CODEWITHSUNDEEP
pythonarrayslistnumpy
khelili miliana
khelili miliana

Reputation: 3822

Split numpy array based column value in list

I'am new in numpy and I want to split array 2D based on columns values if value in another list, I converted a pandas dataframe on numpy array of 2D and I have a another list, I want to split my numpy array on two others array, the first based on (if values of second column in list) and the second contains the rest of my numpy array, and I want to get the rest of my list(contains all values doesn't exist in my numpy array)

numpy_data = np.array([
        [1, 'p1', 2],
        [11, 'p2', 8],
        [1, 'p8', 21],
        [13, 'p10', 2] ])

list_value = ['p1', 'p3', 'p8']

The expected output :

data_in_list = [
        [1, 'p1', 2],
        [1, 'p8', 21]]
list_val_in_numpy = ['p1', 'p8'] # intersection of second column with my list

rest_data = [
        [11, 'p2', 8],
        [13, 'p10', 2]] 
rest_list_value = ['p3']

In my code I have found how to get first output :

first_output =  numpy_data[np.isin(numpy_data[:,1], list_value)]

But I couldn't find the rest of my numpy, I have tried too, Browse my list and seek if values in second column of array and then delete this row, in this case I dont need the first output (That I called data_in_list, b-coz I do what I need on it), here I need the others output

for val in l :
    row = numpy_data[np.where(numpy_data[:,1]== val)]
    row.size != 0 :
        # My custom code
        # then remove this row from my numpy, I couldn't do it

Thanks in advance

Upvotes: 1

Views: 1432

Answers (3)

Yossi Levi
Yossi Levi

Reputation: 1268

list comprehension will solve it I guess:

numpy_data = [
        [1, 'p1', 2],
        [11, 'p2', 8],
        [1, 'p8', 21],
        [13, 'p10', 2],

]

list_value = ['p1', 'p3', 'p8']

output_list = [[item] for item in numpy_data if item[1] in list_value]
print(output_list)

output:

[[[1, 'p1', 2]], [[1, 'p8', 21]]]

Upvotes: 0

Bharath
Bharath

Reputation: 416

There are multiple ways of doing this. I would prefer a vectorized way of using list comprehension. But for sake of clarity here is loop way of doing the same thing.

data_in_list=[]
list_val_in_numpy = []
rest_data=[]
for x in numpy_data:
    for y in x:
        if y in list_value:
            data_in_list.append(x)
            for x in list_value:
                if x == y:
                    list_val_in_numpy.append(x)
for x in numpy_data:
    if x in data_in_list:
        pass
    else:
        rest_data.append(x)

This gives you all the three lists you were looking for. Concatenate to get the list you want exactly.

Upvotes: 0

Gilad Green
Gilad Green

Reputation: 37299

Use python's invert ~ operator over the result of the np.isin:

rest = numpy_data[~np.isin(numpy_data[:,1], list_value)]

Upvotes: 2

Related Questions