pandas reading csv orientation

Question

Hei I\'m trying to read in pandas the csv file you can download from here (euribor rates I think you can imagine the reason I would like to have this file!). The file is a CSV f

Answer 1

A pandas dataframe has a .transpose() method, but it doesn't like all the empty rows in this file. Here's how to get it cleaned up:

df = pandas.read_csv("hist_EURIBOR_2012.csv")  # Read the file
df = df[:15]    # Chop off the empty rows beyond 12m
df2 = df.transpose()
df2 = df2[:88]  # Chop off what were empty columns (I guess you should increase 88 as more data is added.

Of course, you can chain these together:

df2 = pandas.read_csv("hist_EURIBOR_2012.csv")[:15].transpose()[:88]

Then df2['3m'] is the data you want, but the dates are still stored as strings. I'm not quite sure how to convert it to a DateIndex.

Answer 2

I've never used pandas for csv processing. I just use the standard Python lib csv functions as these use iterators.

import csv
myCSVfile=r"c:/Documents and Settings/Jason/Desktop/hist_EURIBOR_2012.csv"
f=open(myCSVfile,"r")
reader=csv.reader(f,delimiter=',')
data=[]
for l in reader:
    if l[0].strip()=="3m":
        data.append(l)

f.close()