Converting a data dictionary to numpy array in python

Question

im trying to convert a data dictionary with a structure as below:

{'name': array(['Ben','Sean,'Fred'])
 'age': array([22, 16, 35]),
 'marks': array([98, 75, 60]),
 'result': array('HD','D','C')}

I need to then filter out the dictionary to only include name, mark and result in the new numpy array to be able to plot on a graph (i can do this but cant for the life of me filter the list and then convert to numpy)

Answer 1

Let's assume your dictionary is something like this.

dict = {
'name': ['Ben','Sean','Fred'],
'age': [22, 16, 35], 
'marks': [98, 75, 60], 
'result': ['HD','D','C']
}

You can iterate over the dictionary to get desired values and append them into a list. Then convert it into a NumPy array. Here I am using all of the keys

name, age, marks, result

but you can filter some keys if you like.

if key not in ['age']:

import numpy as np
data_list = []
for key, val in dict.items():
    data_list.append(val)

numpy_array = np.array(data_list)
transpose = numpy_array.T
transpose_list = transpose.tolist()

The end result will be following:

[['Ben', '22', '98', 'HD'],
['Sean', '16', '75', 'D'],
['Fred', '35', '60', 'C']]

Answer 2

You can try pandas

import pandas as pd

d = {
    'name': ['Ben','Sean','Fred'],
    'age': [22, 16, 35],
    'marks': [98, 75, 60],
    'result': ['HD','D','C']
}

df = pd.DataFrame(d)

result = df[['name', 'marks', 'result']].T.values

print(type(result))
print(result)

<class 'numpy.ndarray'>
[['Ben' 'Sean' 'Fred']
 [98 75 60]
 ['HD' 'D' 'C']]