Periodic Patterns Identification

General
1

I want to identify temporal patterns in a time series.

structure(list(ID = c("a", "b", "c", "d", "e", "f", "g", "h",
"i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u",
"v", "w", "x"), 2016/01 = c(1, NA, NA, 1, NA, NA, 1, NA, NA,
1, NA, 1, 1, 1, NA, 1, NA, NA, 1, NA, NA, 1, NA, NA), 2016/02 = c(NA,
1, NA, NA, 1, NA, NA, 1, NA, NA, 1, 1, 1, NA, 1, NA, 1, NA, NA,
1, NA, NA, 1, NA), 2016/03 = c(NA, NA, 1, NA, NA, 1, NA, NA,
1, 1, NA, 1, 1, 1, NA, NA, NA, 1, NA, NA, 1, NA, NA, 1), 2016/04 = c(NA,
NA, NA, 1, NA, NA, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA,
1, NA, NA, NA, NA, NA), 2016/05 = c(NA, NA, NA, NA, 1, NA,
NA, NA, NA, 1, NA, 1, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA,
NA), 2016/06 = c(NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, 1,
1, 1, NA, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA), 2016/07 = c(NA,
NA, NA, 1, NA, NA, 1, NA, NA, 1, NA, 1, 1, 1, NA, 1, NA, NA,
1, NA, NA, NA, NA, NA), 2016/08 = c(NA, NA, NA, NA, 1, NA,
NA, 1, NA, NA, 1, 1, 1, NA, 1, NA, 1, NA, NA, 1, NA, NA, NA,
NA), 2016/09 = c(NA, NA, NA, NA, NA, 1, NA, NA, 1, 1, NA, 1,
1, 1, NA, NA, NA, 1, NA, NA, 1, NA, NA, NA), 2016/10 = c(NA,
NA, NA, 1, NA, NA, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA,
1, NA, NA, NA, NA, NA), 2016/11 = c(NA, NA, NA, NA, 1, NA,
NA, NA, NA, 1, NA, 1, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA,
NA), 2016/12 = c(NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, 1,
1, 1, NA, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA), 2017/01 = c(1,
NA, NA, 1, NA, NA, 1, NA, NA, 1, NA, 1, 1, 1, NA, 1, NA, NA,
1, NA, NA, 1, NA, NA), 2017/02 = c(NA, 1, NA, NA, 1, NA, NA,
1, NA, NA, 1, 1, 1, NA, 1, NA, 1, NA, NA, 1, NA, NA, 1, NA),
2017/03 = c(NA, NA, 1, NA, NA, 1, NA, NA, 1, 1, NA, 1,
1, 1, NA, NA, NA, 1, NA, NA, 1, NA, NA, 1), 2017/04 = c(NA,
NA, NA, 1, NA, NA, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA,
NA, 1, NA, NA, NA, NA, NA), 2017/05 = c(NA, NA, NA, NA,
1, NA, NA, NA, NA, 1, NA, 1, 1, 1, NA, NA, NA, NA, NA, 1,
NA, NA, NA, NA), 2017/06 = c(NA, NA, NA, NA, NA, 1, NA,
NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA, NA, NA, 1, NA, NA,
NA), 2017/07 = c(NA, NA, NA, 1, NA, NA, 1, NA, NA, 1, NA,
1, 1, 1, NA, 1, NA, NA, 1, NA, NA, NA, NA, NA), 2017/08 = c(NA,
NA, NA, NA, 1, NA, NA, 1, NA, NA, 1, 1, 1, NA, 1, NA, 1,
NA, NA, 1, NA, NA, NA, NA), 2017/09 = c(NA, NA, NA, NA,
NA, 1, NA, NA, NA, 1, NA, 1, 1, 1, NA, NA, NA, NA, NA, NA,
1, NA, NA, NA), 2017/10 = c(NA, NA, NA, 1, NA, NA, NA,
NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA, 1, NA, NA, NA, NA,
NA), 2017/11 = c(NA, NA, NA, NA, 1, NA, NA, NA, NA, 1,
NA, 1, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA), 2017/12 = c(1,
NA, NA, NA, NA, 1, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA,
NA, NA, NA, 1, 1, NA, NA), 2018/01 = c(NA, 1, NA, 1, NA,
NA, 1, NA, NA, 1, NA, 1, 1, 1, NA, 1, NA, NA, 1, NA, NA,
NA, 1, NA), 2018/02 = c(NA, NA, 1, NA, 1, NA, NA, 1, NA,
NA, 1, 1, 1, NA, 1, NA, 1, NA, NA, 1, NA, NA, NA, 1), 2018/03 = c(NA,
NA, NA, NA, NA, 1, NA, NA, 1, 1, NA, 1, 1, 1, NA, NA, NA,
1, NA, NA, 1, NA, NA, NA), 2018/04 = c(NA, NA, NA, 1, NA,
NA, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA, 1, NA, NA,
NA, NA, NA), 2018/05 = c(NA, NA, NA, NA, 1, NA, NA, NA,
NA, 1, NA, 1, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA
), 2018/06 = c(NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, 1,
1, 1, NA, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA), 2018/07 = c(NA,
NA, NA, 1, NA, NA, 1, NA, NA, 1, NA, 1, 1, 1, NA, 1, NA,
NA, 1, NA, NA, NA, NA, NA), 2018/08 = c(NA, NA, NA, NA,
1, NA, NA, 1, NA, NA, 1, 1, 1, NA, 1, NA, 1, NA, NA, 1, NA,
NA, NA, NA), 2018/09 = c(NA, NA, NA, NA, NA, 1, NA, NA,
1, 1, NA, 1, 1, 1, NA, NA, NA, 1, NA, NA, 1, NA, NA, NA),
2018/10 = c(NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, 1, 1,
1, NA, 1, NA, NA, NA, 1, NA, NA, NA, NA, NA), 2018/11 = c(NA,
NA, NA, NA, 1, NA, NA, NA, NA, 1, NA, 1, 1, 1, NA, NA, NA,
NA, NA, 1, NA, NA, NA, NA), 2018/12 = c(NA, NA, NA, NA,
NA, 1, NA, NA, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA, NA, NA,
1, NA, NA, NA)), row.names = c(NA, -24L), class = c("tbl_df",
"tbl", "data.frame"))

In the upper dataframe indivuidual:

  • List item

a has the same pattern as v
b has the same pattern as w
c has the same pattern as x

In the upper dataframe indivuiduals a, b, c, v, w and x have the same frequency - yearly.

The are some other cases as bimensal, quartlerly and semestral.

My objetive is to identify all this cases and classify all individuals with a time pattern.

I suppose that the package arulesSequences can be useful.

Can you help me please?

2

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