Error in mutate_impl(.data, dots) : Evaluation error: 'from' must be a finite number
I have a large dataset (19945862 obs. of 3 variables) and I am building a time series model for around 50,000 members. Below is the script I am using.
memeberid date amount
165595 17471 2
165596 17471 1.99
165596 17471 1.29
165597 17471 0.88
...... 19945858 obs
library(sweep)
library(tidyquant)
library(forecast)
library(timetk)
yearweek <- function(x) structure(floor(52*x + .00001)/52, class = "yearweek")
reaaranging the data by week
ts$date <- as.numeric(ts$date)
weekly_amt_by_member <- ts %>%
mutate(order.week = as_date(yearweek(date))) %>%
group_by(memberid, order.week) %>%
summarise(total.amt = sum(amount))
bundleing the data on memeberid using nest()
weekly_amt_by_member_nest <- weekly_amt_by_member %>%
group_by(memberid) %>%
nest(.key = "data.tbl")
mutate and map memberid bundles and function to ts class object
weekly_amt_by_member_ts <- weekly_amt_by_member_nest %>%
mutate(data.ts = map(.x = data.tbl ,
.f = tk_ts ,
select = -order.week ,
start = 2017 ,
freq = 52))
modelling ets model
weekly_amt_by_member_fit <- weekly_amt_by_member_ts %>%
mutate(fit.ets = map(data.ts , ets))
forecasting the model
weekly_amt_by_member_fcast <- weekly_amt_by_member_fit %>%
mutate(fcast.ets = map(fit.ets , forecast , h = 52))
All the above parts are running without error except the last part (forecasting the model) which is giving me the following error:
Error in mutate_impl(.data, dots) :
Evaluation error: 'from' must be a finite number.
r time-series mutate unnest
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
add a comment |
I have a large dataset (19945862 obs. of 3 variables) and I am building a time series model for around 50,000 members. Below is the script I am using.
memeberid date amount
165595 17471 2
165596 17471 1.99
165596 17471 1.29
165597 17471 0.88
...... 19945858 obs
library(sweep)
library(tidyquant)
library(forecast)
library(timetk)
yearweek <- function(x) structure(floor(52*x + .00001)/52, class = "yearweek")
reaaranging the data by week
ts$date <- as.numeric(ts$date)
weekly_amt_by_member <- ts %>%
mutate(order.week = as_date(yearweek(date))) %>%
group_by(memberid, order.week) %>%
summarise(total.amt = sum(amount))
bundleing the data on memeberid using nest()
weekly_amt_by_member_nest <- weekly_amt_by_member %>%
group_by(memberid) %>%
nest(.key = "data.tbl")
mutate and map memberid bundles and function to ts class object
weekly_amt_by_member_ts <- weekly_amt_by_member_nest %>%
mutate(data.ts = map(.x = data.tbl ,
.f = tk_ts ,
select = -order.week ,
start = 2017 ,
freq = 52))
modelling ets model
weekly_amt_by_member_fit <- weekly_amt_by_member_ts %>%
mutate(fit.ets = map(data.ts , ets))
forecasting the model
weekly_amt_by_member_fcast <- weekly_amt_by_member_fit %>%
mutate(fcast.ets = map(fit.ets , forecast , h = 52))
All the above parts are running without error except the last part (forecasting the model) which is giving me the following error:
Error in mutate_impl(.data, dots) :
Evaluation error: 'from' must be a finite number.
r time-series mutate unnest
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
add a comment |
I have a large dataset (19945862 obs. of 3 variables) and I am building a time series model for around 50,000 members. Below is the script I am using.
memeberid date amount
165595 17471 2
165596 17471 1.99
165596 17471 1.29
165597 17471 0.88
...... 19945858 obs
library(sweep)
library(tidyquant)
library(forecast)
library(timetk)
yearweek <- function(x) structure(floor(52*x + .00001)/52, class = "yearweek")
reaaranging the data by week
ts$date <- as.numeric(ts$date)
weekly_amt_by_member <- ts %>%
mutate(order.week = as_date(yearweek(date))) %>%
group_by(memberid, order.week) %>%
summarise(total.amt = sum(amount))
bundleing the data on memeberid using nest()
weekly_amt_by_member_nest <- weekly_amt_by_member %>%
group_by(memberid) %>%
nest(.key = "data.tbl")
mutate and map memberid bundles and function to ts class object
weekly_amt_by_member_ts <- weekly_amt_by_member_nest %>%
mutate(data.ts = map(.x = data.tbl ,
.f = tk_ts ,
select = -order.week ,
start = 2017 ,
freq = 52))
modelling ets model
weekly_amt_by_member_fit <- weekly_amt_by_member_ts %>%
mutate(fit.ets = map(data.ts , ets))
forecasting the model
weekly_amt_by_member_fcast <- weekly_amt_by_member_fit %>%
mutate(fcast.ets = map(fit.ets , forecast , h = 52))
All the above parts are running without error except the last part (forecasting the model) which is giving me the following error:
Error in mutate_impl(.data, dots) :
Evaluation error: 'from' must be a finite number.
r time-series mutate unnest
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
I have a large dataset (19945862 obs. of 3 variables) and I am building a time series model for around 50,000 members. Below is the script I am using.
memeberid date amount
165595 17471 2
165596 17471 1.99
165596 17471 1.29
165597 17471 0.88
...... 19945858 obs
library(sweep)
library(tidyquant)
library(forecast)
library(timetk)
yearweek <- function(x) structure(floor(52*x + .00001)/52, class = "yearweek")
reaaranging the data by week
ts$date <- as.numeric(ts$date)
weekly_amt_by_member <- ts %>%
mutate(order.week = as_date(yearweek(date))) %>%
group_by(memberid, order.week) %>%
summarise(total.amt = sum(amount))
bundleing the data on memeberid using nest()
weekly_amt_by_member_nest <- weekly_amt_by_member %>%
group_by(memberid) %>%
nest(.key = "data.tbl")
mutate and map memberid bundles and function to ts class object
weekly_amt_by_member_ts <- weekly_amt_by_member_nest %>%
mutate(data.ts = map(.x = data.tbl ,
.f = tk_ts ,
select = -order.week ,
start = 2017 ,
freq = 52))
modelling ets model
weekly_amt_by_member_fit <- weekly_amt_by_member_ts %>%
mutate(fit.ets = map(data.ts , ets))
forecasting the model
weekly_amt_by_member_fcast <- weekly_amt_by_member_fit %>%
mutate(fcast.ets = map(fit.ets , forecast , h = 52))
All the above parts are running without error except the last part (forecasting the model) which is giving me the following error:
Error in mutate_impl(.data, dots) :
Evaluation error: 'from' must be a finite number.
r time-series mutate unnest
r time-series mutate unnest
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
edited Nov 29 '18 at 18:39
ABHIK ARORA
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
asked Nov 20 '18 at 22:55
ABHIK ARORAABHIK ARORA
63
63
add a comment |
add a comment |
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