Filter next two rows

[Julien1]

Hey Guys,

i need help.
I have a dataset with: date, action Day, packet outputs
Now i want to filter: action day = "x" and the following two days (there is no "x")

best regards

[andresrcs]

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[Julien1]

This is my dataset:

Date Action Day Packet Outputs
2015-01-01 x 10000
2015-01-02 - 3000
2015-01-03 - 5000
2015-01-04 - 1000
2015-01-05 - 1000
2015-01-06 x 5000
2015-01-07 - 4000
2015-01-08 - 3000
2015-01-09 - 1500
2015-01-10 - 800
2015-01-11 - 1000
2015-01-12 - 1200

Now my Question:
Packet Output at action day and the following 2 days
Result: 10000+3000+5000+5000+4000+3000 = 30.000
I need a code for this. Take the outputs from the action day (x) (2015-01-01 - 2015-01-03) (2015-01-06 - 2015-01-08) and count the outputs of the next two following days aswell.

[andresrcs]

That is not copy /paste friendly, please read the link I gave you before and reformat your example.

[Julien1]

date	action_day	packet_output
01.01.15	1	10000
02.01.15	0	3000
03.01.15	0	5000
04.01.15	0	1000
05.01.15	0	1000
06.01.15	1	5000
07.01.15	0	4000
08.01.15	0	3000
09.01.15	0	1500
10.01.15	0	800
11.01.15	0	1000
12.01.15	0	1200
13.01.15	0	950
14.01.15	0	700
15.01.15	0	1000
16.01.15	0	900
17.01.15	0	800
18.01.15	0	850
19.01.15	0	1300
20.01.15	0	1100

Filtern2 <- bsp %>%
  filter(action_day == 1)

Filtern2

The missing part are the two following days but i have no idea how I can implement it.

[andresrcs]

Is this what you want to do?

bsp <- data.frame(stringsAsFactors=FALSE,
                  date = c("01.01.15", "02.01.15", "03.01.15", "04.01.15",
                           "05.01.15", "06.01.15", "07.01.15", "08.01.15",
                           "09.01.15", "10.01.15", "11.01.15", "12.01.15", "13.01.15",
                           "14.01.15", "15.01.15", "16.01.15", "17.01.15", "18.01.15",
                           "19.01.15", "20.01.15"),
                  action_day = c(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
                  packet_output = c(10000, 3000, 5000, 1000, 1000, 5000, 4000, 3000, 1500,
                                    800, 1000, 1200, 950, 700, 1000, 900, 800, 850, 1300,
                                    1100)
                  )
library(dplyr)

bsp %>% 
    mutate(action_day = ifelse(action_day == 1 | lag(action_day, 1) == 1 | lag(action_day, 2) == 1,
                               1, 0)) %>%
    filter(action_day == 1) %>% 
    summarise(packet_output = sum(packet_output))
#>   packet_output
#> 1         30000

^{Created on 2019-05-16 by the reprex package (v0.2.1)}

PD: This is the proper way of sharing a reprex