小编foc*_*foc的帖子

我正在研究python中的时间序列.我觉得有用和有前途的图书馆是

• 大熊猫;
• statsmodel(用于ARIMA);
• 大熊猫提供简单的指数平滑.

也用于可视化:matplotlib

有没有人知道指数平滑的库？

我试着在内存中加载一个文件:

import mmap

with open(path+fileinput+'example.txt', 'rb') as f:
       fileinput = mmap.mmap(f.fileno(), 0, prot=mmap.PROT_READ)

当我运行代码时出错:

AttributeError: 'module' object has no attribute 'PROT_READ'

名为d的数据框包含以下数据:

timestamp,value
"2013-06-02 00:00:00",70
"2013-06-02 00:02:00",70
"2013-06-02 00:07:00",60
"2013-06-02 00:15:00",70
"2013-06-02 00:12:00",60
"2013-06-02 00:30:00",70
"2013-06-02 00:45:00",70
"2013-06-02 01:00:00",70

我的代码是:

 d = read.csv(path, header=TRUE, sep=",")
 d2 <- xts(x = d[c("value")], order.by = as.POSIXct(d[, "timestamp"], tz = "GMT", format = "%Y-%m-%d %H:%M:%S"))
ends <- endpoints(d2, on = "minutes", k = 15)
d3   <- period.apply(d2, ends, mean)

之后,我想将xts对象转换为数据帧,我使用这个:

d3$timestamp = rownames(d3)
rownames(d3) = NULL
d3$timestamp = strptime(d3$timestamp, "%Y-%m-%d %H:%M:%S")

但是在最后一步中它会向此输出错误:

Error in NextMethod(.Generic) : 
   number of items to replace is not a multiple …

在这个特定 viridis 选项的条形图中，是否可以设置颜色，即使对于刻度的较暗选项，也可以清晰地显示图表内的数字？

library(ggplot2)
Year      <- c(rep(c("2006-07", "2007-08", "2008-09", "2009-10"), each = 4))
Category  <- c(rep(c("A", "B", "C", "D"), times = 4))
Frequency <- c(168, 259, 226, 340, 216, 431, 319, 368, 423, 645, 234, 685, 166, 467, 274, 251)
Data      <- data.frame(Year, Category, Frequency)
ggplot(Data, aes(x = Year, y = Frequency, fill = Category, label = Frequency)) +
  geom_bar(stat = "identity") +
  geom_text(size = 3, position = position_stack(vjust = 0.5)) +  scale_fill_viridis_d(option  = "magma")

df1 <- data.frame(freetext = c("open until monday night", "one more time to insert your coin"), numid = c(291,312))
df2 <- data.frame(freetext = c("open until night", "one time to insert your be"), aid = c(3,5))

我会使用自由文本列作为选项来合并两个数据框。然而，文本与删除或显示的某些单词并不完全相同。

是否有任何选项可以找到行之间相同单词的最大数量并根据此将它们合并？

这是预期输出的示例

df3 <- data.frame(freetext = c("open until night", "one time to insert your be"), aid = c(3,5), numid = c(291,312))

我发现来自R的预测包是时间序列分析和预测的最佳解决方案.

我想在Python中使用它.我可以使用rpy并在Python中使用预测包吗？

我用这个数据加载一个数据框(命名库存):

day               value
2000-12-01 00:00:00 11.809242 
2000-12-01 06:00:00 10.919792 
2000-12-01 12:00:00 13.265208 
2000-12-01 18:00:00 13.005139 
2000-12-02 00:00:00 10.592222  
2000-12-02 06:00:00 8.873160 
2000-12-02 12:00:00 12.292847 
2000-12-02 18:00:00 12.609722 
2000-12-03 00:00:00 11.378299 
2000-12-03 06:00:00 10.510972  
2000-12-03 12:00:00 8.297222  
2000-12-03 18:00:00 8.110486  
2000-12-04 00:00:00 8.066154

我尝试使用ets()模型实现预测:

library(forecast)
fs <- forecast(stock$value,h=8,model="AAN") 
fs

fs的输出是:

Point Forecast    Lo 80     Hi 80    Lo 95     Hi 95
14       8.778035 6.967009 10.589061 6.008310 11.547761
15       8.536608 6.725582 10.347635 5.766883 11.306334
16       8.295182 6.484155 10.106208 5.525456 11.064907
17       8.053755 6.242728 …

问题的例子

           date          X         Y
 2012-07-05 00:01:19   0.0122     NA
 2012-07-05 03:19:34   0.0121     NA
 2012-07-05 03:19:56   0.0121   0.027
 2012-07-05 03:20:31   0.0121   0.027
 2012-07-05 04:19:56   0.0121   0.028
 2012-07-05 04:20:31   0.0121   0.028
 2012-07-05 04:20:50   0.0121   0.028

我怎样才能填补NA与0.027在Y列？