我想遍歷我的資料并使用“事件”值及其相應的“xCordAdjusted”和“yCordAdjusted”填充我的字典
資料框：
season period teamCode event goal xCord xCordAdjusted yCord yCordAdjusted shotType playerPositionThatDidEvent playerNumThatDidEvent shooterPlayerId shooterName shooterLeftRight
2014 1 MTL MISS 0 61 61 29 29 WRIST C 51 8471976.0 David Desharnais L
2014 1 TOR SHOT 0 -54 54 29 -29 BACK C 42 8475098.0 Tyler Bozak R
2014 1 TOR SHOT 0 -40 40 32 -32 WRIST D 46 8471392.0 Roman Polak R
我的作業：
league_data = {};
league_data['SHOT'] = {};
league_data['SHOT']['x'] = [];
league_data['SHOT']['y'] = [];
league_data['GOAL'] = {};
league_data['GOAL']['x'] = [];
league_data['GOAL']['y'] = [];
league_data['MISS'] = {};
league_data['MISS']['x'] = [];
league_data['MISS']['y'] = [];
event_types = ['SHOT','GOAL','MISS']
for data in season_df:
for event in event_types:
if data in event_types:
if 'x' in range(0,100):
league_data[event]['x'].append(['xCordAdjusted'])
league_data[event]['y'].append(['yCordAdjusted'])
league_data
輸出：
{'SHOT': {'x': [], 'y': []},
'GOAL': {'x': [], 'y': []},
'MISS': {'x': [], 'y': []}}
uj5u.com熱心網友回復：
您可以以矢量化的方式直接從 DataFrame 中提取所需的資訊，而不是重復回圈：
league_data = {
'SHOT': {},
'GOAL': {},
'MISS': {},
}
for event in event_types:
mask = (season_df['event'] == event) & season_df['xCord'].between(0, 100)
x_adjusted = season_df.loc[mask, 'xCordAdjusted'].tolist()
y_adjusted = season_df.loc[mask, 'yCordAdjusted'].tolist()
league_data[event]['x'] = x_adjusted
league_data[event]['y'] = y_adjusted
給
{'GOAL': {'x': [], 'y': []},
'MISS': {'x': [61], 'y': [-29]},
'SHOT': {'x': [], 'y': []}
}
請注意，我調整了范圍條件，因為您的原始代碼if 'x' in range(0,100)沒有按照您的意圖執行，因為它根本沒有參考您的 DataFrame。
uj5u.com熱心網友回復：
for data in season_df:迭代列，而不是行。
相反，使用for index, row in season_df.iterrows()
但是，行上的迭代很慢，所以如果你的資料很大，你可以利用矢量化。
此外，您的代碼看起來不像您預期??的那樣作業......就像if 'x' in range(0, 100)。我根據我的假設重新編碼，試試這個。
for event in event_types:
matched_df = season_df[season_df['event'] == event]
x_matched_list = matched_df[(0 <= matched_df['xCordAdjusted']) & (matched_df['xCordAdjusted'] <= 100)]['xCordAdjusted'].tolist()
league_data[event]['x'] = x_matched_list # or extend
y_matched_list = matched_df[(0 <= matched_df['yCordAdjusted']) & (matched_df['yCordAdjusted'] <= 100)]['yCordAdjusted'].tolist()
league_data[event]['y'] = y_matched_list # or extend
但要注意長度 'xCordAdjusted' 與 'yCordAdjusted' 不匹配的可能性
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