Python ZeroDivisionError: division by zero occurs while requesting NHL data and writing it into a CSV
Python ZeroDivisionError: division by zero occurs while requesting NHL data and writing it into a CSV
我 运行 遇到了这个错误：
Traceback (most recent call last):
File "C:\Python36\Projects\NHL\HANDICAP\NHL_Indiv_TEAM.py", line 55, in <module>
item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'],
ZeroDivisionError: division by zero
它会工作到一定程度。我知道我需要将它排除在外才能继续完成整个脚本，但我正在努力思考如何以及在何处写入它。不确定它是 try: 还是 except 行我应该写在那里。任何提示都会有很大帮助，谢谢！
import csv
import requests
import os
import datetime
outfile = open("NHL_Indiv_TEAM.csv","w",newline='')
writer = csv.writer(outfile)
header=[
"TmAbr","Team","Opp","GameLocation","GameId",
"Date","GP","GF","SF","S%","GA","SA","SV%","W","L","OTL",
"SoGW","SoGL","PPopp","PPGF","PPPctg","PK",
"PPGA","PKpctg","TeamPoints","FOW","FOL","FO%","TeamId",
"BS","GiveA's","TakeA's","HitsFor",
"Rest",
"ENgoals","EVgoals","OTgoals","PPgoals","SHgoals",
"shotAA","shotAAhead","shotAttemptsBehind","shotAttemptsClose","shotAttemptsFor","shotAttemptsTied",
"unblockedShotAttempts","unblockedShotAttemptsAgainst","unblockedShotAttemptsAhead","unblockedShotAttemptsBehind",
"unblockedShotAttemptsClose","unblockedShotAttemptsFor","unblockedShotAttemptsTied"]
writer.writerow(header)
req = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamsummary&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data = req.json()['data']
req2 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=realtime&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data2 = req2.json()['data']
req3 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamdaysbetweengames&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data3 = req3.json()['data']
req4 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamgoalsbytype&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data4 = req4.json()['data']
req5 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=shooting&isGame=true&reportName=teamsummaryshooting&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data5 = req5.json()['data']
# Consider this section of the code and how row is obtained
for item, item2, item3, item4, item5 in zip(data, data2, data3, data4, data5):
row = (
item['teamAbbrev'],
item['teamFullName'],
item['opponentTeamAbbrev'],
item['gameLocationCode'],
item['gameId'],
item['gameDate'],
item['gamesPlayed'],
item['goalsFor'],
item['shotsFor'],
item['goalsFor']/item['shotsFor'],
item['goalsAgainst'],
item['shotsAgainst'],
# This line is where the traceback occurred:
item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'],
item['wins'],
item['losses'],
item['otLosses'],
item['shootoutGamesWon'],
item['shootoutGamesLost'],
item['ppOpportunities'],
item['ppGoalsFor'],
item['ppPctg'],
item['shNumTimes'],
item['ppGoalsAgainst'],
item['penaltyKillPctg'],
item['points'],
item['faceoffsWon'],
item['faceoffsLost'],
item['faceoffWinPctg'],
item['teamId'],
item2['blockedShots'],
item2['giveaways'],
item2['takeaways'],
item2['hits'],
item3['daysBtwGamesGroup'],
item4['enGoalsFor'],
item4['evGoalsFor'],
item4['otGoals'],
item4['ppGoalsFor'],
item4['shGoalsFor'],
item5['shotAttempts'],
item5['shotAttemptsAgainst'],
item5['shotAttemptsAhead'],
item5['shotAttemptsBehind'],
item5['shotAttemptsClose'],
item5['shotAttemptsFor'],
item5['shotAttemptsTied'],
item5['unblockedShotAttempts'],
item5['unblockedShotAttemptsAgainst'],
item5['unblockedShotAttemptsAhead'],
item5['unblockedShotAttemptsBehind'],
item5['unblockedShotAttemptsClose'],
item5['unblockedShotAttemptsFor'],
item5['unblockedShotAttemptsTied'],
)
writer.writerow(row)
你最终出现被零除错误的原因是因为在这种情况下，第 55 行中的 item['goalsAgainst']，item['shotsAgainst']/item['goalsAgainst'] 等于零。
你还需要注意row中的item['goalsFor']/item['shotsFor'],。
由于异常发生在分配给 row 的一个巨型表达式中，因此创建一个函数来计算这些比率，并捕获 ZeroDivisionErrors。如果捕获到 ZeroDivisionError，return 标记值 -1。
正在计算 item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst']（导致该错误）
def save_ratio(shotsAgainst, goalsAgainst):
try:
return shotsAgainst/goalsAgainst + shotsAgainst
except ZeroDivisionError:
return -1
...
#replace item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'] with
save_ratio(item['shotsAgainst'], item['goalsAgainst']),
正在计算 item['goalsFor']/item['shotsFor'],:
def for_ratio(goalsFor, shotsFor):
try:
return goalsFor/shotsFor
except ZeroDivisionError:
return -1 # Sentinel value, since goalsFor/shotsFor >= 0 otherwise
...
#replace item['goalsFor']/item['shotsFor'] with
for_ratio(item['goalsFor'],item['shotsFor']),
我 运行 遇到了这个错误：
Traceback (most recent call last):
File "C:\Python36\Projects\NHL\HANDICAP\NHL_Indiv_TEAM.py", line 55, in <module>
item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'],
ZeroDivisionError: division by zero
它会工作到一定程度。我知道我需要将它排除在外才能继续完成整个脚本，但我正在努力思考如何以及在何处写入它。不确定它是 try: 还是 except 行我应该写在那里。任何提示都会有很大帮助，谢谢！
import csv
import requests
import os
import datetime
outfile = open("NHL_Indiv_TEAM.csv","w",newline='')
writer = csv.writer(outfile)
header=[
"TmAbr","Team","Opp","GameLocation","GameId",
"Date","GP","GF","SF","S%","GA","SA","SV%","W","L","OTL",
"SoGW","SoGL","PPopp","PPGF","PPPctg","PK",
"PPGA","PKpctg","TeamPoints","FOW","FOL","FO%","TeamId",
"BS","GiveA's","TakeA's","HitsFor",
"Rest",
"ENgoals","EVgoals","OTgoals","PPgoals","SHgoals",
"shotAA","shotAAhead","shotAttemptsBehind","shotAttemptsClose","shotAttemptsFor","shotAttemptsTied",
"unblockedShotAttempts","unblockedShotAttemptsAgainst","unblockedShotAttemptsAhead","unblockedShotAttemptsBehind",
"unblockedShotAttemptsClose","unblockedShotAttemptsFor","unblockedShotAttemptsTied"]
writer.writerow(header)
req = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamsummary&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data = req.json()['data']
req2 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=realtime&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data2 = req2.json()['data']
req3 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamdaysbetweengames&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data3 = req3.json()['data']
req4 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=basic&isGame=true&reportName=teamgoalsbytype&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data4 = req4.json()['data']
req5 = requests.get('http://www.nhl.com/stats/rest/team?isAggregate=false&reportType=shooting&isGame=true&reportName=teamsummaryshooting&sort=[{%22property%22:%22teamAbbrev%22,%22direction%22:%22ASC%22},{%22property%22:%22gameDate%22,%22direction%22:%22ASC%22}]&cayenneExp=gameDate%3E=%222016-10-12%22%20and%20gameDate%3C=%222017-04-09%22%20and%20gameTypeId=2')
data5 = req5.json()['data']
# Consider this section of the code and how row is obtained
for item, item2, item3, item4, item5 in zip(data, data2, data3, data4, data5):
row = (
item['teamAbbrev'],
item['teamFullName'],
item['opponentTeamAbbrev'],
item['gameLocationCode'],
item['gameId'],
item['gameDate'],
item['gamesPlayed'],
item['goalsFor'],
item['shotsFor'],
item['goalsFor']/item['shotsFor'],
item['goalsAgainst'],
item['shotsAgainst'],
# This line is where the traceback occurred:
item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'],
item['wins'],
item['losses'],
item['otLosses'],
item['shootoutGamesWon'],
item['shootoutGamesLost'],
item['ppOpportunities'],
item['ppGoalsFor'],
item['ppPctg'],
item['shNumTimes'],
item['ppGoalsAgainst'],
item['penaltyKillPctg'],
item['points'],
item['faceoffsWon'],
item['faceoffsLost'],
item['faceoffWinPctg'],
item['teamId'],
item2['blockedShots'],
item2['giveaways'],
item2['takeaways'],
item2['hits'],
item3['daysBtwGamesGroup'],
item4['enGoalsFor'],
item4['evGoalsFor'],
item4['otGoals'],
item4['ppGoalsFor'],
item4['shGoalsFor'],
item5['shotAttempts'],
item5['shotAttemptsAgainst'],
item5['shotAttemptsAhead'],
item5['shotAttemptsBehind'],
item5['shotAttemptsClose'],
item5['shotAttemptsFor'],
item5['shotAttemptsTied'],
item5['unblockedShotAttempts'],
item5['unblockedShotAttemptsAgainst'],
item5['unblockedShotAttemptsAhead'],
item5['unblockedShotAttemptsBehind'],
item5['unblockedShotAttemptsClose'],
item5['unblockedShotAttemptsFor'],
item5['unblockedShotAttemptsTied'],
)
writer.writerow(row)
你最终出现被零除错误的原因是因为在这种情况下，第 55 行中的 item['goalsAgainst']，item['shotsAgainst']/item['goalsAgainst'] 等于零。
你还需要注意row中的item['goalsFor']/item['shotsFor'],。
由于异常发生在分配给 row 的一个巨型表达式中，因此创建一个函数来计算这些比率，并捕获 ZeroDivisionErrors。如果捕获到 ZeroDivisionError，return 标记值 -1。
正在计算 item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst']（导致该错误）
def save_ratio(shotsAgainst, goalsAgainst):
try:
return shotsAgainst/goalsAgainst + shotsAgainst
except ZeroDivisionError:
return -1
...
#replace item['shotsAgainst']/item['goalsAgainst']+item['shotsAgainst'] with
save_ratio(item['shotsAgainst'], item['goalsAgainst']),
正在计算 item['goalsFor']/item['shotsFor'],:
def for_ratio(goalsFor, shotsFor):
try:
return goalsFor/shotsFor
except ZeroDivisionError:
return -1 # Sentinel value, since goalsFor/shotsFor >= 0 otherwise
...
#replace item['goalsFor']/item['shotsFor'] with
for_ratio(item['goalsFor'],item['shotsFor']),