functions on nested dataframes from R to python
Recently I have become addicted to the following pattern in R tidyverse:
mtcars %>%
as_tibble() %>%
tidyr::nest(-carb) %>%
mutate(data = purrr::map(data, function(x)
do_something_to_data
))
I tend to use it quite often to create nested dataframes depending on a variable (carb in this example) and to mutate the nested data (e.g. adding a new column or transforming an existing one).
I am curious about what would be the best way to achieve the same goal in python + pandas. Does pandas support nested dataframes, and if not, what would be the best data structure to emulate what R does here?
python r pandas tidyverse
add a comment |
Recently I have become addicted to the following pattern in R tidyverse:
mtcars %>%
as_tibble() %>%
tidyr::nest(-carb) %>%
mutate(data = purrr::map(data, function(x)
do_something_to_data
))
I tend to use it quite often to create nested dataframes depending on a variable (carb in this example) and to mutate the nested data (e.g. adding a new column or transforming an existing one).
I am curious about what would be the best way to achieve the same goal in python + pandas. Does pandas support nested dataframes, and if not, what would be the best data structure to emulate what R does here?
python r pandas tidyverse
add a comment |
Recently I have become addicted to the following pattern in R tidyverse:
mtcars %>%
as_tibble() %>%
tidyr::nest(-carb) %>%
mutate(data = purrr::map(data, function(x)
do_something_to_data
))
I tend to use it quite often to create nested dataframes depending on a variable (carb in this example) and to mutate the nested data (e.g. adding a new column or transforming an existing one).
I am curious about what would be the best way to achieve the same goal in python + pandas. Does pandas support nested dataframes, and if not, what would be the best data structure to emulate what R does here?
python r pandas tidyverse
Recently I have become addicted to the following pattern in R tidyverse:
mtcars %>%
as_tibble() %>%
tidyr::nest(-carb) %>%
mutate(data = purrr::map(data, function(x)
do_something_to_data
))
I tend to use it quite often to create nested dataframes depending on a variable (carb in this example) and to mutate the nested data (e.g. adding a new column or transforming an existing one).
I am curious about what would be the best way to achieve the same goal in python + pandas. Does pandas support nested dataframes, and if not, what would be the best data structure to emulate what R does here?
python r pandas tidyverse
python r pandas tidyverse
asked Nov 13 '18 at 13:52
RiccardoRiccardo
114
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