I have the following table :

The column "Days" shows the number of days since the last time the "Values" sign switched from positive to negative and vice versa.

How can I create the column "Days" using "dplyr mutate" in R ?

Thanks.

CodePudding user response：

If using both dplyr and data.table allowed,

Data

df <- read.table(text = "Date   Values  Days
12/28/2020  0.485002    0
12/29/2020  0.385427    1
12/30/2020  0.323091    2
12/31/2020  0.19967 3
1/4/2021    0.009859    4
1/5/2021    -0.15653    0
1/6/2021    -0.26286    1
1/7/2021    -0.18659    2
1/8/2021    -0.18207    3
1/22/2021   1.077845    0
1/25/2021   1.300135    1
1/26/2021   1.390824    2
1/27/2021   1.256247    3
1/28/2021   1.09526 4", header = T)

Code

library(data.table)
library(dplyr)

df %>%
  select(-Days) %>% # This line may not needed if Days is not at your data at the beginning
  mutate(key = sign(Values) == sign(lag(Values)),
         key = ifelse(!key | is.na(key), 0, 1)) %>%
  data.table() %>%
  .[,Days := cumsum(key), by = rleid(key)] %>%
  select(-key)

          Date    Values days
 1: 12/28/2020  0.485002    0
 2: 12/29/2020  0.385427    1
 3: 12/30/2020  0.323091    2
 4: 12/31/2020  0.199670    3
 5:   1/4/2021  0.009859    4
 6:   1/5/2021 -0.156530    0
 7:   1/6/2021 -0.262860    1
 8:   1/7/2021 -0.186590    2
 9:   1/8/2021 -0.182070    3
10:  1/22/2021  1.077845    0
11:  1/25/2021  1.300135    1
12:  1/26/2021  1.390824    2
13:  1/27/2021  1.256247    3
14:  1/28/2021  1.095260    4

CodePudding user response：

We can use rleid from the data.table package to create a grouping variable, and then create the count of days.

library(dplyr)
library(data.table)

dat2 <- dat %>%
  mutate(G = rleid(Values > 0)) %>%
  group_by(G) %>%
  mutate(Days = 0:(n() - 1)) %>%
  ungroup() %>%
  select(-G)
dat2
# # A tibble: 14 x 3
#    Date         Values  Days
#    <chr>         <dbl> <int>
#  1 12/28/2020  0.485       0
#  2 12/29/2020  0.385       1
#  3 12/30/2020  0.323       2
#  4 12/31/2020  0.200       3
#  5 1/4/2021    0.00986     4
#  6 1/5/2021   -0.157       0
#  7 1/6/2021   -0.263       1
#  8 1/7/2021   -0.187       2
#  9 1/8/2021   -0.182       3
# 10 1/22/2021   1.08        0
# 11 1/25/2021   1.30        1
# 12 1/26/2021   1.39        2
# 13 1/27/2021   1.26        3
# 14 1/28/2021   1.10        4

Data

dat <- read.table(text = "Date  Values
'12/28/2020'    0.485002
'12/29/2020'    0.385427
'12/30/2020'    0.323091
'12/31/2020'    0.19967
'1/4/2021'  0.009859
'1/5/2021'  -0.15653
'1/6/2021'  -0.26286
'1/7/2021'  -0.18659
'1/8/2021'  -0.18207
'1/22/2021' 1.077845
'1/25/2021' 1.300135
'1/26/2021' 1.390824
'1/27/2021' 1.256247
'1/28/2021' 1.09526",
                  header = TRUE)