我有3个不同的文件：NewRush4.csv，NewRush5.csv，NewRush6.csv。 我试图从每个赛季（4,5和6）收集一位“历史领袖”。
我想要读取每个文件中的每个玩家的名字，如果它们是重复的，请将它们合并，或者读取第一个文件并将其与其他两个文件进行比较以组合它们。
这是我的python代码。我必须阅读第一个文件。我不知道如何使用DictReader。
#!/usr/bin/python
import csv
file = open("NewRush4.csv", "rb")
for line in csv.DictReader(file, delimiter=","):
name = line["Player"].strip()
yds = line["YDS"].strip()
car = line["CAR"].strip()
td = line["TD"].strip()
fum = line["FUM"].strip()
ypc = line["YPC"].strip()
print "%-20s%10s%10s%10s%10s%10s" % (name, car, yds, td, fum, ypc)
file.close()
输出：
49erswag 3 14.0 0 0 4.7
A Beast Playa 7 23.0 0 0 3.3
A Swanky Guy 2 29 154.0 1 2 5.3
ACIDRUST 1 4.0 0 0 4.0
Aj dahitman 227 1898.0 19 2 8.4
Aldizzl 10 45.0 0 0 4.5
Areis21 13 58.0 0 2 4.5
at43 48 214.0 1 1 4.5
Ayala2012xTCU 57 195.0 0 1 3.4
B O R Nx 25 13 31.0 0 1 2.4
B r e e z yx60 4 13.0 0 0 3.3
Beardown74 116 621.0 6 3 5.4
beatdown54 2010 26 126.0 3 1 4.8
behe SWAG 1 -5.0 0 0 -5.0
Big Murph22 73 480.0 6 2 6.6
BigBlack973 18 57.0 0 1 3.2
BiGDaDDyNaPSacK 184 1181.0 20 4 6.4
Season4文件：
Player,YDS,TD,CAR,FUM,YPC
49erswag, 14.0, 0, 3, 0, 4.7
A Beast Playa, 23.0, 0, 7, 0, 3.3
A Swanky Guy 2, 154.0, 1, 29, 2, 5.3
ACIDRUST, 4.0, 0, 1, 0, 4.0
Aj dahitman, 1898.0, 19, 227, 2, 8.4
Aldizzl, 45.0, 0, 10, 0, 4.5
Areis21, 58.0, 0, 13, 2, 4.5
at43, 214.0, 1, 48, 1, 4.5
Ayala2012xTCU, 195.0, 0, 57, 1, 3.4
B O R Nx 25, 31.0, 0, 13, 1, 2.4
B r e e z yx60, 13.0, 0, 4, 0, 3.3
...
Season5文件：
Player,YDS,TD,CAR,FUM,YPC
a toxic taz, 307.0, 4, 44, 0, 7.0
AbNL Boss, 509.0, 4, 174, 2, 2.9
AFFISHAUL, 190.0, 0, 35, 2, 5.4
AJ DA HITMAN, 1283.0, 19, 228, 6, 5.6
allen5422, 112.0, 2, 18, 0, 6.2
Allxdayxapx, 264.0, 1, 76, 2, 3.5
AlpHaaNike, 51.0, 1, 10, 1, 5.1
Aura Reflexx, 215.0, 1, 40, 0, 5.4
AWAKEN DA BEAST, -5.0, 0, 4, 1, -1.3
AxDub24, -3.0, 0, 2, 1, -1.5
Ayala2012xTCU, 568.0, 4, 173, 1, 3.3
BALLxXHAWKXx, 221.0, 1, 47, 2, 4.7
BANG FIGHTY007, 983.0, 6, 171, 3, 5.7
bang z ro, 29.0, 0, 9, 0, 3.2
BEARDOWN74, 567.0, 6, 104, 2, 5.5
...
所以，如果一名球员在多个赛季中出场，请添加他的统计数据并打印。否则，只需打印。
答案 0 :(得分：0)
你可以试试python pandas，看起来像你需要的工具。对于阅读部分，您可以使用read_csv，然后创建三个DataFrame（或一个，包含所有记录），并进一步操作它们。
例如，对于重复项，您可以尝试duplicated function，例如使用df[ df.duplicated('Player') ]。您还会发现许多descriptive statistics函数，例如您可能需要的max。看看。
为了给你品味（根据原帖中的Season4和Season5数据）：
import pandas as pd
if __name__ == '__main__':
# reading in is very convenient here:
df_4 = pd.read_csv('season4.csv')
df_5 = pd.read_csv('season5.csv')
# combine the two DataFrames into one:
df = pd.concat([df_4, df_5], ignore_index=True)
# see how it looks:
print df.head(50)
Player YDS TD CAR FUM YPC
0 49erswag 14 0 3 0 4.7
1 A Beast Playa 23 0 7 0 3.3
2 A Swanky Guy 2 154 1 29 2 5.3
3 ACIDRUST 4 0 1 0 4.0
4 Aj dahitman 1898 19 227 2 8.4
5 Aldizzl 45 0 10 0 4.5
6 Areis21 58 0 13 2 4.5
7 at43 214 1 48 1 4.5
8 Ayala2012xTCU 195 0 57 1 3.4
9 B O R Nx 25 31 0 13 1 2.4
10 B r e e z yx60 13 0 4 0 3.3
11 a toxic taz 307 4 44 0 7.0
12 AbNL Boss 509 4 174 2 2.9
13 AFFISHAUL 190 0 35 2 5.4
14 AJ DA HITMAN 1283 19 228 6 5.6
15 allen5422 112 2 18 0 6.2
16 Allxdayxapx 264 1 76 2 3.5
17 AlpHaaNike 51 1 10 1 5.1
18 Aura Reflexx 215 1 40 0 5.4
19 AWAKEN DA BEAST -5 0 4 1 -1.3
20 AxDub24 -3 0 2 1 -1.5
21 Ayala2012xTCU 568 4 173 1 3.3
22 BALLxXHAWKXx 221 1 47 2 4.7
23 BANG FIGHTY007 983 6 171 3 5.7
24 bang z ro 29 0 9 0 3.2
25 BEARDOWN74 567 6 104 2 5.5
# see for duplicated entries in the 'Player' column:
print df[ df.duplicated('Player') ]
Player YDS TD CAR FUM YPC
21 Ayala2012xTCU 568 4 173 1 3.3
# see for the maximum value in the 'YDS' column:
print 'Max YDS:', df['YDS'].max()
Max YDS: 1898.0
希望有所帮助。
答案 1 :(得分：0)
我不知道每个字段的含义;我总结每个领域。根据需要进行调整。
from collections import defaultdict
import csv
class PlayerStat(object):
def __init__(self, yds=0, car=0, td=0, fum=0, ypc=0, count=0):
self.yds = float(yds)
self.car = float(car)
self.td = float(td)
self.fum = float(fum)
self.ypc = float(ypc)
self.count = count
def __iadd__(self, other):
self.yds += other.yds
self.car += other.car
self.td += other.td
self.fum += other.fum
self.ypc += other.ypc
self.count += other.count
return self
filenames = 'NewRush4.csv', 'NewRush5.csv', 'NewRush6.csv',
stats = defaultdict(PlayerStat)
for filename in filenames:
with open(filename) as f:
reader = csv.DictReader(f, delimiter=',')
for row in reader:
stat = PlayerStat(row['YDS'], row['CAR'], row['TD'], row['FUM'], row['YPC'], count=1)
stats[row['Player']] += stat
for player in sorted(stats, key=lambda player: stats[player].yds):
stat = stats[player]
if stat.count == 1:
continue
print '{0:<20}{1.car:>10}{1.yds:>10}{1.td:>10}{1.fum:>10}{1.ypc:>10}'.format(player, stat)