Setup

library(reticulate)
use_python("/usr/local/bin/python")
readr::write_csv(nycflights13::flights,path = "flights.csv")

From Python to R

Use Python to manipulate data

import pandas
flights = pandas.read_csv("flights.csv")
flights = flights[flights['dest'] == "ORD"]
flights = flights[['carrier', 'dep_delay', 'arr_delay']]
flights = flights.dropna()

Use R to visualize Pandas DataFrame

library(ggplot2)
ggplot(py$flights, aes(carrier, arr_delay)) + geom_point() + geom_jitter()

From R to Python

Use R to read and manipulate data

library(tidyverse)
flights <- read_csv("flights.csv") %>%
  filter(dest == "ORD") %>%
  select(carrier, dep_delay, arr_delay) %>%
  na.omit()

Use Python to print R dataframe

print r.flights.head(10)
  carrier  dep_delay  arr_delay
0      UA       -4.0       12.0
1      AA       -2.0        8.0
2      MQ        8.0       32.0
3      AA       -1.0       14.0
4      AA       -4.0        4.0
5      UA        9.0       20.0
6      UA        2.0       21.0
7      AA       -6.0      -12.0
8      MQ       39.0       49.0
9      B6       -2.0       15.0

See the reticulate website for details.

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