我创建了一个Pandas数据框架
错误信息为:
df
:df.head()
Out[1]:
A B DateTime
2010-01-01 50.662365 101.035099 2010-01-01
2010-01-02 47.652424 99.274288 2010-01-02
2010-01-03 51.387459 99.747135 2010-01-03
2010-01-04 52.344788 99.621896 2010-01-04
2010-01-05 47.106364 98.286224 2010-01-05
我可以添加A列的移动平均:
df['A_moving_average'] = df.A.rolling(window=50, axis="rows") \
.apply(lambda x: np.mean(x))
问题: 如何添加列A和B的移动平均值?
这个方法应该是有效的,但是会导致错误:
df['A_B_moving_average'] = df.rolling(window=50, axis="rows") \
.apply(lambda row: (np.mean(row.A) + np.mean(row.B)) / 2)
错误信息为:
NotImplementedError: ops for Rolling for this dtype datetime64[ns] are not implemented
附录A:创建Pandas数据框的代码
以下是我创建测试Pandas数据框 df
的方法:
import numpy.random as rnd
import pandas as pd
import numpy as np
count = 1000
dates = pd.date_range('1/1/2010', periods=count, freq='D')
df = pd.DataFrame(
{
'DateTime': dates,
'A': rnd.normal(50, 2, count), # Mean 50, standard deviation 2
'B': rnd.normal(100, 4, count) # Mean 100, standard deviation 4
}, index=dates
)
'DateTime': dates,
这一行,那么会出现不同的错误:AttributeError: 'numpy.ndarray' object has no attribute 'A'
。 - Contango