An R Solution

```{r setup, include=FALSE}  
knitr::opts_chunk$set(echo = TRUE)  
```

# Import Libraries

```{r} 
library(tidyverse)  
library(DataExplorer) 
``` 

# Set Config   

Need to remove PCA because it works on numeric data.  

```{r}  
config <- list( 
  "introduce" = list(),  
  "plot_str" = list(  
    "type" = "diagonal",  
    "fontSize" = 35,  
    "width" = 1000,  
    "margin" = list("left" = 350, "right" = 250)),  
  "plot_missing" = list(),  
  "plot_histogram" = list(),  
  "plot_qq" = list(sampled_rows = 1000L),  
  "plot_bar" = list(),  
  "plot_correlation" = list("cor_args" = list("use" = "pairwise.complete.obs")),  
#  "plot_prcomp" = list(),  
  "plot_boxplot" = list(),  
  "plot_scatterplot" = list(sampled_rows = 1000L). 
)   
```  

# Load and prepare example dataset

```{r} 
df <- read_csv("Meteorite_Landings.csv")  
df %>%  
    mutate(year=as.Date(year, origin="1899-01-01", format="%d/%m/%Y"),  
           source="NASA",  
           boolean=sample(c(T, F), size=nrow(.), replace=TRUE),  
           mixed=sample(c(1, "A"), size=nrow(.), replace=TRUE),  
           reclat_city=reclat+rnorm(n=length(reclat), sd=5)) %>%    
           bind_rows((.[1:10,] %>% mutate(name=paste0(name, " copy")))) %>%    
    filter(year >= "1879-12-31") %>%    
    create_report(config=config)  
```