如何创建列表列表，然后在列表上执行矢量化功能 [英] How to create a list of list and then perform a vectorised function over it
问题描述
我正在此请求中寻找两个特定的帮助点 1)如何在给定我的数据库(all.df)的情况下创建列表列表 2)如何在此列表清单上向量化功能
I'm looking for two specific help point in this request 1) how to create a list of list given my data base (all.df) below 2) how to vectorise a function over this list of list
我正在尝试使用Prophet库在客户/产品级别生成预测. 我正在努力使操作向量化. 我目前正在运行for循环，我希望避免并加快计算速度.
I'm trying to generate a forecast at a customer / product level using the Prophet library. Im struggling to vectorise the operation. I currently run a for loop, which I want to avoid and speed-up my calculations.
set.seed(1123)
df1 <- data.frame(
Date = seq(dmy("01/01/2017"), by = "day", length.out = 365*2),
Customer = "a",
Product = "xxx",
Revenue = sample(1:100, 365*2, replace=TRUE))
df2 <- data.frame(
Date = seq(dmy("01/01/2017"), by = "day", length.out = 365*2),
Customer = "a",
Product = "yyy",
Revenue = sample(25:200, 365*2, replace=TRUE))
df3 <- data.frame(
Date = seq(dmy("01/01/2017"), by = "day", length.out = 365*2),
Customer = "b",
Product = "xxx",
Revenue = sample(1:100, 365*2, replace=TRUE))
df4 <- data.frame(
Date = seq(dmy("01/01/2017"), by = "day", length.out = 365*2),
Customer = "b",
Product = "yyy",
Revenue = sample(25:200, 365*2, replace=TRUE) )
all.df <- rbind(df1, df2, df3, df4)
这是我的预测功能
daily_forecast <- function(df, forecast.days = 365){
# fit actuals into prophet
m <- prophet(df,
yearly.seasonality = TRUE,
weekly.seasonality = TRUE,
changepoint.prior.scale = 0.55) # default value is 0.05
# create dummy data frame to hold prodictions
future <- make_future_dataframe(m, periods = forecast.days, freq = "day")
# run the prediction
forecast <- predict(m, future)
### Select the date and forecast from the model and then merge with actuals
daily_fcast <- forecast %>% select(ds, yhat) %>% dplyr::rename(Date = ds, fcast.daily = yhat)
actual.to.merge <- df %>% dplyr::rename(Date = ds, Actual.Revenue = y)
daily_fcast <- merge(actual.to.merge, daily_fcast, all = TRUE)
}
当前，我使用for循环一次处理一个客户/产品
x <- df1 %>% select(-c(Customer, Product)) %>%
dplyr::rename(ds = Date, y = Revenue) %>%
daily_forecast()
我想将整个操作矢量化:
I would like to instead, vectorise the whole operation:
1-创建列表列表，即，将all.df拆分为:
1-Create a list of list, i.e. split the all.df by:
a)产品，然后
b)由客户
2-然后在上述1)中创建的列表列表上设置了daily_forecast函数映射
2-Then have the daily_forecast function map over the list of list created in 1) above
我非常想使用purrr之外的功能.
I would very much like to use functions out of purrr.
推荐答案
以下是我如何使用purrr来完成您要问的事情:
Here is how I would do what you're asking with purrr:
library(tidyverse)
library(lubridate)
library(prophet)
res <-
all.df %>%
split(.$Customer) %>%
map(~ split(.x, .x$Product)) %>%
at_depth(2, select, ds = Date, y = Revenue) %>%
at_depth(2, daily_forecast)
str(res)
# List of 2
# $ a:List of 2
# ..$ xxx:'data.frame': 1095 obs. of 3 variables:
# .. ..$ Date : Date[1:1095], format: "2017-01-01" ...
# .. ..$ Actual.Revenue: int [1:1095] 76 87 87 56 83 17 19 72 92 35 ...
# .. ..$ fcast.daily : num [1:1095] 55.9 57.9 51.9 51.9 54 ...
# ..$ yyy:'data.frame': 1095 obs. of 3 variables:
# .. ..$ Date : Date[1:1095], format: "2017-01-01" ...
# .. ..$ Actual.Revenue: int [1:1095] 62 87 175 186 168 190 30 192 119 170 ...
# .. ..$ fcast.daily : num [1:1095] 121 121 119 119 116 ...
# $ b:List of 2
# ..$ xxx:'data.frame': 1095 obs. of 3 variables:
# .. ..$ Date : Date[1:1095], format: "2017-01-01" ...
# .. ..$ Actual.Revenue: int [1:1095] 71 94 81 32 85 59 59 55 50 50 ...
# .. ..$ fcast.daily : num [1:1095] 51.9 54.2 54.5 53.1 51.9 ...
# ..$ yyy:'data.frame': 1095 obs. of 3 variables:
# .. ..$ Date : Date[1:1095], format: "2017-01-01" ...
# .. ..$ Actual.Revenue: int [1:1095] 105 46 153 136 59 59 34 72 70 85 ...
# .. ..$ fcast.daily : num [1:1095] 103.3 103.3 103.1 103.1 91.5 ...
但是对我来说，以下内容更自然(将所有内容保存在一个数据帧中):
But the following would be more natural to me (keeping everything in a dataframe):
res_2 <-
all.df %>%
rename(ds = Date, y = Revenue) %>%
nest(ds, y) %>%
transmute(Customer, Product, res = map(data, daily_forecast)) %>%
unnest()
# # A tibble: 4,380 × 5
# Customer Product Date Actual.Revenue fcast.daily
# <fctr> <fctr> <date> <int> <dbl>
# 1 a xxx 2017-01-01 76 55.93109
# 2 a xxx 2017-01-02 87 57.92577
# 3 a xxx 2017-01-03 87 51.92263
# 4 a xxx 2017-01-04 56 51.86267
# 5 a xxx 2017-01-05 83 54.04588
# 6 a xxx 2017-01-06 17 52.75289
# 7 a xxx 2017-01-07 19 52.35083
# 8 a xxx 2017-01-08 72 53.91887
# 9 a xxx 2017-01-09 92 55.81202
# 10 a xxx 2017-01-10 35 49.78302
# # ... with 4,370 more rows
这篇关于如何创建列表列表，然后在列表上执行矢量化功能的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
