Creating NumPy array with Pandas

Question

I'm trying to use scikit with some data that are in one spreadsheet (.xlsx). To achieve this I'm using Pandas to read the spreadsheet and then I was going to use numpy to use scikit.

The problem here is that when I covert my DF structure to numpy, I lose almost all the data! I think it is because it doesn't have columns names. There are just raw data. EX:

28.7967 16.0021 2.6449 0.3918 0.1982

31.6036 11.7235 2.5185 0.5303 0.3773

162.052 136.031 4.0612 0.0374 0.0187

My code so far:

def split_data():
    test_data = pd.read_excel('magic04.xlsx', sheetname=0, skip_footer=16020)
    #code below prints correctly the data
    print test_data.iloc[:, 0:10] 

    #none of the code below work as expected 
    test1 = np.array(test_data.iloc[:, 0:10])
    test2 = test_data.as_matrix()

I'm really lost here. Any help would be very welcome...

Ami Tavory · Accepted Answer · 2015-09-19 23:40:06Z

2

I'd suggest that you use header=None in read_excel. See the following:

df = pd.read_excel('stuff.xlsx')
>> df
    28.7967 16.0021 2.6449  0.3918  0.1982
0   31.6036 11.7235 2.5185  0.5303  0.3773
1   162.0520    136.0310    4.0612  0.0374  0.0187

>> df.ix[:, 1: 2]

0
1

Versus:

df = pd.read_excel('stuff.xlsx', header=None)
>> df

0   1   2   3   4
0   28.7967 16.0021 2.6449  0.3918  0.1982
1   31.6036 11.7235 2.5185  0.5303  0.3773
2   162.0520    136.0310    4.0612  0.0374  0.0187

>> df.ix[:, 1: 2]
    1   2
0   16.0021 2.6449
1   11.7235 2.5185
2   136.0310    4.0612

answered Sep 19, 2015 at 23:40

Ami Tavory

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1 Comment

renno Over a year ago

That worked!!! It worked with both ways: the attribute ".iloc[:, 0:X] " and the method "as_matrix()"! Really thanks!

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