我開始從事一個有趣的項目，以更好地練習我的數據抓取技能，我從 NHL API 抓取數據并嘗試記錄射門和進球的所有位置坐標（此 API 將向您顯示任何 NHL 比賽并具有坐標以及在所述游戲中發生的每個事件的玩家信息）。但是，我在通過數據編制索引時遇到問題，而且我真的不確定如何處理它。下面是我的代碼...import requests as rqimport csvGAME_ID = "2017021121" #Game ID indicates which game I want to look at...first 4 digits is the year, second two the point in season, (01 Pre, 02 Reg, 03 Playoffs, 04 All Star)#URL to access the coordinates of every event in given game...comes in nested dictionary formurl = f"https://statsapi.web.nhl.com/api/v1/game/{GAME_ID}/feed/live"game = rq.get(url)#turn the file into a readable onecontents = game.text#split text into list so we can fool around with itcontents_list = list(csv.reader(contents.splitlines()))def main(): file = open( f'coordinates.{GAME_ID}.txt', 'a')我現在要做的是使用 for 循環遍歷數據集并檢查“事件類型”以及它們是否等于“射門”或“目標”，以及它們是否要添加它們的值x, y 坐標到打印到新文件中的字典。我已經嘗試通過自己建立索引，但我不太擅長數據抓取，所以我沒有走得太遠。作為參考，這里是數據集的樣子（或至少是它的一個片段）。} ], "result" : { "event" : "Penalty", "eventCode" : "COL162", "eventTypeId" : "PENALTY", "description" : "Blake Coleman Tripping against Erik Johnson", "secondaryType" : "Tripping", "penaltySeverity" : "Minor", "penaltyMinutes" : 2 }, "about" : { "eventIdx" : 30, "eventId" : 162, "period" : 1, "periodType" : "REGULAR", "ordinalNum" : "1st", "periodTime" : "04:47", "periodTimeRemaining" : "15:13", "dateTime" : "2019-03-17T19:15:33Z", "goals" : { "away" : 0, "home" : 0 } }, "coordinates" : { "x" : -58.0, "y" : -37.0 },對我來說，它看起來像是一堆嵌套的字典，但我又不太確定。任何幫助將不勝感激??！謝謝你??！
2 回答
慕仙森
TA貢獻1827條經驗 獲得超8個贊
它看起來像一個大列表，包含字典列表。您可以使用for-each-loop.
for entry in list:
然后，您可以單獨查看每個條目并檢查它們是否eventTypeId等于shot或goal：
if entry["result"]["eventTypeId"] == "SHOT":
在這種情況下，您可以像這樣提取 X 和 Y 坐標的值：
x = entry["coordinates"]["x"] y = entry["coordinates"]["y"]
之后，您可以使用這些坐標來做任何您想做的事情。
慕的地8271018
TA貢獻1796條經驗 獲得超4個贊
您可以遍歷列表，通過將所需數據放入字典中以使用 pandas 構建表。
import requests as rq
import pandas as pd
GAME_ID = "2017021121" #Game ID indicates which game I want to look at...first 4 digits is the year, second two the point in season, (01 Pre, 02 Reg, 03 Playoffs, 04 All Star)
#URL to access the coordinates of every event in given game...comes in nested dictionary form
url = f"https://statsapi.web.nhl.com/api/v1/game/{GAME_ID}/feed/live"
game = rq.get(url).json()
game = game['liveData']['plays']['allPlays']
rows = []
for each in game:
if each['result']['event'] in ['Shot','Goal']:
print(each['result']['event'])
row = {
'result':each['result']['event'],
'x':each['coordinates']['x'],
'y':each['coordinates']['y']}
rows.append(row)
df = pd.DataFrame(rows)
輸出：
print(df)
result x y
0 Shot 76.0 -8.0
1 Shot -41.0 -24.0
2 Shot 69.0 -1.0
3 Shot 37.0 30.0
4 Shot -60.0 1.0
5 Goal 43.0 -20.0
6 Shot -85.0 6.0
7 Shot -83.0 11.0
8 Shot -85.0 -5.0
9 Shot 81.0 -1.0
10 Shot -84.0 -7.0
11 Shot -81.0 -3.0
12 Shot -57.0 12.0
13 Shot 74.0 -14.0
14 Goal 64.0 0.0
15 Shot 68.0 2.0
16 Shot 73.0 5.0
17 Shot 63.0 -2.0
18 Shot -26.0 -16.0
19 Shot -84.0 -2.0
20 Shot -74.0 36.0
21 Shot 83.0 6.0
22 Shot -88.0 7.0
23 Shot -39.0 30.0
24 Shot -69.0 -22.0
25 Shot 65.0 32.0
26 Shot 80.0 -3.0
27 Shot -70.0 -6.0
28 Shot -87.0 17.0
29 Shot -29.0 -20.0
.. ... ... ...
47 Shot 81.0 1.0
48 Shot -82.0 0.0
49 Shot 38.0 -28.0
50 Shot 66.0 -9.0
51 Shot 49.0 5.0
52 Shot -48.0 -12.0
53 Shot 39.0 20.0
54 Goal 75.0 -9.0
55 Shot -84.0 -7.0
56 Shot 88.0 -28.0
57 Shot 41.0 -20.0
58 Shot -41.0 12.0
59 Shot 40.0 7.0
60 Shot 72.0 -4.0
61 Goal 86.0 7.0
62 Shot -77.0 -8.0
63 Shot 34.0 -32.0
64 Shot -79.0 -10.0
65 Shot 61.0 6.0
66 Shot -43.0 17.0
67 Shot -41.0 -5.0
68 Shot -35.0 19.0
69 Shot -45.0 -11.0
70 Shot -77.0 -8.0
71 Shot 80.0 -1.0
72 Shot -87.0 7.0
73 Shot 84.0 24.0
74 Shot 76.0 7.0
75 Goal 83.0 -18.0
76 Shot -81.0 -5.0
[77 rows x 3 columns]
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