如何避免对 if 语句进行两次编码
How to avoid coding if statement twice
我主要是自己编程,所以没有人检查我的代码。我觉得我养成了一堆坏习惯。
我在此处粘贴的代码有效,但我想听听其他一些解决方案。
我创建了一个名为 teams_shots
的字典。我遍历 pandas 数据框,其中客队名称和主队名称排成一行。我想跟踪数据框中出现的每个团队的投篮。这就是为什么我检查 home_team_name
或 away_team_name
是否在字典中没有条目,如果是的话我创建一个。
for index,match in df.iterrows():
if match['home_team_name'] not in teams_shots:
#we have to setup an entry in the dictionary
teams_shots[match['home_team_name']]=[]
teams_shots[match['home_team_name']].append(match['home_team_shots'])
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[match['home_team_name']]))
teams_shots[match['home_team_name']].append(match['home_team_shots'])
if match['away_team_name'] not in teams_shots:
teams_shots[match['away_team_name']]=[]
teams_shots[match['away_team_name']].append(match['away_team_shots'])
away_shots_avg.append(None)
else:
away_shots_avg.append(np.mean(teams_shots[match['away_team_name']]))
teams_shots[match['away_team_name']].append(match['away_team_shots'])
如你所见,几乎相同的代码被写了两次,这不是好的编程的标志。我考虑过在 if 语句中使用 or
运算符,但可能已经有一个条目,我会截断它。关于如何更好地编写此代码的任何想法。
在这种情况下,我认为额外的 for
循环应该可以解决问题:
for index,match in df.iterrows():
for name, shots in {'home_team_name':'home_team_shots',
'away_team_name':'away_team_shots'}:
if match[name] not in teams_shots:
#we have to setup an entry in the dictionary
teams_shots[name]=[]
teams_shots[name].append(match[shots])
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[name]))
但可能有一种方法可以以矢量化方式处理此问题。
我会使用 get
作为快速查找。它不会抛出 KeyErrors
并且默认 None
在 truthiness
中充当 False
for index, match in df.iterrows():
home, away, home_shots, away_shots = match['home_team_name'],
match['away_team_name'],
match['home_team_shots'],
match['away_team_shots']
if not teams_shots.get(home):
# No need to separately allocate the array
teams_shots[home] = [home]
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[home_shots]))
if not teams_shots.get(away):
teams_shots[away] = [away]
away_shots_avg.append(None)
else:
away_shots_avg.append(np.mean(teams_shots[away_shots]))
我主要是自己编程,所以没有人检查我的代码。我觉得我养成了一堆坏习惯。
我在此处粘贴的代码有效,但我想听听其他一些解决方案。
我创建了一个名为 teams_shots
的字典。我遍历 pandas 数据框,其中客队名称和主队名称排成一行。我想跟踪数据框中出现的每个团队的投篮。这就是为什么我检查 home_team_name
或 away_team_name
是否在字典中没有条目,如果是的话我创建一个。
for index,match in df.iterrows():
if match['home_team_name'] not in teams_shots:
#we have to setup an entry in the dictionary
teams_shots[match['home_team_name']]=[]
teams_shots[match['home_team_name']].append(match['home_team_shots'])
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[match['home_team_name']]))
teams_shots[match['home_team_name']].append(match['home_team_shots'])
if match['away_team_name'] not in teams_shots:
teams_shots[match['away_team_name']]=[]
teams_shots[match['away_team_name']].append(match['away_team_shots'])
away_shots_avg.append(None)
else:
away_shots_avg.append(np.mean(teams_shots[match['away_team_name']]))
teams_shots[match['away_team_name']].append(match['away_team_shots'])
如你所见,几乎相同的代码被写了两次,这不是好的编程的标志。我考虑过在 if 语句中使用 or
运算符,但可能已经有一个条目,我会截断它。关于如何更好地编写此代码的任何想法。
在这种情况下,我认为额外的 for
循环应该可以解决问题:
for index,match in df.iterrows():
for name, shots in {'home_team_name':'home_team_shots',
'away_team_name':'away_team_shots'}:
if match[name] not in teams_shots:
#we have to setup an entry in the dictionary
teams_shots[name]=[]
teams_shots[name].append(match[shots])
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[name]))
但可能有一种方法可以以矢量化方式处理此问题。
我会使用 get
作为快速查找。它不会抛出 KeyErrors
并且默认 None
在 truthiness
False
for index, match in df.iterrows():
home, away, home_shots, away_shots = match['home_team_name'],
match['away_team_name'],
match['home_team_shots'],
match['away_team_shots']
if not teams_shots.get(home):
# No need to separately allocate the array
teams_shots[home] = [home]
home_shots_avg.append(None)
else:
home_shots_avg.append(np.mean(teams_shots[home_shots]))
if not teams_shots.get(away):
teams_shots[away] = [away]
away_shots_avg.append(None)
else:
away_shots_avg.append(np.mean(teams_shots[away_shots]))