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tests/testthat/_snaps/long-to-wide-converter.md
In statsExpressions: Tidy Dataframes and Expressions with Statistical Details
long_to_wide_converter works - spread true
Code
purrr::walk(list(df1, df2, df3, df4), dplyr::glimpse)
Output
Rows: 150
Columns: 5
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17~
$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.~
$ Petal.Width <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.~
$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.~
$ Sepal.Width <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.~
Rows: 32
Columns: 3
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, ~
$ `0` <dbl> 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, ~
$ `1` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
Rows: 88
Columns: 5
$ .rowid <int> 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,~
$ HDHF <dbl> 10.0, 10.0, 9.0, 8.5, 3.0, 10.0, 10.0, 10.0, 0.0, 10.0, 8.5, 8.~
$ HDLF <dbl> 9.0, 10.0, 6.0, 5.5, 7.5, 10.0, 9.0, 6.0, 0.0, 8.5, 6.5, 4.0, 6~
$ LDHF <dbl> 6.0, 10.0, 9.0, 6.5, 0.5, 10.0, 10.0, 9.5, 2.5, 7.5, 8.5, 8.0, ~
$ LDLF <dbl> 6.0, 5.0, 6.0, 3.0, 2.0, 10.0, 10.0, 9.5, 0.0, 9.5, 7.0, 3.0, 4~
Rows: 51
Columns: 5
$ .rowid <int> 3, 4, 5, 7, 9, 12, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29,~
$ carni <dbl> 0.0700, 0.0108, 0.0256, 0.3250, 0.0125, 0.1570, 0.0175, 0.0445~
$ herbi <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.42300, 0.09820, 0.11500,~
$ insecti <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
$ omni <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
Code
purrr::map(list(df1, df2, df3, df4), summary)
Output
[[1]]
.rowid Petal.Length Petal.Width Sepal.Length
Min. : 1.00 Min. :1.000 Min. :0.100 Min. :4.300
1st Qu.: 38.25 1st Qu.:1.600 1st Qu.:0.300 1st Qu.:5.100
Median : 75.50 Median :4.350 Median :1.300 Median :5.800
Mean : 75.50 Mean :3.758 Mean :1.199 Mean :5.843
3rd Qu.:112.75 3rd Qu.:5.100 3rd Qu.:1.800 3rd Qu.:6.400
Max. :150.00 Max. :6.900 Max. :2.500 Max. :7.900
Sepal.Width
Min. :2.000
1st Qu.:2.800
Median :3.000
Mean :3.057
3rd Qu.:3.300
Max. :4.400
[[2]]
.rowid 0 1
Min. : 1.00 Min. :2.465 Min. :1.513
1st Qu.: 8.75 1st Qu.:3.438 1st Qu.:1.935
Median :16.50 Median :3.520 Median :2.320
Mean :16.50 Mean :3.769 Mean :2.411
3rd Qu.:24.25 3rd Qu.:3.842 3rd Qu.:2.780
Max. :32.00 Max. :5.424 Max. :3.570
NA's :13 NA's :19
[[3]]
.rowid HDHF HDLF LDHF
Min. : 1.00 Min. : 0.000 Min. : 0.000 Min. : 0.500
1st Qu.:24.75 1st Qu.: 6.000 1st Qu.: 4.375 1st Qu.: 6.000
Median :47.50 Median : 8.500 Median : 7.750 Median : 8.000
Mean :47.57 Mean : 7.824 Mean : 6.676 Mean : 7.352
3rd Qu.:70.25 3rd Qu.:10.000 3rd Qu.: 9.500 3rd Qu.: 9.500
Max. :93.00 Max. :10.000 Max. :10.000 Max. :10.000
LDLF
Min. : 0.000
1st Qu.: 3.500
Median : 6.000
Mean : 5.659
3rd Qu.: 7.500
Max. :10.000
[[4]]
.rowid carni herbi insecti
Min. : 3.00 Min. :0.01080 Min. :0.000400 Min. :0.00025
1st Qu.:25.50 1st Qu.:0.01750 1st Qu.:0.005125 1st Qu.:0.00030
Median :46.00 Median :0.04450 Median :0.012285 Median :0.00120
Mean :42.96 Mean :0.07926 Mean :0.621598 Mean :0.02155
3rd Qu.:61.50 3rd Qu.:0.07000 3rd Qu.:0.236000 3rd Qu.:0.02500
Max. :76.00 Max. :0.32500 Max. :5.712000 Max. :0.08100
NA's :42 NA's :31 NA's :46
omni
Min. :0.00014
1st Qu.:0.00260
Median :0.00660
Mean :0.14573
3rd Qu.:0.17900
Max. :1.32000
NA's :34
long_to_wide_converter works - spread false
Code
purrr::walk(list(df1, df2, df3, df4), dplyr::glimpse)
Output
Rows: 600
Columns: 3
$ .rowid <int> 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, ~
$ condition <fct> Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Petal.~
$ value <dbl> 1.4, 0.2, 5.1, 3.5, 1.4, 0.2, 4.9, 3.0, 1.3, 0.2, 4.7, 3.2, ~
Rows: 32
Columns: 3
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, ~
$ am <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, ~
$ wt <dbl> 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, ~
Rows: 352
Columns: 3
$ .rowid <int> 1, 1, 1, 1, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, ~
$ condition <fct> HDHF, HDLF, LDHF, LDLF, HDHF, HDLF, LDHF, LDLF, HDHF, HDLF, ~
$ desire <dbl> 10.0, 9.0, 6.0, 6.0, 10.0, 10.0, 10.0, 5.0, 9.0, 6.0, 9.0, 6~
Rows: 51
Columns: 3
$ .rowid <int> 3, 4, 5, 7, 9, 12, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29,~
$ vore <fct> carni, carni, carni, carni, carni, carni, carni, carni, carni,~
$ brainwt <dbl> 0.07000, 0.01080, 0.02560, 0.32500, 0.01250, 0.15700, 0.01750,~
Code
purrr::map(list(df1, df2, df3, df4), summary)
Output
[[1]]
.rowid condition value
Min. : 1.0 Petal.Length:150 Min. :0.100
1st Qu.: 38.0 Petal.Width :150 1st Qu.:1.700
Median : 75.5 Sepal.Length:150 Median :3.200
Mean : 75.5 Sepal.Width :150 Mean :3.465
3rd Qu.:113.0 3rd Qu.:5.100
Max. :150.0 Max. :7.900
[[2]]
.rowid am wt
Min. : 1.00 0:19 Min. :1.513
1st Qu.: 8.75 1:13 1st Qu.:2.581
Median :16.50 Median :3.325
Mean :16.50 Mean :3.217
3rd Qu.:24.25 3rd Qu.:3.610
Max. :32.00 Max. :5.424
[[3]]
.rowid condition desire
Min. : 1.00 HDHF:88 Min. : 0.000
1st Qu.:24.75 HDLF:88 1st Qu.: 5.000
Median :47.50 LDHF:88 Median : 7.500
Mean :47.57 LDLF:88 Mean : 6.878
3rd Qu.:70.25 3rd Qu.: 9.500
Max. :93.00 Max. :10.000
[[4]]
.rowid vore brainwt
Min. : 3.00 carni : 9 Min. :0.00014
1st Qu.:25.50 herbi :20 1st Qu.:0.00375
Median :46.00 insecti: 5 Median :0.01550
Mean :42.96 omni :17 Mean :0.30844
3rd Qu.:61.50 3rd Qu.:0.16300
Max. :76.00 Max. :5.71200
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long_to_wide_converter works - spread true
Code
purrr::walk(list(df1, df2, df3, df4), dplyr::glimpse)
Output
Rows: 150
Columns: 5
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17~
$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.~
$ Petal.Width <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.~
$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.~
$ Sepal.Width <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.~
Rows: 32
Columns: 3
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, ~
$ `0` <dbl> 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, ~
$ `1` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
Rows: 88
Columns: 5
$ .rowid <int> 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,~
$ HDHF <dbl> 10.0, 10.0, 9.0, 8.5, 3.0, 10.0, 10.0, 10.0, 0.0, 10.0, 8.5, 8.~
$ HDLF <dbl> 9.0, 10.0, 6.0, 5.5, 7.5, 10.0, 9.0, 6.0, 0.0, 8.5, 6.5, 4.0, 6~
$ LDHF <dbl> 6.0, 10.0, 9.0, 6.5, 0.5, 10.0, 10.0, 9.5, 2.5, 7.5, 8.5, 8.0, ~
$ LDLF <dbl> 6.0, 5.0, 6.0, 3.0, 2.0, 10.0, 10.0, 9.5, 0.0, 9.5, 7.0, 3.0, 4~
Rows: 51
Columns: 5
$ .rowid <int> 3, 4, 5, 7, 9, 12, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29,~
$ carni <dbl> 0.0700, 0.0108, 0.0256, 0.3250, 0.0125, 0.1570, 0.0175, 0.0445~
$ herbi <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.42300, 0.09820, 0.11500,~
$ insecti <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
$ omni <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
Code
purrr::map(list(df1, df2, df3, df4), summary)
Output
[[1]]
.rowid Petal.Length Petal.Width Sepal.Length
Min. : 1.00 Min. :1.000 Min. :0.100 Min. :4.300
1st Qu.: 38.25 1st Qu.:1.600 1st Qu.:0.300 1st Qu.:5.100
Median : 75.50 Median :4.350 Median :1.300 Median :5.800
Mean : 75.50 Mean :3.758 Mean :1.199 Mean :5.843
3rd Qu.:112.75 3rd Qu.:5.100 3rd Qu.:1.800 3rd Qu.:6.400
Max. :150.00 Max. :6.900 Max. :2.500 Max. :7.900
Sepal.Width
Min. :2.000
1st Qu.:2.800
Median :3.000
Mean :3.057
3rd Qu.:3.300
Max. :4.400
[[2]]
.rowid 0 1
Min. : 1.00 Min. :2.465 Min. :1.513
1st Qu.: 8.75 1st Qu.:3.438 1st Qu.:1.935
Median :16.50 Median :3.520 Median :2.320
Mean :16.50 Mean :3.769 Mean :2.411
3rd Qu.:24.25 3rd Qu.:3.842 3rd Qu.:2.780
Max. :32.00 Max. :5.424 Max. :3.570
NA's :13 NA's :19
[[3]]
.rowid HDHF HDLF LDHF
Min. : 1.00 Min. : 0.000 Min. : 0.000 Min. : 0.500
1st Qu.:24.75 1st Qu.: 6.000 1st Qu.: 4.375 1st Qu.: 6.000
Median :47.50 Median : 8.500 Median : 7.750 Median : 8.000
Mean :47.57 Mean : 7.824 Mean : 6.676 Mean : 7.352
3rd Qu.:70.25 3rd Qu.:10.000 3rd Qu.: 9.500 3rd Qu.: 9.500
Max. :93.00 Max. :10.000 Max. :10.000 Max. :10.000
LDLF
Min. : 0.000
1st Qu.: 3.500
Median : 6.000
Mean : 5.659
3rd Qu.: 7.500
Max. :10.000
[[4]]
.rowid carni herbi insecti
Min. : 3.00 Min. :0.01080 Min. :0.000400 Min. :0.00025
1st Qu.:25.50 1st Qu.:0.01750 1st Qu.:0.005125 1st Qu.:0.00030
Median :46.00 Median :0.04450 Median :0.012285 Median :0.00120
Mean :42.96 Mean :0.07926 Mean :0.621598 Mean :0.02155
3rd Qu.:61.50 3rd Qu.:0.07000 3rd Qu.:0.236000 3rd Qu.:0.02500
Max. :76.00 Max. :0.32500 Max. :5.712000 Max. :0.08100
NA's :42 NA's :31 NA's :46
omni
Min. :0.00014
1st Qu.:0.00260
Median :0.00660
Mean :0.14573
3rd Qu.:0.17900
Max. :1.32000
NA's :34
long_to_wide_converter works - spread false
Code
purrr::walk(list(df1, df2, df3, df4), dplyr::glimpse)
Output
Rows: 600
Columns: 3
$ .rowid <int> 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, ~
$ condition <fct> Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Petal.~
$ value <dbl> 1.4, 0.2, 5.1, 3.5, 1.4, 0.2, 4.9, 3.0, 1.3, 0.2, 4.7, 3.2, ~
Rows: 32
Columns: 3
$ .rowid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, ~
$ am <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, ~
$ wt <dbl> 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, ~
Rows: 352
Columns: 3
$ .rowid <int> 1, 1, 1, 1, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, ~
$ condition <fct> HDHF, HDLF, LDHF, LDLF, HDHF, HDLF, LDHF, LDLF, HDHF, HDLF, ~
$ desire <dbl> 10.0, 9.0, 6.0, 6.0, 10.0, 10.0, 10.0, 5.0, 9.0, 6.0, 9.0, 6~
Rows: 51
Columns: 3
$ .rowid <int> 3, 4, 5, 7, 9, 12, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29,~
$ vore <fct> carni, carni, carni, carni, carni, carni, carni, carni, carni,~
$ brainwt <dbl> 0.07000, 0.01080, 0.02560, 0.32500, 0.01250, 0.15700, 0.01750,~
Code
purrr::map(list(df1, df2, df3, df4), summary)
Output
[[1]]
.rowid condition value
Min. : 1.0 Petal.Length:150 Min. :0.100
1st Qu.: 38.0 Petal.Width :150 1st Qu.:1.700
Median : 75.5 Sepal.Length:150 Median :3.200
Mean : 75.5 Sepal.Width :150 Mean :3.465
3rd Qu.:113.0 3rd Qu.:5.100
Max. :150.0 Max. :7.900
[[2]]
.rowid am wt
Min. : 1.00 0:19 Min. :1.513
1st Qu.: 8.75 1:13 1st Qu.:2.581
Median :16.50 Median :3.325
Mean :16.50 Mean :3.217
3rd Qu.:24.25 3rd Qu.:3.610
Max. :32.00 Max. :5.424
[[3]]
.rowid condition desire
Min. : 1.00 HDHF:88 Min. : 0.000
1st Qu.:24.75 HDLF:88 1st Qu.: 5.000
Median :47.50 LDHF:88 Median : 7.500
Mean :47.57 LDLF:88 Mean : 6.878
3rd Qu.:70.25 3rd Qu.: 9.500
Max. :93.00 Max. :10.000
[[4]]
.rowid vore brainwt
Min. : 3.00 carni : 9 Min. :0.00014
1st Qu.:25.50 herbi :20 1st Qu.:0.00375
Median :46.00 insecti: 5 Median :0.01550
Mean :42.96 omni :17 Mean :0.30844
3rd Qu.:61.50 3rd Qu.:0.16300
Max. :76.00 Max. :5.71200
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