How to create my own datasets using in scikit-learn?

Question

I want to create my own datasets, and use it in scikit-learn. Scikit-learn has some datasets like 'The Boston Housing Dataset' (.csv), user can use it by:

from sklearn import datasets 
boston = datasets.load_boston()

and codes below can get the data and target of this dataset:

X = boston.data
y = boston.target

The question is how to create my own dataset and can be used in that way? Any answers is appreciated, Thanks!

Answer 1

Here's a quick and dirty way to achieve what you intend:

my_datasets.py

import numpy as np
import csv
from sklearn.utils import Bunch

def load_my_fancy_dataset():
    with open(r'my_fancy_dataset.csv') as csv_file:
        data_reader = csv.reader(csv_file)
        feature_names = next(data_reader)[:-1]
        data = []
        target = []
        for row in data_reader:
            features = row[:-1]
            label = row[-1]
            data.append([float(num) for num in features])
            target.append(int(label))
        
        data = np.array(data)
        target = np.array(target)
    return Bunch(data=data, target=target, feature_names=feature_names)

my_fancy_dataset.csv

feature_1,feature_2,feature_3,class_label
5.9,1203,0.69,2
7.2,902,0.52,0
6.3,143,0.44,1
-2.6,291,0.15,1
1.8,486,0.37,0

Demo

In [12]: import my_datasets

In [13]: mfd = my_datasets.load_my_fancy_dataset()

In [14]: X = mfd.data

In [15]: y = mfd.target

In [16]: X
Out[16]: 
array([[ 5.900e+00,  1.203e+03,  6.900e-01],
       [ 7.200e+00,  9.020e+02,  5.200e-01],
       [ 6.300e+00,  1.430e+02,  4.400e-01],
       [-2.600e+00,  2.910e+02,  1.500e-01],
       [ 1.800e+00,  4.860e+02,  3.700e-01]])

In [17]: y
Out[17]: array([2, 0, 1, 1, 0])

In [18]: mfd.feature_names
Out[18]: ['feature_1', 'feature_2', 'feature_3']