Unstable group_by behaviour

Hello! Thanks for the great package for reporting everything! I have faced a minor issue recently and hope that this summary will help to fix it.

group_by() summary statistics fails with simple penguins data

To Reproduce:

library(palmerpenguins)
library(tidyverse)
library(report)     

palmerpenguins::penguins %>% 
  select(species, body_mass_g, ends_with("_mm")) %>% 
  drop_na() %>% 
  group_by(species) %>%
  report()

results into:

The same happens with:

Expected behavior as in the examples:

iris %>%
    dplyr::group_by(Species) %>%
    report_table()

interestingly, similar calls are working with report_sample and report_text

palmerpenguins::penguins %>% 
  select(species, body_mass_g, ends_with("_mm")) %>% 
  drop_na() %>% 
  group_by(species) %>%
  report_sample()

palmerpenguins::penguins %>% 
  select(species, body_mass_g, ends_with("_mm")) %>% 
  drop_na() %>% 
  group_by(species) %>%
  report_text()

Specifications

Package	Version
dplyr	1.0.5
forcats	0.5.1
ggplot2	3.3.3
palmerpenguins	0.1.0
purrr	0.3.4
R	4.0.5
readr	1.4.0
report	0.3.0
stringr	1.4.0
tibble	3.1.0
tidyr	1.1.3
tidyverse	1.3.1

Just for the record, grouped data frame do not yet work for report_sample(), the syntax would be:

palmerpenguins::penguins %>% 
  select(species, body_mass_g, ends_with("_mm")) %>% 
  drop_na() %>% 
  report_sample(group_by = "species")

@DominiqueMakowski I committed a hotfix, which should fix the bug, however, the issue is a bit more complicated.

At some point, report() calls report_table.numeric(), which removes either the column n_missing or percentage_missing:

https://github.com/easystats/report/blob/4ce4f01bd8bc0d4b6429087a7681a93460a0b20f/R/report.numeric.R#L119-L134

missing_percentage is determined here:

https://github.com/easystats/report/blob/4ce4f01bd8bc0d4b6429087a7681a93460a0b20f/R/report.numeric.R#L69

That function, in turn, checks the length of a vector or data frame, and if > 100, returns TRUE:

https://github.com/easystats/report/blob/fe09f4dcfc1e8c35aa79d32432990a057c5d8280/R/report.data.frame.R#L520-L537

Not sure why this is done? In the above example, the different species have different length, so for one group, column n_Missing only is removed, for the other percentage_Missing only is removed, although both have no missings. This results in different column names, and thus, rbind() fails:

https://github.com/easystats/report/blob/4ce4f01bd8bc0d4b6429087a7681a93460a0b20f/R/report.data.frame.R#L362-L368

I just don't know why you define missing_percentage this way?

weird lemme take a look

Okay so the n >= 100 was a pure heuristic decision for the default, in which it will display the n for small-ish numbers, but the percentage for bigger dataframes (if n > 100), but indeed it should be checked accrosss the whole, ungrouped dataframe, and not on the subgroups 😓

do you have in mind a smarter way of dealing with that? Essentially currently report.data.frame has levels_percentage = "auto" and missing_percentage = "auto", and the auto rule was to put TRUE for bigger numbers and FALSE for smaller numbers

It doens't fiail if missing_percentage is specified. Maybe we should set it to just TRUE / FALSE by default and remove the "auto"? Though in principle it was nice because it's true that for smaller numbers ('til 100) it's easier to represent with numbers, but for more than that we switch to percentage which brings it back to a 0-100 scale in a way

library(palmerpenguins)
library(tidyverse)
#> Warning: package 'tibble' was built under R version 4.0.5
library(report)     

palmerpenguins::penguins %>% 
  select(species, body_mass_g, ends_with("_mm")) %>% 
  drop_na() %>% 
  group_by(species) %>%
  report(missing_percentage = FALSE)
#> The data contains 342 observations, grouped by species, of the following 5 variables:
#> 
#> - Adelie (n = 151):
#>   - body_mass_g: n = 151, Mean = 3700.66, SD = 458.57, Median = 3700.00, MAD = 444.78, range: [2850, 4775], Skewness = 0.29, Kurtosis = -0.57, 0 missing
#>   - bill_length_mm: n = 151, Mean = 38.79, SD = 2.66, Median = 38.80, MAD = 2.97, range: [32.10, 46], Skewness = 0.16, Kurtosis = -0.16, 0 missing
#>   - bill_depth_mm: n = 151, Mean = 18.35, SD = 1.22, Median = 18.40, MAD = 1.19, range: [15.50, 21.50], Skewness = 0.32, Kurtosis = -0.06, 0 missing
#>   - flipper_length_mm: n = 151, Mean = 189.95, SD = 6.54, Median = 190.00, MAD = 7.41, range: [172, 210], Skewness = 0.09, Kurtosis = 0.33, 0 missing
#> 
#> - Chinstrap (n = 68):
#>   - body_mass_g: n = 68, Mean = 3733.09, SD = 384.34, Median = 3700.00, MAD = 370.65, range: [2700, 4800], Skewness = 0.25, Kurtosis = 0.59, 0 missing
#>   - bill_length_mm: n = 68, Mean = 48.83, SD = 3.34, Median = 49.55, MAD = 3.63, range: [40.90, 58], Skewness = -0.09, Kurtosis = 0.04, 0 missing
#>   - bill_depth_mm: n = 68, Mean = 18.42, SD = 1.14, Median = 18.45, MAD = 1.41, range: [16.40, 20.80], Skewness = 6.88e-03, Kurtosis = -0.87, 0 missing
#>   - flipper_length_mm: n = 68, Mean = 195.82, SD = 7.13, Median = 196.00, MAD = 7.41, range: [178, 212], Skewness = -9.47e-03, Kurtosis = 0.05, 0 missing
#> 
#> - Gentoo (n = 123):
#>   - body_mass_g: n = 123, Mean = 5076.02, SD = 504.12, Median = 5000.00, MAD = 555.98, range: [3950, 6300], Skewness = 0.07, Kurtosis = -0.72, 0 missing
#>   - bill_length_mm: n = 123, Mean = 47.50, SD = 3.08, Median = 47.30, MAD = 3.11, range: [40.90, 59.60], Skewness = 0.65, Kurtosis = 1.30, 0 missing
#>   - bill_depth_mm: n = 123, Mean = 14.98, SD = 0.98, Median = 15.00, MAD = 1.19, range: [13.10, 17.30], Skewness = 0.32, Kurtosis = -0.58, 0 missing
#>   - flipper_length_mm: n = 123, Mean = 217.19, SD = 6.48, Median = 216.00, MAD = 5.93, range: [203, 231], Skewness = 0.39, Kurtosis = -0.58, 0 missing

^{Created on 2021-04-23 by the reprex package (v1.0.0)}

Somehow, one group is omitted with report_table after the hot fix 4ce4f01...

library(tidyverse)
library(report)
palmerpenguins::penguins %>%
  select(species, body_mass_g, ends_with("_mm")) %>%
  group_by(species) %>%
  report_table()
#> Group     |          Variable | n_Obs |    Mean |     SD |  Median |    MAD |     Min |     Max |  Skewness | Kurtosis | percentage_Missing | n_Missing
#> -------------------------------------------------------------------------------------------------------------------------------------------------------
#> Chinstrap |       body_mass_g |    68 | 3733.09 | 384.34 | 3700.00 | 370.65 | 2700.00 | 4800.00 |      0.25 |     0.59 |                    |         0
#> Chinstrap |    bill_length_mm |    68 |   48.83 |   3.34 |   49.55 |   3.63 |   40.90 |   58.00 |     -0.09 |     0.04 |                    |         0
#> Chinstrap |     bill_depth_mm |    68 |   18.42 |   1.14 |   18.45 |   1.41 |   16.40 |   20.80 |  6.88e-03 |    -0.87 |                    |         0
#> Chinstrap | flipper_length_mm |    68 |  195.82 |   7.13 |  196.00 |   7.41 |  178.00 |  212.00 | -9.47e-03 |     0.05 |                    |         0
#> Gentoo    |       body_mass_g |   124 | 5076.02 | 504.12 |         | 555.98 | 3950.00 | 6300.00 |      0.07 |    -0.72 |               0.81 |          
#> Gentoo    |    bill_length_mm |   124 |   47.50 |   3.08 |         |   3.11 |   40.90 |   59.60 |      0.65 |     1.30 |               0.81 |          
#> Gentoo    |     bill_depth_mm |   124 |   14.98 |   0.98 |         |   1.19 |   13.10 |   17.30 |      0.32 |    -0.58 |               0.81 |          
#> Gentoo    | flipper_length_mm |   124 |  217.19 |   6.48 |         |   5.93 |  203.00 |  231.00 |      0.39 |    -0.58 |               0.81 |

palmerpenguins::penguins %>%
  select(species, body_mass_g, ends_with("_mm")) %>%
  group_by(species) %>%
  report_table(missing_percentage = FALSE)
#> Group     |          Variable | n_Obs |    Mean |     SD |  Median |    MAD |     Min |     Max |  Skewness | Kurtosis | n_Missing
#> ----------------------------------------------------------------------------------------------------------------------------------
#> Chinstrap |       body_mass_g |    68 | 3733.09 | 384.34 | 3700.00 | 370.65 | 2700.00 | 4800.00 |      0.25 |     0.59 |         0
#> Chinstrap |    bill_length_mm |    68 |   48.83 |   3.34 |   49.55 |   3.63 |   40.90 |   58.00 |     -0.09 |     0.04 |         0
#> Chinstrap |     bill_depth_mm |    68 |   18.42 |   1.14 |   18.45 |   1.41 |   16.40 |   20.80 |  6.88e-03 |    -0.87 |         0
#> Chinstrap | flipper_length_mm |    68 |  195.82 |   7.13 |  196.00 |   7.41 |  178.00 |  212.00 | -9.47e-03 |     0.05 |         0
#> Gentoo    |       body_mass_g |   124 | 5076.02 | 504.12 |         | 555.98 | 3950.00 | 6300.00 |      0.07 |    -0.72 |         1
#> Gentoo    |    bill_length_mm |   124 |   47.50 |   3.08 |         |   3.11 |   40.90 |   59.60 |      0.65 |     1.30 |         1
#> Gentoo    |     bill_depth_mm |   124 |   14.98 |   0.98 |         |   1.19 |   13.10 |   17.30 |      0.32 |    -0.58 |         1
#> Gentoo    | flipper_length_mm |   124 |  217.19 |   6.48 |         |   5.93 |  203.00 |  231.00 |      0.39 |    -0.58 |         1

^{Created on 2021-04-23 by the reprex package (v2.0.0)}

Somehow, one group is omitted with report_table

Hi - I'm running into this issue as well, maybe duplicated in #246 ?

System: Analyses were conducted using the R Statistical language (version 4.1.2; R Core Team, 2021) on Pop!_OS 22.04 LTS

Packages:

effectsize (version 0.8.3; Ben-Shachar MS et al., 2020)
fmtr (version 1.5.9; Bosak D, 2022)
common (version 1.0.5; Bosak D, Simmons A, 2022)
officedown (version 0.3.0; Gohel D, Ross N, 2023)
flextable (version 0.8.6; Gohel D, Skintzos P, 2023)
ggpubr (version 0.6.0; Kassambara A, 2023)
batman (version 0.1.0; Keyes O et al., 2015)
parameters (version 0.20.2; Lüdecke D et al., 2020)
performance (version 0.10.2; Lüdecke D et al., 2021)
easystats (version 0.6.0; Lüdecke D et al., 2022)
see (version 0.7.4; Lüdecke D et al., 2021)
insight (version 0.19.0; Lüdecke D et al., 2019)
bayestestR (version 0.13.0; Makowski D et al., 2019)
modelbased (version 0.8.6; Makowski D et al., 2020)
correlation (version 0.8.3; Makowski D et al., 2020)
report (version 0.5.6; Makowski D et al., 2023)
datawizard (version 0.6.5; Patil I et al., 2022)
R (version 4.1.2; R Core Team, 2021)
ggplot2 (version 3.4.1; Wickham H, 2016)
readxl (version 1.4.1; Wickham H, Bryan J, 2022)
dplyr (version 1.1.0; Wickham H et al., 2023)
tidyr (version 1.3.0; Wickham H et al., 2023)
kableExtra (version 1.3.4; Zhu H, 2021)

When I add print(table) inside the for loop of report_table.grouped_df of report.data.frame line 390 and provide iris %>% group_by(Species)

I get:

[1] Variable  Mean      SD        Min       Max       n_Missing Group    
<0 rows> (or 0-length row.names)
      Variable  Mean        SD Min Max n_Missing      Group
1 Sepal.Length 5.936 0.5161711 4.9 7.0         0 versicolor
2  Sepal.Width 2.770 0.3137983 2.0 3.4         0 versicolor
3 Petal.Length 4.260 0.4699110 3.0 5.1         0 versicolor
4  Petal.Width 1.326 0.1977527 1.0 1.8         0 versicolor
      Variable  Mean        SD Min Max n_Missing      Group
1 Sepal.Length 5.936 0.5161711 4.9 7.0         0 versicolor
2  Sepal.Width 2.770 0.3137983 2.0 3.4         0 versicolor
3 Petal.Length 4.260 0.4699110 3.0 5.1         0 versicolor
4  Petal.Width 1.326 0.1977527 1.0 1.8         0 versicolor
5 Sepal.Length 6.588 0.6358796 4.9 7.9         0  virginica
6  Sepal.Width 2.974 0.3224966 2.2 3.8         0  virginica
7 Petal.Length 5.552 0.5518947 4.5 6.9         0  virginica
8  Petal.Width 2.026 0.2746501 1.4 2.5         0  virginica

Showing a zero-length table on the first iteration, and loosing that group from the output

Group      |     Variable | n_Obs | Mean |   SD | Median |  MAD |  Min |  Max | Skewness | Kurtosis | n_Missing
---------------------------------------------------------------------------------------------------------------
versicolor | Sepal.Length |    50 | 5.94 | 0.52 |   5.90 | 0.52 | 4.90 | 7.00 |     0.11 |    -0.53 |         0
versicolor |  Sepal.Width |    50 | 2.77 | 0.31 |   2.80 | 0.30 | 2.00 | 3.40 |    -0.36 |    -0.37 |         0
versicolor | Petal.Length |    50 | 4.26 | 0.47 |   4.35 | 0.52 | 3.00 | 5.10 |    -0.61 |     0.05 |         0
versicolor |  Petal.Width |    50 | 1.33 | 0.20 |   1.30 | 0.22 | 1.00 | 1.80 |    -0.03 |    -0.41 |         0
virginica  | Sepal.Length |    50 | 6.59 | 0.64 |   6.50 | 0.59 | 4.90 | 7.90 |     0.12 |     0.03 |         0
virginica  |  Sepal.Width |    50 | 2.97 | 0.32 |   3.00 | 0.30 | 2.20 | 3.80 |     0.37 |     0.71 |         0
virginica  | Petal.Length |    50 | 5.55 | 0.55 |   5.55 | 0.67 | 4.50 | 6.90 |     0.55 |    -0.15 |         0
virginica  |  Petal.Width |    50 | 2.03 | 0.27 |   2.00 | 0.30 | 1.40 | 2.50 |    -0.13 |    -0.60 |         0

If I instead run print(current_table), I find three tables as expected

Variable     | Mean |   SD |  Min |  Max | n_Missing |  Group
-------------------------------------------------------------
Sepal.Length | 5.01 | 0.35 | 4.30 | 5.80 |         0 | setosa
Sepal.Width  | 3.43 | 0.38 | 2.30 | 4.40 |         0 | setosa
Petal.Length | 1.46 | 0.17 | 1.00 | 1.90 |         0 | setosa
Petal.Width  | 0.25 | 0.11 | 0.10 | 0.60 |         0 | setosa
Variable     | Mean |   SD |  Min |  Max | n_Missing |      Group
-----------------------------------------------------------------
Sepal.Length | 5.94 | 0.52 | 4.90 | 7.00 |         0 | versicolor
Sepal.Width  | 2.77 | 0.31 | 2.00 | 3.40 |         0 | versicolor
Petal.Length | 4.26 | 0.47 | 3.00 | 5.10 |         0 | versicolor
Petal.Width  | 1.33 | 0.20 | 1.00 | 1.80 |         0 | versicolor
Variable     | Mean |   SD |  Min |  Max | n_Missing |     Group
----------------------------------------------------------------
Sepal.Length | 6.59 | 0.64 | 4.90 | 7.90 |         0 | virginica
Sepal.Width  | 2.97 | 0.32 | 2.20 | 3.80 |         0 | virginica
Petal.Length | 5.55 | 0.55 | 4.50 | 6.90 |         0 | virginica
Petal.Width  | 2.03 | 0.27 | 1.40 | 2.50 |         0 | virginica

but of course, the same output.

Similar problem for table_full

 [1] Variable  n_Obs     Mean      SD        Median    MAD       Min       Max       Skewness  Kurtosis 
[11] n_Missing Group    
<0 rows> (or 0-length row.names)
      Variable n_Obs  Mean        SD Median     MAD Min Max   Skewness   Kurtosis n_Missing      Group
1 Sepal.Length    50 5.936 0.5161711   5.90 0.51891 4.9 7.0  0.1053776 -0.5330095         0 versicolor
2  Sepal.Width    50 2.770 0.3137983   2.80 0.29652 2.0 3.4 -0.3628448 -0.3662374         0 versicolor
3 Petal.Length    50 4.260 0.4699110   4.35 0.51891 3.0 5.1 -0.6065077  0.0479033         0 versicolor
4  Petal.Width    50 1.326 0.1977527   1.30 0.22239 1.0 1.8 -0.0311796 -0.4100592         0 versicolor
      Variable n_Obs  Mean        SD Median     MAD Min Max   Skewness    Kurtosis n_Missing      Group
1 Sepal.Length    50 5.936 0.5161711   5.90 0.51891 4.9 7.0  0.1053776 -0.53300954         0 versicolor
2  Sepal.Width    50 2.770 0.3137983   2.80 0.29652 2.0 3.4 -0.3628448 -0.36623736         0 versicolor
3 Petal.Length    50 4.260 0.4699110   4.35 0.51891 3.0 5.1 -0.6065077  0.04790330         0 versicolor
4  Petal.Width    50 1.326 0.1977527   1.30 0.22239 1.0 1.8 -0.0311796 -0.41005924         0 versicolor
5 Sepal.Length    50 6.588 0.6358796   6.50 0.59304 4.9 7.9  0.1180151  0.03290442         0  virginica
6  Sepal.Width    50 2.974 0.3224966   3.00 0.29652 2.2 3.8  0.3659491  0.70607051         0  virginica
7 Petal.Length    50 5.552 0.5518947   5.55 0.66717 4.5 6.9  0.5494446 -0.15377856         0  virginica
8  Petal.Width    50 2.026 0.2746501   2.00 0.29652 1.4 2.5 -0.1294769 -0.60226448         0  virginica
>

Two very crude modifications get the expected result. I'm not sure if there is a better way to handle merge in this case.

I wonder if merge does not include new rows but adopts new columns when a non-empty data frame merges with an empty data frame?

    if(!length(table_full) == 0){
      table_full <- merge(table_full, current_table_full, all = TRUE, sort = FALSE)
    }else{
      table_full <- current_table_full
    }

    if(!length(table) == 0){
      table <- merge(table, current_table, all = TRUE, sort = FALSE)
    }else{
      table <- current_table
    }

Produces table_full:

 Variable     | n_Obs | Mean |   SD | Median |  MAD |  Min |  Max | Skewness | Kurtosis | n_Missing |  Group
-----------------------------------------------------------------------------------------------------------
Sepal.Length |    50 | 5.01 | 0.35 |   5.00 | 0.30 | 4.30 | 5.80 |     0.12 |    -0.25 |         0 | setosa
Sepal.Width  |    50 | 3.43 | 0.38 |   3.40 | 0.37 | 2.30 | 4.40 |     0.04 |     0.95 |         0 | setosa
Petal.Length |    50 | 1.46 | 0.17 |   1.50 | 0.15 | 1.00 | 1.90 |     0.11 |     1.02 |         0 | setosa
Petal.Width  |    50 | 0.25 | 0.11 |   0.20 | 0.00 | 0.10 | 0.60 |     1.25 |     1.72 |         0 | setosa
      Variable n_Obs  Mean        SD Median     MAD Min Max    Skewness   Kurtosis n_Missing      Group
1 Sepal.Length    50 5.006 0.3524897   5.00 0.29652 4.3 5.8  0.12008699 -0.2526888         0     setosa
2  Sepal.Width    50 3.428 0.3790644   3.40 0.37065 2.3 4.4  0.04116652  0.9547033         0     setosa
3 Petal.Length    50 1.462 0.1736640   1.50 0.14826 1.0 1.9  0.10639390  1.0215761         0     setosa
4  Petal.Width    50 0.246 0.1053856   0.20 0.00000 0.1 0.6  1.25386137  1.7191302         0     setosa
5 Sepal.Length    50 5.936 0.5161711   5.90 0.51891 4.9 7.0  0.10537762 -0.5330095         0 versicolor
6  Sepal.Width    50 2.770 0.3137983   2.80 0.29652 2.0 3.4 -0.36284484 -0.3662374         0 versicolor
7 Petal.Length    50 4.260 0.4699110   4.35 0.51891 3.0 5.1 -0.60650769  0.0479033         0 versicolor
8  Petal.Width    50 1.326 0.1977527   1.30 0.22239 1.0 1.8 -0.03117960 -0.4100592         0 versicolor
       Variable n_Obs  Mean        SD Median     MAD Min Max    Skewness    Kurtosis n_Missing      Group
1  Sepal.Length    50 5.006 0.3524897   5.00 0.29652 4.3 5.8  0.12008699 -0.25268880         0     setosa
2   Sepal.Width    50 3.428 0.3790644   3.40 0.37065 2.3 4.4  0.04116652  0.95470326         0     setosa
3  Petal.Length    50 1.462 0.1736640   1.50 0.14826 1.0 1.9  0.10639390  1.02157611         0     setosa
4   Petal.Width    50 0.246 0.1053856   0.20 0.00000 0.1 0.6  1.25386137  1.71913025         0     setosa
5  Sepal.Length    50 5.936 0.5161711   5.90 0.51891 4.9 7.0  0.10537762 -0.53300954         0 versicolor
6   Sepal.Width    50 2.770 0.3137983   2.80 0.29652 2.0 3.4 -0.36284484 -0.36623736         0 versicolor
7  Petal.Length    50 4.260 0.4699110   4.35 0.51891 3.0 5.1 -0.60650769  0.04790330         0 versicolor
8   Petal.Width    50 1.326 0.1977527   1.30 0.22239 1.0 1.8 -0.03117960 -0.41005924         0 versicolor
9  Sepal.Length    50 6.588 0.6358796   6.50 0.59304 4.9 7.9  0.11801512  0.03290442         0  virginica
10  Sepal.Width    50 2.974 0.3224966   3.00 0.29652 2.2 3.8  0.36594907  0.70607051         0  virginica
11 Petal.Length    50 5.552 0.5518947   5.55 0.66717 4.5 6.9  0.54944459 -0.15377856         0  virginica
12  Petal.Width    50 2.026 0.2746501   2.00 0.29652 1.4 2.5 -0.12947693 -0.60226448         0  virginica

and

Variable     | Mean |   SD |  Min |  Max | n_Missing |  Group
-------------------------------------------------------------
Sepal.Length | 5.01 | 0.35 | 4.30 | 5.80 |         0 | setosa
Sepal.Width  | 3.43 | 0.38 | 2.30 | 4.40 |         0 | setosa
Petal.Length | 1.46 | 0.17 | 1.00 | 1.90 |         0 | setosa
Petal.Width  | 0.25 | 0.11 | 0.10 | 0.60 |         0 | setosa
      Variable  Mean        SD Min Max n_Missing      Group
1 Sepal.Length 5.006 0.3524897 4.3 5.8         0     setosa
2  Sepal.Width 3.428 0.3790644 2.3 4.4         0     setosa
3 Petal.Length 1.462 0.1736640 1.0 1.9         0     setosa
4  Petal.Width 0.246 0.1053856 0.1 0.6         0     setosa
5 Sepal.Length 5.936 0.5161711 4.9 7.0         0 versicolor
6  Sepal.Width 2.770 0.3137983 2.0 3.4         0 versicolor
7 Petal.Length 4.260 0.4699110 3.0 5.1         0 versicolor
8  Petal.Width 1.326 0.1977527 1.0 1.8         0 versicolor
       Variable  Mean        SD Min Max n_Missing      Group
1  Sepal.Length 5.006 0.3524897 4.3 5.8         0     setosa
2   Sepal.Width 3.428 0.3790644 2.3 4.4         0     setosa
3  Petal.Length 1.462 0.1736640 1.0 1.9         0     setosa
4   Petal.Width 0.246 0.1053856 0.1 0.6         0     setosa
5  Sepal.Length 5.936 0.5161711 4.9 7.0         0 versicolor
6   Sepal.Width 2.770 0.3137983 2.0 3.4         0 versicolor
7  Petal.Length 4.260 0.4699110 3.0 5.1         0 versicolor
8   Petal.Width 1.326 0.1977527 1.0 1.8         0 versicolor
9  Sepal.Length 6.588 0.6358796 4.9 7.9         0  virginica
10  Sepal.Width 2.974 0.3224966 2.2 3.8         0  virginica
11 Petal.Length 5.552 0.5518947 4.5 6.9         0  virginica
12  Petal.Width 2.026 0.2746501 1.4 2.5         0  virginica

With resulting output as expected

Group      |     Variable | n_Obs | Mean |   SD | Median |  MAD |  Min |  Max | Skewness | Kurtosis | n_Missing
---------------------------------------------------------------------------------------------------------------
setosa     | Sepal.Length |    50 | 5.01 | 0.35 |   5.00 | 0.30 | 4.30 | 5.80 |     0.12 |    -0.25 |         0
setosa     |  Sepal.Width |    50 | 3.43 | 0.38 |   3.40 | 0.37 | 2.30 | 4.40 |     0.04 |     0.95 |         0
setosa     | Petal.Length |    50 | 1.46 | 0.17 |   1.50 | 0.15 | 1.00 | 1.90 |     0.11 |     1.02 |         0
setosa     |  Petal.Width |    50 | 0.25 | 0.11 |   0.20 | 0.00 | 0.10 | 0.60 |     1.25 |     1.72 |         0
versicolor | Sepal.Length |    50 | 5.94 | 0.52 |   5.90 | 0.52 | 4.90 | 7.00 |     0.11 |    -0.53 |         0
versicolor |  Sepal.Width |    50 | 2.77 | 0.31 |   2.80 | 0.30 | 2.00 | 3.40 |    -0.36 |    -0.37 |         0
versicolor | Petal.Length |    50 | 4.26 | 0.47 |   4.35 | 0.52 | 3.00 | 5.10 |    -0.61 |     0.05 |         0
versicolor |  Petal.Width |    50 | 1.33 | 0.20 |   1.30 | 0.22 | 1.00 | 1.80 |    -0.03 |    -0.41 |         0
virginica  | Sepal.Length |    50 | 6.59 | 0.64 |   6.50 | 0.59 | 4.90 | 7.90 |     0.12 |     0.03 |         0
virginica  |  Sepal.Width |    50 | 2.97 | 0.32 |   3.00 | 0.30 | 2.20 | 3.80 |     0.37 |     0.71 |         0
virginica  | Petal.Length |    50 | 5.55 | 0.55 |   5.55 | 0.67 | 4.50 | 6.90 |     0.55 |    -0.15 |         0
virginica  |  Petal.Width |    50 | 2.03 | 0.27 |   2.00 | 0.30 | 1.40 | 2.50 |    -0.13 |    -0.60 |         0

easystats / report

Unstable group_by behaviour #162