我的csv有：Date,Open,High,Low,Close,Adj Close,Volume,dOpen,dHigh,dLow,dClose,dVolume1/29/93,43.96875,43.96875,43.75,43.9375,26.45393,1003200,0,0,0,0,02/1/93,43.96875,44.25,43.96875,44.25,26.642057,480500,0,0.006396588,0.005,0.007112376,0.0071114952/2/93,44.21875,44.375,44.125,44.34375,26.698507,201300,0.005685856,0.002824859,0.00355366,0.002118644,0.002118832/3/93,44.40625,44.84375,44.375,44.8125,26.980742,529400,0.004240283,0.01056338,0.005665722,0.010570825,0.010571192/4/93,44.96875,45.09375,44.46875,45,27.093624,531500,0.012667136,0.005574913,0.002112676,0.0041841,0.004183799我在做： spy_data = pd.read_csv('data/SPY_daily.csv') spy_data['day_of_week'] = spy_data.apply( lambda row: datetime.strptime(row['Date'], "%m/%d/%Y")) print(spy_data)但我得到一個錯誤KeyError: ('Date', 'occurred at index Date')我做錯了什么？
3 回答
胡子哥哥
TA貢獻1825條經驗 獲得超6個贊
而不是使用apply它更好地將日期視為適當的日期時間并使用dt方法的功能
例如
spy_data = pd.read_csv(StringIO(your_data),sep=',')
spy_data['Date'] = pd.to_datetime(spy_data['Date'])
day_of_week = spy_data['Date'].dt.strftime("%m/%d/%Y")
print(day_of_week)
0 01/29/1993
1 02/01/1993
2 02/02/1993
3 02/03/1993
4 02/04/1993
Name: Date, dtype: object
如果您的日期設置為您的索引：
spy_data.index.strftime("%m/%d/%Y")
out:
Index(['01/29/1993', '02/01/1993', '02/02/1993', '02/03/1993', '02/04/1993'], dtype='object')
慕運維8079593
TA貢獻1876條經驗 獲得超5個贊
您還需要指定axis=1何時使用apply()函數，以表明它應該應用于行級。
軸：{0 或“索引”，1 或“列”}，默認 0
沿其應用函數的軸：
0 或“索引”：將函數應用于每一列。
1 或“列”：將函數應用于每一行。
以下應該可以解決問題：
spy_data = pd.read_csv('data/SPY_daily.csv')
spy_data['day_of_week'] = spy_data.apply(
lambda row: datetime.strptime(row['Date'], "%m/%d/%Y"), axis=1)
print(spy_data)
回首憶惘然
TA貢獻1847條經驗 獲得超11個贊
問題是pandas.read_csv將第一列作為數據框的索引，因此它不在列中。為了避免這種情況，你應該明確說熊貓不要這樣做：
spy_data = pd.read_csv('data/SPY_daily.csv', index_col=False)添加回答
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