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Great package for exploratory data analysis, thanks for sharing!
Could the package enable filtering results before plotting? I'd love to be able to do something like this:
# Load packages library(inspectdf) library(dplyr) # Single dataframe summary inspect_cor(starwars) #> # A tibble: 3 x 7 #> col_1 col_2 corr p_value lower upper pcnt_nna #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 birth_year mass 0.478 0.00602 0.177 0.697 41.4 #> 2 birth_year height -0.400 0.0114 -0.625 -0.113 49.4 #> 3 mass height 0.134 0.316 -0.127 0.377 67.8 # Filter inspect_cor(starwars) %>% filter(abs(corr) > 0.2) #> # A tibble: 2 x 7 #> col_1 col_2 corr p_value lower upper pcnt_nna #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 birth_year mass 0.478 0.00602 0.177 0.697 41.4 #> 2 birth_year height -0.400 0.0114 -0.625 -0.113 49.4 # Filter and plot inspect_cor(starwars) %>% filter(abs(corr) > 0.2) %>% show_plot() #> Error: Tibble columns must have consistent sizes, only values of size one are recycled: #> * Size 2: Existing data #> * Size 3: Column `pair`
Created on 2020-02-21 by the reprex package (v0.3.0)
When you have a lot of features, you want to focus only on relevant correlations and avoid clutter.
The text was updated successfully, but these errors were encountered:
Hi @RoelVerbelen thanks a lot for the report, this should now work on the GH version. CRAN update to follow in a week or so.
Thanks! Alastair
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Fantastic, thanks Alastair!
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Great package for exploratory data analysis, thanks for sharing!
Could the package enable filtering results before plotting? I'd love to be able to do something like this:
Created on 2020-02-21 by the reprex package (v0.3.0)
When you have a lot of features, you want to focus only on relevant correlations and avoid clutter.
The text was updated successfully, but these errors were encountered: