,1,0\n',
 '55,None,1,0,0,1\n',
 '56,Ad,0,1,0,0\n',
 '57,Joke,0,0,1,0\n',
 '58,None,0,0,0,1\n',
 '59,Ad,0,1,0,0\n',
 '60,Joke,1,0,1,0\n',
 '61,Ad,0,1,0,0\n',
 '62,None,1,0,0,1\n',
 '63,Joke,0,0,1,0\n',
 '64,Ad,0,1,0,0\n',
 '65,Joke,0,0,1,0\n',
 '66,Ad,0,1,0,0\n',
 '67,Ad,0,1,0,0\n',
 '68,Ad,0,1,0,0\n',
 '69,None,0,0,0,1\n',
 '70,Joke,1,0,1,0\n',
 '71,None,1,0,0,1\n',
 '72,None,0,0,0,1\n',
 '73,None,0,0,0,1\n',
 '74,Joke,0,0,1,0\n',
 '75,Ad,1,1,0,0\n',
 '76,Ad,0,1,0,0\n',
 '77,Ad,1,1,0,0\n',
 '78,Joke,0,0,1,0\n',
 '79,Joke,0,0,1,0\n',
 '80,Ad,1,1,0,0\n',
 '81,Ad,0,1,0,0\n',
 '82,None,0,0,0,1\n',
 '83,Ad,0,1,0,0\n',
 '84,Joke,0,0,1,0\n',
 '85,Joke,0,0,1,0\n',
 '86,Ad,1,1,0,0\n',
 '87,None,1,0,0,1\n',
 '88,Joke,1,0,1,0\n',
 '89,Ad,0,1,0,0\n',
 '90,None,0,0,0,1\n',
 '91,None,0,0,0,1\n',
 '92,Joke,0,0,1,0\n',
 '93,Joke,0,0,1,0\n',
 '94,Ad,0,1,0,0\n',
 '95,Ad,0,1,0,0\n',
 '96,Ad,0,1,0,0\n',
 '97,Joke,1,0,1,0\n',
 '98,None,0,0,0,1\n',
 '99,None,0,0,0,1\n',
 '100,None,1,0,0,1\n',
 '101,Joke,0,0,1,0\n',
 '102,Joke,0,0,1,0\n',
 '103,Ad,1,1,0,0\n',
 '104,Ad,0,1,0,0\n',
 '105,Ad,0,1,0,0\n',
 '106,Ad,1,1,0,0\n',
 '107,Ad,0,1,0,0\n',
 '108,None,0,0,0,1\n',
 '109,Ad,0,1,0,0\n',
 '110,Joke,1,0,1,0\n',
 '111,None,0,0,0,1\n',
 '112,Ad,0,1,0,0\n',
 '113,Ad,0,1,0,0\n',
 '114,None,0,0,0,1\n',
 '115,Ad,0,1,0,0\n',
 '116,None,0,0,0,1\n',
 '117,None,0,0,0,1\n',
 '118,Ad,0,1,0,0\n',
 '119,None,1,0,0,1\n',
 '120,Ad,1,1,0,0\n',
 '121,Ad,0,1,0,0\n',
 '122,Ad,1,1,0,0\n',
 '123,None,0,0,0,1\n',
 '124,None,0,0,0,1\n',
 '125,Joke,1,0,1,0\n',
 '126,Joke,1,0,1,0\n',
 '127,Ad,0,1,0,0\n',
 '128,Joke,0,0,1,0\n',
 '129,Joke,0,0,1,0\n',
 '130,Ad,0,1,0,0\n',
 '131,None,0,0,0,1\n',
 '132,None,0,0,0,1\n',
 '133,None,0,0,0,1\n',
 '134,Joke,1,0,1,0\n',
 '135,Ad,0,1,0,0\n',
 '136,None,0,0,0,1\n',
 '137,Joke,0,0,1,0\n',
 '138,Ad,0,1,0,0\n',
 '139,Ad,0,1,0,0\n',
 '140,None,0,0,0,1\n',
 '141,Joke,0,0,1,0\n',
 '142,None,0,0,0,1\n',
 '143,Ad,0,1,0,0\n',
 '144,None,1,0,0,1\n',
 '145,Joke,0,0,1,0\n',
 '146,Ad,0,1,0,0\n',
 '147,Ad,0,1,0,0\n',
 '148,Ad,0,1,0,0\n',
 '149,Joke,1,0,1,0\n',
 '150,Ad,1,1,0,0\n',
 '151,Joke,1,0,1,0\n',
 '152,None,0,0,0,1\n',
 '153,Ad,0,1,0,0\n',
 '154,None,0,0,0,1\n',
 '155,None,0,0,0,1\n',
 '156,Ad,0,1,0,0\n',
 '157,Ad,0,1,0,0\n',
 '158,Joke,0,0,1,0\n',
 '159,None,0,0,0,1\n',
 '160,Joke,1,0,1,0\n',
 '161,None,1,0,0,1\n',
 '162,Ad,1,1,0,0\n',
 '163,Joke,0,0,1,0\n',
 '164,Joke,0,0,1,0\n',
 '165,Ad,0,1,0,0\n',
 '166,Joke,1,0,1,0\n',
 '167,Joke,1,0,1,0\n',
 '168,Ad,0,1,0,0\n',
 '169,Joke,1,0,1,0\n',
 '170,Joke,0,0,1,0\n',
 '171,Ad,0,1,0,0\n',
 '172,Joke,0,0,1,0\n',
 '173,Joke,0,0,1,0\n',
 '174,Ad,0,1,0,0\n',
 '175,None,0,0,0,1\n',
 '176,Joke,1,0,1,0\n',
 '177,Ad,0,1,0,0\n',
 '178,Joke,0,0,1,0\n',
 '179,Joke,0,0,1,0\n',
 '180,None,0,0,0,1\n',
 '181,None,0,0,0,1\n',
 '182,Ad,0,1,0,0\n',
 '183,None,0,0,0,1\n',
 '184,None,0,0,0,1\n',
 '185,None,0,0,0,1\n',
 '186,None,0,0,0,1\n',
 '187,Ad,0,1,0,0\n',
 '188,None,1,0,0,1\n',
 '189,Ad,0,1,0,0\n',
 '190,Ad,0,1,0,0\n',
 '191,Ad,0,1,0,0\n',
 '192,Joke,1,0,1,0\n',
 '193,Joke,0,0,1,0\n',
 '194,Ad,0,1,0,0\n',
 '195,None,0,0,0,1\n',
 '196,Joke,1,0,1,0\n',
 '197,Joke,0,0,1,0\n',
 '198,Joke,1,0,1,0\n',
 '199,Ad,0,1,0,0\n',
 '200,None,0,0,0,1\n',
 '201,Joke,1,0,1,0\n',
 '202,Joke,0,0,1,0\n',
 '203,Joke,0,0,1,0\n',
 '204,Ad,0,1,0,0\n',
 '205,None,0,0,0,1\n',
 '206,Ad,0,1,0,0\n',
 '207,Ad,0,1,0,0\n',
 '208,Joke,0,0,1,0\n',
 '209,Ad,0,1,0,0\n',
 '210,Joke,0,0,1,0\n',
 '211,None,0,0,0,1\n']

我目前正在尝试查找指定卡片类型的条目总数以及指定卡片类型的提示百分比（精度为小数点后两位）。提示栏是卡类型（无、广告、笑话）后面的0或1。

这有效

from pprint import pprint
from string import punctuation

counts = {"Joke": 0, "Ad": 0, "None": 0}
with open("TipJoke.csv", "r") as f:
    for line in f:
        line_clean = line.replace('"', "").replace("\n", "").split(",")
        try:
            counts[line_clean[1]] += int(line_clean[2])
        except:
            pass


print(counts)

这很有效

from pprint import pprint
from string import punctuation

counts = {"Joke": 0, "Ad": 0, "None": 0}
with open("TipJoke.csv", "r") as f:
    for line in f:
        line_clean = line.replace('"', "").replace("\n", "").split(",")
        try:
            counts[line_clean[1]] += int(line_clean[2])
        except:
            pass


print(counts)

---

如果你被允许进入熊猫图书馆，那么

作为pd进口熊猫

df=pd.read\u csv（“TipJoke.csv”）

df是一个数据帧对象，您可以根据需要在其中执行多个过滤任务

例如，如果要获取笑话的数据，可以按如下方式进行筛选：

print(df[df["Card"] == "Joke"])

---

不过，我只是为您提供方向，而不是问题的全部逻辑。

如果允许您使用熊猫图书馆，那么

作为pd进口熊猫

df=pd.read\u csv（“TipJoke.csv”）

df是一个数据帧对象，您可以根据需要在其中执行多个过滤任务

例如，如果要获取笑话的数据，可以按如下方式进行筛选：

print(df[df["Card"] == "Joke"])

不过，我只是为你提供方向，而不是你问题的全部逻辑