Testing rpy2

testrpy2.py

import pandas as pd
import numpy as np
import rpy2
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
from pprint import pprint
import requests

req = requests.get('http://www.google.com')
pprint(req)

# Here is how imports work.
stats = importr('stats')
base = importr('base')
amelia = importr('Amelia') # Make sure you have this installed.

# Here is how to grab a constant
pi = robjects.r['pi']
print(pi[0])

# Or a whole data frame
dat = robjects.r['iris']

# Here is how you take an R function and put it in python
rhead =  robjects.r['head']
rhead2 = lambda x : map(rhead,x)

print(rhead(dat)[0])
pprint(rhead2(dat))

# Here's another R function used here:
rnorm = stats.rnorm

print(rnorm(100))

# So important:
summary = robjects.r['summary']

print(summary(rnorm(100)))
print(summary(dat)) # wow!  It works on the object I brought in!

from datetime import datetime
import pandas.rpy.common as com

# generate some fake tick data with 1 million observations
n = 10
df = pd.DataFrame({
    "timestamp": [datetime.now() for t in range(n)],
    "value": np.random.uniform(-1, 1, n)
    })
 
# similar dataframe operations to R
df.head()
df.describe()
df.count()

r_dataframe = com.convert_to_r_dataframe(df)
print(r_dataframe)


# GRAPHICS DEMO
from rpy2 import robjects
from rpy2.robjects import Formula, Environment
from rpy2.robjects.vectors import IntVector, FloatVector
from rpy2.robjects.lib import grid
from rpy2.robjects.packages import importr, data
from rpy2.rinterface import RRuntimeError
import warnings

# The R 'print' function
rprint = robjects.globalenv.get("print")
#stats = importr('stats')
grdevices = importr('grDevices')
#base = importr('base')
datasets = importr('datasets')

grid.activate()
lattice = importr('lattice')
xyplot = lattice.xyplot
datasets = importr('datasets')
mtcars = data(datasets).fetch('mtcars')['mtcars']
formula = Formula('mpg ~ wt')
formula.getenvironment()['mpg'] = mtcars.rx2('mpg')
formula.getenvironment()['wt'] = mtcars.rx2('wt')

p = lattice.xyplot(formula)
#rprint(p)

# GRAPHICS GGPLOT
import math, datetime
import rpy2.robjects.lib.ggplot2 as ggplot2
import rpy2.robjects as ro
from rpy2.robjects.packages import importr
#base = importr('base')

mtcars = data(datasets).fetch('mtcars')['mtcars']
rnorm = stats.rnorm
dataf_rnorm = robjects.DataFrame({'value': rnorm(300, mean=0) + rnorm(100, mean=3),
                                  'other_value': rnorm(300, mean=0) + rnorm(100, mean=3),
                                  'mean': IntVector([0, ]*300 + [3, ] * 100)})


gp = ggplot2.ggplot(mtcars)

pp = gp + \
     ggplot2.aes_string(x='wt', y='mpg') + \
     ggplot2.geom_point() + \
     ggplot2.theme_bw()

pp.plot()