Following the example here
http://www.randalolson.com/2013/01/14/filling-in-pythons-gaps-in-statistics-packages-with-rmagic/
I tried the same on a different data set found here, in an IPython notebook.
https://github.com/burakbayramli/kod/blob/master/delltest/dell.tgz
from pandas import *
orders = read_csv("dell.csv",sep=",")
%load_ext rmagic
%R -i orders print(summary(orders))
I get
Length Class Mode
[1,] 25 -none- list
[2,] 25 -none- list
[3,] 25 -none- list
..
However the same in R
data <- read.csv ("dell.csv",header=TRUE,sep=",")
print (summary(data))
gives me the correct summary information.
rank per_customer_count total_total_amount orderid
Min. : 1.000 Min. : 1.000 Min. : 0.14 Min. : 1
1st Qu.: 2.000 1st Qu.: 6.000 1st Qu.: 866.11 1st Qu.: 2964
Median : 4.000 Median : 8.000 Median : 1764.08 Median : 5980
Mean : 4.997 Mean : 9.426 Mean : 2004.95 Mean : 5987
3rd Qu.: 7.000 3rd Qu.:12.000 3rd Qu.: 2856.06 3rd Qu.: 9004
...
Any ideas?
I had a quick look and there appear to be a number of situations in which the ipython magic is not getting the conversion right. I have to get in touch with them regarding rmagic and more magic.
In the meantime, you should be able to cook up what you need to progress from the snippet of code below:
import pandas
orders = pandas.read_csv("dell.csv", sep=",")
%load_ext rmagic
import rpy2.robjects
d = dict()
for i, (k,v) in enumerate(orders.iteritems()):
print("%s (type: %s - %i/%i)" %(k, v.dtype.kind, i, orders.shape[1]))
if v.dtype.kind == 'O':
v = rpy2.robjects.vectors.StrVector(v)
d[k] = rpy2.robjects.conversion.py2ri(v)
df = rpy2.robjects.DataFrame(d)
def print_rsummary(x):
print(rpy2.robjects.baseenv['summary'](x))
print_rsummary(df)
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