Reticulate converts Python integers to "-1" in R

[PizzaRoma]

>>> AAPL["financials"]["annual"]["revenue"]
[5742000000, 6207000000, 8279000000, 13931000000, 19315000000, 24578000000, 37491000000, 42905000000, 65225000000, 108249000000, 156508000000, 170910000000, 182795000000, 233715000000, 215639000000, 229234000000, 265595000000, 260174000000, 274515000000, 365817000000]

py$AAPL$financials$annual$revenue
 [1] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

What are the things I should start looking into?

> sessioninfo()
Error in sessioninfo() : could not find function "sessioninfo"
> sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 8.1 x64 (build 9600)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    
system code page: 1257

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] reticulate_1.23

loaded via a namespace (and not attached):
 [1] compiler_4.1.2    here_1.0.1        Matrix_1.3-4      rprojroot_2.0.2   tools_4.1.2      
 [6] rappdirs_0.3.3    Rcpp_1.0.8        grid_4.1.2        data.table_1.14.2 jsonlite_1.7.3   
[11] png_0.1-7         lattice_0.20-45  

[nirgrahamuk]

R integers can't store arbitrarily large numbers.

as.integer(2^30)
as.integer(2^31)

[1] 1073741824
[1] NA

your 'integers' are very large. either scale them down by division. or cast them to a type that accommodates larger values

[PizzaRoma]

Thank you.

fl = float(AAPL["financials"]["annual"]["revenue"][0])
5742000000.0
py$fl
[1] 5742000000

Works for single element.

Any suggestions for best practices to prepare complex data frames in Python for conversion to R for someone with zero knowledge in Python? For example change all integers to float for the whole data frame?