Using the python 2.7 shell on osx lion. The .csv file has 12 columns by 892 rows.
import csv as csv
import numpy as np
# Open up csv file into a Python object
csv_file_object = csv.reader(open('/Users/scdavis6/Documents/Kaggle/train.csv', 'rb'))
header = csv_file_object.next()
data=[]
for row in csv_file_object:
data.append(row)
data = np.array(data)
# Convert to float for numerical calculations
number_passengers = np.size(data[0::,0].astype(np.float))
And this is the error I get:
Traceback (most recent call last):
File "pyshell#5>", line 1, in <module>
number_passengers = np.size(data[0::,0].astype(np.float))
TypeError: list indices must be integers, not tuple
What am I doing wrong.
Don't use csv to read the data into a NumPy array. Use numpy.genfromtxt; using dtype=None will cause genfromtxt to make an intelligent guess at the dtypes for you. By doing it this way you won't have to manually convert strings to floats.
data[0::, 0] just gives you the first column of data.
data[:, 0] would give you the same result.
The error message
TypeError: list indices must be integers, not tuple
suggests that for some reason your data variable might be holding a list rather than a ndarray. For example, the same Exception can produced like this:
In [73]: data = [1,2,3]
In [74]: data[1,2]
TypeError: list indices must be integers, not tuple
I don't know why that is happening, but if you post a sample of your CSV we should be able to help fix that.
Using np.genfromtxt, your current code could be simplified to:
import numpy as np
filename = '/Users/scdavis6/Documents/Kaggle/train.csv'
data = np.genfromtxt(filename, delimiter=',', skiprows=1, dtype=None)
number_passengers = np.size(data, axis=0)