Welcome to the rpy2 Documentation

import pandas as pd
import rpy2.robjects as ro
from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr

# Activate conversion between pandas and R
pandas2ri.activate()

# Create pandas DataFrame
pdf = pd.DataFrame({
    'a': [1, 2, 3, 4, 5],
    'b': ['a', 'b', 'c', 'd', 'e'],
    'c': [True, False, True, False, True]
})

# Convert to R DataFrame
rdf = pandas2ri.py2rpy(pdf)

# Use R functions on the dataframe
stats = importr('stats')
result = stats.aggregate(rdf.rx2('a'), rdf.rx2('c'), ro.r('mean'))

# Convert result back to Python
py_result = pandas2ri.rpy2py(result)

import rpy2.robjects as ro
from rpy2.robjects.packages import importr
from rpy2.robjects import pandas2ri
import pandas as pd

# Activate pandas to R conversion
pandas2ri.activate()

# Import ggplot2 and other packages
ggplot2 = importr('ggplot2')
datasets = importr('datasets')

# Get mtcars dataset
mtcars = ro.r('mtcars')
# For Python object
mtcars_pd = pandas2ri.rpy2py(mtcars)

# Create a ggplot
pp = ggplot2.ggplot(mtcars) + \
     ggplot2.aes_string(x='wt', y='mpg', color='factor(cyl)') + \
     ggplot2.geom_point() + \
     ggplot2.ggtitle('MPG vs Weight by Cylinders')

# Display the plot
ro.r.X11()
pp.plot()
input("Press Enter to continue...")