Python - Using column headings as keys for dictionary from csv file (without import module)

Question

I must perform some calculations with values provided from a.csv file, and need to use the column headings as keys to their values in each column. However there is a likelihood that the columns of the file may be jumbled up or swapped around, and thus simply indexing for the values of each key wouldn't work. Also keeping in mind i cant import any modules such as csv. Heres a sample of what the csv file would look like, except with many more rows, and more AdultIDs...

AdultID	Landmark	X	Y	Z
R7033	Ex_L	-32	-39	-4.6
R7033	En_L	-1.8	-41	6.7
R7033	N	12	-34	22.6
R7033	En_R	30.1	-43	8.3

So effectively, I need the dictionary as such: {AdultID: [R7033, R7033, R7033], Landmark:[Ex_L, En_R, N, En_R]... } and so on.

Answer 1

Assume that your input file (let's call it luh.csv) is a well formed CSV using commas as delimiters like this:

AdultID,Landmark,X,Y,Z
R7033,Ex_L,-32,-39,-4.6
R7033,En_L,-1.8,-41,6.7
R7033,N,12,-34,22.6
R7033,En_R,30.1,-43,8.3

Then:

with open('luh.csv') as csv:
    columns = next(csv).strip().split(',')
    dict_ = {}
    for line in map(str.strip, csv):
        for col, val in zip(columns, line.split(',')):
            dict_.setdefault(col, []).append(val)
    print(dict_)

Output:

{'AdultID': ['R7033', 'R7033', 'R7033', 'R7033'], 'Landmark': ['Ex_L', 'En_L', 'N', 'En_R'], 'X': ['-32', '-1.8', '12', '30.1'], 'Y': ['-39', '-41', '-34', '-43'], 'Z': ['-4.6', '6.7', '22.6', '8.3']}