tests/testthat/_snaps/xnew-data.md
In poissonconsulting/newdata: Generate New Data Frames for Prediction
simple dataset
Code
data
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a TRUE 2023-09-27
2 2.5 4 b FALSE 2023-09-28
3 3.5 5 c FALSE 2023-09-29
4 4.5 6 d TRUE 2023-09-30
5 5.5 7 e FALSE 2023-10-01
Code
xnew_data(data)
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, a)
Output
# A tibble: 30 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.64 5 a FALSE 2023-09-29
3 1.78 5 a FALSE 2023-09-29
4 1.91 5 a FALSE 2023-09-29
5 2.05 5 a FALSE 2023-09-29
6 2.19 5 a FALSE 2023-09-29
7 2.33 5 a FALSE 2023-09-29
8 2.47 5 a FALSE 2023-09-29
9 2.60 5 a FALSE 2023-09-29
10 2.74 5 a FALSE 2023-09-29
# i 20 more rows
Code
xnew_data(data, a = new_value(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_value(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, a = dplyr::last(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, b)
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 3 a FALSE 2023-09-29
2 3.5 4 a FALSE 2023-09-29
3 3.5 5 a FALSE 2023-09-29
4 3.5 6 a FALSE 2023-09-29
5 3.5 7 a FALSE 2023-09-29
Code
xnew_data(data, c)
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d FALSE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(c))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d FALSE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a))
Output
# A tibble: 30 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.64 5 a FALSE 2023-09-29
3 1.78 5 a FALSE 2023-09-29
4 1.91 5 a FALSE 2023-09-29
5 2.05 5 a FALSE 2023-09-29
6 2.19 5 a FALSE 2023-09-29
7 2.33 5 a FALSE 2023-09-29
8 2.47 5 a FALSE 2023-09-29
9 2.60 5 a FALSE 2023-09-29
10 2.74 5 a FALSE 2023-09-29
# i 20 more rows
Code
xnew_data(data, xnew_seq(a, length_out = 12))
Output
# A tibble: 12 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.86 5 a FALSE 2023-09-29
3 2.23 5 a FALSE 2023-09-29
4 2.59 5 a FALSE 2023-09-29
5 2.95 5 a FALSE 2023-09-29
6 3.32 5 a FALSE 2023-09-29
7 3.68 5 a FALSE 2023-09-29
8 4.05 5 a FALSE 2023-09-29
9 4.41 5 a FALSE 2023-09-29
10 4.77 5 a FALSE 2023-09-29
11 5.14 5 a FALSE 2023-09-29
12 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a, length_out = 12, obs_only = TRUE))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 2.5 5 a FALSE 2023-09-29
3 3.5 5 a FALSE 2023-09-29
4 4.5 5 a FALSE 2023-09-29
5 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a, length_out = 12), b)
Output
# A tibble: 60 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a FALSE 2023-09-29
2 1.5 4 a FALSE 2023-09-29
3 1.5 5 a FALSE 2023-09-29
4 1.5 6 a FALSE 2023-09-29
5 1.5 7 a FALSE 2023-09-29
6 1.86 3 a FALSE 2023-09-29
7 1.86 4 a FALSE 2023-09-29
8 1.86 5 a FALSE 2023-09-29
9 1.86 6 a FALSE 2023-09-29
10 1.86 7 a FALSE 2023-09-29
# i 50 more rows
Code
xnew_data(data, b, xnew_seq(a, length_out = 12))
Output
# A tibble: 60 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a FALSE 2023-09-29
2 1.86 3 a FALSE 2023-09-29
3 2.23 3 a FALSE 2023-09-29
4 2.59 3 a FALSE 2023-09-29
5 2.95 3 a FALSE 2023-09-29
6 3.32 3 a FALSE 2023-09-29
7 3.68 3 a FALSE 2023-09-29
8 4.05 3 a FALSE 2023-09-29
9 4.41 3 a FALSE 2023-09-29
10 4.77 3 a FALSE 2023-09-29
# i 50 more rows
Code
xnew_data(data, tidyr::nesting(c, d))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a TRUE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d TRUE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, b = 8:10, z = "zed", tidyr::nesting(c, d))
Output
# A tibble: 15 x 6
a b c d e z
<dbl> <int> <fct> <lgl> <date> <chr>
1 3.5 8 a TRUE 2023-09-29 zed
2 3.5 8 b FALSE 2023-09-29 zed
3 3.5 8 c FALSE 2023-09-29 zed
4 3.5 8 d TRUE 2023-09-29 zed
5 3.5 8 e FALSE 2023-09-29 zed
6 3.5 9 a TRUE 2023-09-29 zed
7 3.5 9 b FALSE 2023-09-29 zed
8 3.5 9 c FALSE 2023-09-29 zed
9 3.5 9 d TRUE 2023-09-29 zed
10 3.5 9 e FALSE 2023-09-29 zed
11 3.5 10 a TRUE 2023-09-29 zed
12 3.5 10 b FALSE 2023-09-29 zed
13 3.5 10 c FALSE 2023-09-29 zed
14 3.5 10 d TRUE 2023-09-29 zed
15 3.5 10 e FALSE 2023-09-29 zed
factors
Code
data
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2001 2001
2 before 2002 2002 2002
3 before 2003 2003 2003
4 before 2004 2004 2004
5 before 2005 2005 2005
6 after 2006 2006 2006
7 after 2007 2007 2007
8 after 2008 2008 2008
9 after 2009 2009 2009
10 after 2010 2010 2010
Code
xnew_data(data)
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2000 2005
Code
xnew_data(data, xnew_value(annual))
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2000 2005
Code
xnew_data(data, xnew_value(annual, obs_only = TRUE))
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2001 2005
Code
xnew_data(data, tidyr::nesting(period, year))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
Code
xnew_data(data, tidyr::nesting(period, year, annual))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2001 2005
2 before 2002 2002 2005
3 before 2003 2003 2005
4 before 2004 2004 2005
5 before 2005 2005 2005
6 after 2006 2006 2005
7 after 2007 2007 2005
8 after 2008 2008 2005
9 after 2009 2009 2005
10 after 2010 2010 2005
Code
xnew_data(data, tidyr::nesting(period, year, xnew_value(annual)))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
Code
xnew_data(data, tidyr::nesting(period, year), xnew_value(annual))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
xnew_data called twice works
Code
data
Output
# A tibble: 3 x 3
a b d
<int> <dbl> <chr>
1 1 4 a
2 3 4.5 b
3 4 6 c
Code
xnew_data(xnew_data(data, a))
Output
# A tibble: 1 x 3
a b d
<int> <dbl> <chr>
1 2 4.83 a
Code
xnew_data(xnew_data(data, a, b = new_value(b), xnew_value(d)))
Output
# A tibble: 1 x 3
a b d
<int> <dbl> <chr>
1 2 4.83 a
poissonconsulting/newdata documentation built on Jan. 18, 2024, 1:30 a.m.
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simple dataset
Code
data
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a TRUE 2023-09-27
2 2.5 4 b FALSE 2023-09-28
3 3.5 5 c FALSE 2023-09-29
4 4.5 6 d TRUE 2023-09-30
5 5.5 7 e FALSE 2023-10-01
Code
xnew_data(data)
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, a)
Output
# A tibble: 30 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.64 5 a FALSE 2023-09-29
3 1.78 5 a FALSE 2023-09-29
4 1.91 5 a FALSE 2023-09-29
5 2.05 5 a FALSE 2023-09-29
6 2.19 5 a FALSE 2023-09-29
7 2.33 5 a FALSE 2023-09-29
8 2.47 5 a FALSE 2023-09-29
9 2.60 5 a FALSE 2023-09-29
10 2.74 5 a FALSE 2023-09-29
# i 20 more rows
Code
xnew_data(data, a = new_value(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_value(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
Code
xnew_data(data, a = dplyr::last(a))
Output
# A tibble: 1 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, b)
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 3 a FALSE 2023-09-29
2 3.5 4 a FALSE 2023-09-29
3 3.5 5 a FALSE 2023-09-29
4 3.5 6 a FALSE 2023-09-29
5 3.5 7 a FALSE 2023-09-29
Code
xnew_data(data, c)
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d FALSE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(c))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a FALSE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d FALSE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a))
Output
# A tibble: 30 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.64 5 a FALSE 2023-09-29
3 1.78 5 a FALSE 2023-09-29
4 1.91 5 a FALSE 2023-09-29
5 2.05 5 a FALSE 2023-09-29
6 2.19 5 a FALSE 2023-09-29
7 2.33 5 a FALSE 2023-09-29
8 2.47 5 a FALSE 2023-09-29
9 2.60 5 a FALSE 2023-09-29
10 2.74 5 a FALSE 2023-09-29
# i 20 more rows
Code
xnew_data(data, xnew_seq(a, length_out = 12))
Output
# A tibble: 12 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 1.86 5 a FALSE 2023-09-29
3 2.23 5 a FALSE 2023-09-29
4 2.59 5 a FALSE 2023-09-29
5 2.95 5 a FALSE 2023-09-29
6 3.32 5 a FALSE 2023-09-29
7 3.68 5 a FALSE 2023-09-29
8 4.05 5 a FALSE 2023-09-29
9 4.41 5 a FALSE 2023-09-29
10 4.77 5 a FALSE 2023-09-29
11 5.14 5 a FALSE 2023-09-29
12 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a, length_out = 12, obs_only = TRUE))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 5 a FALSE 2023-09-29
2 2.5 5 a FALSE 2023-09-29
3 3.5 5 a FALSE 2023-09-29
4 4.5 5 a FALSE 2023-09-29
5 5.5 5 a FALSE 2023-09-29
Code
xnew_data(data, xnew_seq(a, length_out = 12), b)
Output
# A tibble: 60 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a FALSE 2023-09-29
2 1.5 4 a FALSE 2023-09-29
3 1.5 5 a FALSE 2023-09-29
4 1.5 6 a FALSE 2023-09-29
5 1.5 7 a FALSE 2023-09-29
6 1.86 3 a FALSE 2023-09-29
7 1.86 4 a FALSE 2023-09-29
8 1.86 5 a FALSE 2023-09-29
9 1.86 6 a FALSE 2023-09-29
10 1.86 7 a FALSE 2023-09-29
# i 50 more rows
Code
xnew_data(data, b, xnew_seq(a, length_out = 12))
Output
# A tibble: 60 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 1.5 3 a FALSE 2023-09-29
2 1.86 3 a FALSE 2023-09-29
3 2.23 3 a FALSE 2023-09-29
4 2.59 3 a FALSE 2023-09-29
5 2.95 3 a FALSE 2023-09-29
6 3.32 3 a FALSE 2023-09-29
7 3.68 3 a FALSE 2023-09-29
8 4.05 3 a FALSE 2023-09-29
9 4.41 3 a FALSE 2023-09-29
10 4.77 3 a FALSE 2023-09-29
# i 50 more rows
Code
xnew_data(data, tidyr::nesting(c, d))
Output
# A tibble: 5 x 5
a b c d e
<dbl> <int> <fct> <lgl> <date>
1 3.5 5 a TRUE 2023-09-29
2 3.5 5 b FALSE 2023-09-29
3 3.5 5 c FALSE 2023-09-29
4 3.5 5 d TRUE 2023-09-29
5 3.5 5 e FALSE 2023-09-29
Code
xnew_data(data, b = 8:10, z = "zed", tidyr::nesting(c, d))
Output
# A tibble: 15 x 6
a b c d e z
<dbl> <int> <fct> <lgl> <date> <chr>
1 3.5 8 a TRUE 2023-09-29 zed
2 3.5 8 b FALSE 2023-09-29 zed
3 3.5 8 c FALSE 2023-09-29 zed
4 3.5 8 d TRUE 2023-09-29 zed
5 3.5 8 e FALSE 2023-09-29 zed
6 3.5 9 a TRUE 2023-09-29 zed
7 3.5 9 b FALSE 2023-09-29 zed
8 3.5 9 c FALSE 2023-09-29 zed
9 3.5 9 d TRUE 2023-09-29 zed
10 3.5 9 e FALSE 2023-09-29 zed
11 3.5 10 a TRUE 2023-09-29 zed
12 3.5 10 b FALSE 2023-09-29 zed
13 3.5 10 c FALSE 2023-09-29 zed
14 3.5 10 d TRUE 2023-09-29 zed
15 3.5 10 e FALSE 2023-09-29 zed
factors
Code
data
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2001 2001
2 before 2002 2002 2002
3 before 2003 2003 2003
4 before 2004 2004 2004
5 before 2005 2005 2005
6 after 2006 2006 2006
7 after 2007 2007 2007
8 after 2008 2008 2008
9 after 2009 2009 2009
10 after 2010 2010 2010
Code
xnew_data(data)
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2000 2005
Code
xnew_data(data, xnew_value(annual))
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2000 2005
Code
xnew_data(data, xnew_value(annual, obs_only = TRUE))
Output
# A tibble: 1 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2005 2001 2005
Code
xnew_data(data, tidyr::nesting(period, year))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
Code
xnew_data(data, tidyr::nesting(period, year, annual))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2001 2005
2 before 2002 2002 2005
3 before 2003 2003 2005
4 before 2004 2004 2005
5 before 2005 2005 2005
6 after 2006 2006 2005
7 after 2007 2007 2005
8 after 2008 2008 2005
9 after 2009 2009 2005
10 after 2010 2010 2005
Code
xnew_data(data, tidyr::nesting(period, year, xnew_value(annual)))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
Code
xnew_data(data, tidyr::nesting(period, year), xnew_value(annual))
Output
# A tibble: 10 x 4
period year annual ordered
<fct> <int> <fct> <ord>
1 before 2001 2000 2005
2 before 2002 2000 2005
3 before 2003 2000 2005
4 before 2004 2000 2005
5 before 2005 2000 2005
6 after 2006 2000 2005
7 after 2007 2000 2005
8 after 2008 2000 2005
9 after 2009 2000 2005
10 after 2010 2000 2005
xnew_data called twice works
Code
data
Output
# A tibble: 3 x 3
a b d
<int> <dbl> <chr>
1 1 4 a
2 3 4.5 b
3 4 6 c
Code
xnew_data(xnew_data(data, a))
Output
# A tibble: 1 x 3
a b d
<int> <dbl> <chr>
1 2 4.83 a
Code
xnew_data(xnew_data(data, a, b = new_value(b), xnew_value(d)))
Output
# A tibble: 1 x 3
a b d
<int> <dbl> <chr>
1 2 4.83 a
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