TypeError: 'float' object is not subscriptable --Python

Question

I am trying to create a program to take data from two CSV and then calculate distance and classify features. My code currently is working correctly only for the first iteration and whole code was working fine until I changed the return of weight_based_approach() function, earlier weight_based_approach() was returning 2 float values and now it is only returning one value here is the changed part of code:

    return (eucl_weight_prediction_count / len(test_data) * 100), (
            manhattan_metric_prediction_count / len(test_data) * 100)

Current full code:

import numpy as np
import matplotlib.pyplot as plt


class Implementation:
    def __init__(self):
        pass

    def Distancess(self, training_sub_data, query_instance):

        query_params = query_instance[:10]

        eucl = np.sqrt(np.sum((training_sub_data - query_params) ** 2, axis=-1))
        return eucl, np.argsort(eucl)

    def weight(self, training_data, distances, sorted_indices, k):
        i = 1
        samples_class = training_data[sorted_indices[:k]][:, -1]
        nearest_distances = distances[sorted_indices[:k]]
        nearest_weights = np.divide(1, np.square(nearest_distances))
        class_0_weights_sum = np.sum(nearest_weights[samples_class == 0])
        class_1_weights_sum = np.sum(nearest_weights[samples_class == 1])
        class_2_weights_sum = np.sum(nearest_weights[samples_class == 2])

        if class_0_weights_sum > class_1_weights_sum and class_0_weights_sum > class_2_weights_sum:
            return 0
        elif class_1_weights_sum > class_0_weights_sum and class_1_weights_sum > class_2_weights_sum:
            return 1
        else:
            return 2

def weight_based_approach(training_data, test_data, kn_k_value):
    training_data_10_columns = training_data[:, :10]

    kn = Implementation()

    eucl_weight_prediction_count = 0
    for query_instance in test_data:
        distances, euclidean_indices = kn.Distancess(training_data_10_columns, query_instance)

        weight_based_average = kn.weight(training_data, distances, euclidean_indices, kn_k_value)

        if query_instance[-1] == weight_based_average:
            eucl_weight_prediction_count += 1

    return eucl_weight_prediction_count / len(test_data) * 100


def main():
    global accuracies
    euclidean_accuracies = []
    k_samples = []
    k_samples.extend(list(range(1, 4, 1)))

    print("Range" + str(k_samples))

    for k in k_samples:
        training_file = "classification/trainingData.csv"
        test_file = "classification/testData.csv"
        kn_k_value = k

        training_data = np.genfromtxt(training_file, delimiter=",")
        test_data = np.genfromtxt(test_file, delimiter=",")

        accuracies = weight_based_approach(training_data, test_data, kn_k_value)
        euclidean_accuracies.append(accuracies[0])

    print("distance: " + str(euclidean_accuracies))

    plt.plot(k_samples, euclidean_accuracies, 'r')
    plt.xlabel('K{Number of Nearest Neighbour(s)}')
    plt.ylabel('Accuracy %')
    plt.title('K vs Accuracy graph')
    plt.grid(True)
    plt.show()


if __name__ == '__main__':
    main()

Error:

Traceback (most recent call last):
  File "A:\Anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3296, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-e142ccdf3a2c>", line 1, in <module>
    runfile('A:/Workspace/PML/R00182527/Part2a.py', wdir='A:/Workspace/PML/R00182527')
  File "C:\Program Files\JetBrains\PyCharm 2019.2.2\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "C:\Program Files\JetBrains\PyCharm 2019.2.2\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "A:/Workspace/P7/Part.py", line 143, in <module>
    main()
  File "A:/Workspace/P7/Part.py", line 126, in main
    euclidean_accuracies.append(accuracies[0])
TypeError: 'float' object is not subscriptable

Expecting accuracy % as an output

"whole code was working fine until I changed the return of weight_based_approach() function" Well, what was it before? And why did you change it? And why would you expect this change not to impact on the line in the code where the result is used? — Karl Knechtel
– Karl Knechtel, Commented Oct 28, 2019 at 1:41
@KarlKnechtel, Change was just the number of float values I was returning from that function. Updated question with previous code. — User
– User, Commented Oct 28, 2019 at 2:11
So you see how your eucl_weight_prediction_count / len(test_data) * 100 returns a floating point number as accuracies and you try to append that number accuracies[0] and that doesn't make sense right? Thanks for posting the full traceback, so +1. — Greg Schmit
– Greg Schmit, Commented Oct 28, 2019 at 3:37

Greg Schmit · Accepted Answer · 2019-10-28 01:51:02Z

3

You should try harder to build a Minimal, Reproducible Example. You should also post the full traceback of the error after you've reproduced the error in a minimal example program, so that we can see which line the error occurs on.

However, this error means that you cannot subscript a float because it isn't a container and doesn't implement __getitem__() (like a list, tuple, etc). I.e., this doesn't work:

>>> x = 3.2
>>> x[0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'float' object is not subscriptable

In your example, the variable accuracies is not a list/tuple, it is a float. Therefore, you've probably accidentally created a bug where you returned a float rather than a list/tuple.

edited Oct 28, 2019 at 1:51

answered Oct 28, 2019 at 1:40

Greg Schmit

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