如何根据另一列的日期创建Pandas列？

Question

我的csv有：

Date,Open,High,Low,Close,Adj Close,Volume,dOpen,dHigh,dLow,dClose,dVolume
1/29/93,43.96875,43.96875,43.75,43.9375,26.45393,1003200,0,0,0,0,0
2/1/93,43.96875,44.25,43.96875,44.25,26.642057,480500,0,0.006396588,0.005,0.007112376,0.007111495
2/2/93,44.21875,44.375,44.125,44.34375,26.698507,201300,0.005685856,0.002824859,0.00355366,0.002118644,0.00211883
2/3/93,44.40625,44.84375,44.375,44.8125,26.980742,529400,0.004240283,0.01056338,0.005665722,0.010570825,0.01057119
2/4/93,44.96875,45.09375,44.46875,45,27.093624,531500,0.012667136,0.005574913,0.002112676,0.0041841,0.004183799

我正在做：

    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)

但我犯了个错误

KeyError: ('Date', 'occurred at index Date')

我做错了什么

Answer 1

在使用^{}函数时，还需要指定axis=1，以指示它应该应用于行级别

axis : {0 or ‘index’, 1 or ‘columns’}, default 0

Axis along which the function is applied:

• 0 or ‘index’: apply function to each column.

• 1 or ‘columns’: apply function to each row.

下面应该可以做到这一点：

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)