Consistent accuracy for number display

[hope-data-science]

I have seen the following plot in README, and I wonder whether we can keep a consistent accuracy, which means the "1" should be "1.00", and "1.4" should be "1.40" (I myself use scales package and yields similar results, and in many cases this should be adjusted). Thanks.

[jpquast]

@hope-data-science I agree with you. I found the issue in the paste() function. Didn't know it had this behaviour (see below). I fixed it now and it will be correct in the new version.

# Load library
library(ggplate)
#> 📊 Welcome to ggplate version 0.0.1! 📈
#>                             
#> 🖍 Have fun plotting your data! 💻

# Load data
data("data_continuous_96")

# Numeric values
data_continuous_96$Value
#>  [1] 1.19 0.88 0.17 0.85 0.78 0.23 1.95 0.40 0.88 0.26 1.47 3.04 0.05 0.97 0.90
#> [16] 0.02 2.06 1.01 0.92 1.66 0.12 0.41 1.70 0.24 0.26 2.12 0.17 0.83 0.75 0.25
#> [31] 0.62 0.28 1.36 0.18 0.04 0.03 1.71 0.41 0.35 1.24 1.82 1.17 0.33 0.51 0.23
#> [46] 0.41 0.33 2.73 1.00 0.47 0.05 0.17 0.08 0.67 1.40 0.35 1.05 0.62 1.82 0.10
#> [61] 0.50 0.07 0.20 0.67 0.63 1.65 0.64 0.38 0.87 1.68 1.41 0.98 0.36 0.50 0.65
#> [76] 0.03 1.51 0.37 0.11 0.10 0.39 0.07 0.84 0.41 1.13 0.83 1.11 0.19 0.64 0.32
#> [91] 0.51 1.64 0.85 0.32 1.12 0.91

# Problem when converted to character
paste0(data_continuous_96$Value)
#>  [1] "1.19" "0.88" "0.17" "0.85" "0.78" "0.23" "1.95" "0.4"  "0.88" "0.26"
#> [11] "1.47" "3.04" "0.05" "0.97" "0.9"  "0.02" "2.06" "1.01" "0.92" "1.66"
#> [21] "0.12" "0.41" "1.7"  "0.24" "0.26" "2.12" "0.17" "0.83" "0.75" "0.25"
#> [31] "0.62" "0.28" "1.36" "0.18" "0.04" "0.03" "1.71" "0.41" "0.35" "1.24"
#> [41] "1.82" "1.17" "0.33" "0.51" "0.23" "0.41" "0.33" "2.73" "1"    "0.47"
#> [51] "0.05" "0.17" "0.08" "0.67" "1.4"  "0.35" "1.05" "0.62" "1.82" "0.1" 
#> [61] "0.5"  "0.07" "0.2"  "0.67" "0.63" "1.65" "0.64" "0.38" "0.87" "1.68"
#> [71] "1.41" "0.98" "0.36" "0.5"  "0.65" "0.03" "1.51" "0.37" "0.11" "0.1" 
#> [81] "0.39" "0.07" "0.84" "0.41" "1.13" "0.83" "1.11" "0.19" "0.64" "0.32"
#> [91] "0.51" "1.64" "0.85" "0.32" "1.12" "0.91"

# Corrected output
paste0(format(data_continuous_96$Value, drop0Trailing = F))
#>  [1] "1.19" "0.88" "0.17" "0.85" "0.78" "0.23" "1.95" "0.40" "0.88" "0.26"
#> [11] "1.47" "3.04" "0.05" "0.97" "0.90" "0.02" "2.06" "1.01" "0.92" "1.66"
#> [21] "0.12" "0.41" "1.70" "0.24" "0.26" "2.12" "0.17" "0.83" "0.75" "0.25"
#> [31] "0.62" "0.28" "1.36" "0.18" "0.04" "0.03" "1.71" "0.41" "0.35" "1.24"
#> [41] "1.82" "1.17" "0.33" "0.51" "0.23" "0.41" "0.33" "2.73" "1.00" "0.47"
#> [51] "0.05" "0.17" "0.08" "0.67" "1.40" "0.35" "1.05" "0.62" "1.82" "0.10"
#> [61] "0.50" "0.07" "0.20" "0.67" "0.63" "1.65" "0.64" "0.38" "0.87" "1.68"
#> [71] "1.41" "0.98" "0.36" "0.50" "0.65" "0.03" "1.51" "0.37" "0.11" "0.10"
#> [81] "0.39" "0.07" "0.84" "0.41" "1.13" "0.83" "1.11" "0.19" "0.64" "0.32"
#> [91] "0.51" "1.64" "0.85" "0.32" "1.12" "0.91"

^{Created on 2023-11-09 with reprex v2.0.2}