【发布时间】:2018-05-29 22:25:02
【问题描述】:
为什么我会收到 Nan for rolling mean?这是此代码的代码和输出。最初我认为我的数据是错误的,但简单的.mean() 工作正常。
print(df_train.head())
y_hat_avg['mean'] = df_train['pickups'].mean()
print(y_hat_avg.head())
y_hat_avg['moving_avg_forecast'] = df_train['pickups'].rolling(1).mean()
print(y_hat_avg.head())
添加了一些数据: ..................................................... ....................
pickups
date
2014-04-01 00:00:00 12
2014-04-01 01:00:00 5
2014-04-01 02:00:00 2
2014-04-01 03:00:00 4
2014-04-01 04:00:00 3
pickups mean
date
2014-08-01 00:00:00 19 47.25888
2014-08-01 01:00:00 26 47.25888
2014-08-01 02:00:00 9 47.25888
2014-08-01 03:00:00 4 47.25888
2014-08-01 04:00:00 11 47.25888
pickups mean moving_avg_forecast
date
2014-08-01 00:00:00 19 47.25888 NaN
2014-08-01 01:00:00 26 47.25888 NaN
2014-08-01 02:00:00 9 47.25888 NaN
2014-08-01 03:00:00 4 47.25888 NaN
2014-08-01 04:00:00 11 47.25888 NaN
【问题讨论】:
-
检查y_hat_avg index和df_dtrain index的dtypes。
-
谢谢!很遗憾,无法为您的评论点赞。