Question

I am trying to create a function to read 2 csv files that contain 5 columns of data. Columns 1-4 are floats and column 5 is a string.

I want to only work on with the floats to perform some calculations such as sum of the first 2 columns of each file and then return the closest numbers then return the string to identify the 2 rows of data.

Below is what I have so far. There is a stipulation that I can only use the numpy import.

data =[(x.rstrip()) for x in open('test.csv')]
data2 =[(x.rstrip()) for x in open('training.csv')]

k= len(data)
datas = dict(zip(range(k),data[0:k]))
datas2 = dict(zip(range(k),datas[0:k]))

Data used:

Training
a1	b1	c1	d1	name training
5	3	1.6	0.2	G
5	3.4	1.6	0.4	G
5.5	2.4	3.7	1	R
5.8	2.7	3.9	1.2	R
7.2	3.2	6	1.8	Y
6.2	2.8	4.8	1.8	Y
testing
a2	b2	c2	d2	name true
5	3.6	1.4	0.2	G
5.4	3.9	1.7	0.4	G
6.9	3.1	4.9	1.5	R
5.5	2.3	4	1.3	R
6.4	2.7	5.3	1.9	Y
6.8	3	5.5	2.1	Y

Answer 1

# The Code first sums the first two columns of train and test files and then find difference between the sums. The difference which <=1 is nearest in both train and test. So it prints out the corresponding 'name training'.

  

Please comment for any query.