convert numpy array to json

Question

Here is the input type, a NumPy array, like

[['id' '796132' '1148512' '87741691' '87910849' '88188296']
 ['diagnosis' '1' '0' '1' '0' '0']
 ['fractal_dimension_worst' '0.08701' '0.08006' '0.08255' '0.06484' '0.1118']] 

I want to convert it to a JSON file like

{
 "id": ['796132', '1148512', '87741691', '87910849', '88188296'],
 "diagnosis": ['1', '0', '1', '0', '0'],
 "fractal_dimension_worst": ['0.08701', '0.08006', '0.08255', '0.06484', '0.1118']
}

How to do that?

• hpaulj: Just treat it as a list of lists, even do arr.tolist(). Then create the dict from that. Should be a straight forward iteration.

Answer 1

You can use a dictionary comprehension like this:

import numpy as np
arr = np.array([
 ['id', '796132', '1148512', '87741691', '87910849', '88188296'],
 ['diagnosis', '1', '0', '1', '0', '0'],
 ['fractal_dimension_worst', '0.08701', '0.08006', '0.08255', '0.06484', '0.1118']
])
json_dict = {l[0]: list(l[1:]) for l in arr}
>> {'id': ['796132', '1148512', '87741691', '87910849', '88188296'],
 'diagnosis': ['1', '0', '1', '0', '0'],
 'fractal_dimension_worst': ['0.08701',
 '0.08006',
 '0.08255',
 '0.06484',
 '0.1118']}

Answer 2

That's how I do that after inspiring by @hpaulj.

import csv
import numpy as np
import pandas as pd
# df = pd.read_csv('inf_small.csv')
with open('..\inf.csv', newline='') as csvfile:
 data = list(csv.reader(csvfile, delimiter=','))
npMatrix = np.array(data)
# calculate row and column numbers
row_count, column_count = npMatrix.shape
# neglect first row and get new row numbers
row_count = row_count - 1
npMatrix = npMatrix.transpose()
# transfer numpy array to list
matrix = npMatrix.tolist()
# transfer list to that JSON file
result = {}
for index, item in enumerate(matrix):
 temp = item[0]
 del item[0]
 result[temp] = item