syntax-error.json

[
 "\n{'code': '\\nimport numpy as np\\nmean = np.mean(arr1)\\n', 'is_good': True, 'is_bad': False, 'is_expert': True}",
 "\n{'code': '\\narr2 = np.array(arr1)\\nmean = np.mean(arr2)\\n', 'is_good': True, 'is_bad': False, 'is_expert': True}",
 "\n{'code': '\\nmean = sum(arr1) / len(arr1)\\n', 'is_good': True, 'is_bad': False, 'is_expert': True}",
 "\n{'code': '\\ncount = 0\\nfor x in arr1:\\n    count += x\\nmean = count / len(arr1)\\n', 'is_good': True, 'is_bad': False, 'is_expert': False}",
 "\n{'code': '\\ncount = 0\\nfor (index, value) in enumerate(arr1):\\n    count += arr1[index]\\nmean = count / len(arr1)\\n', 'is_good': True, 'is_bad': False, 'is_expert': True}",
 "\n{'code': '\\narr2 = arr1.copy()\\narr2.sort()\\nlen_arr1 = len(arr1)\\nmiddle_index = int(len_arr1 / 2)\\nmean = (arr2[middle_index - 1] + arr2[middle_index]) / 2\\n', 'is_good': True, 'is_bad': False, 'is_expert': False}",
 "\n{'code': '\\narr2 = np.array(arr1)\\narr2.sort()\\nmean = arr2[int(len_arr1 / 2)]\\n', 'is_good': True, 'is_bad': False, 'is_expert': True}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)'}",
 "\n{'code': 'sum = 0\\nfor i in range(len(arr1)):\\n    sum+=arr1[i]\\nmean = sum / len(arr1)'}",
 "\n{'code': 'sum = 0\\nfor i in arr1:\\n    sum+=i\\nmean = sum / len(arr1)'}",
 "\n{'code': 'return sum(arr1) / len(arr1)'}",
 "\n{'code': 'count = 0\\nfor (index, value) in enumerate(arr1):\\n    count += value\\nmean = count / len(arr1)'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)'}",
 "\n{'code': 'import statistics\\nmean = statistics.mean(arr1)'}",
 "\n{'code': 'mean = np.average(arr1)'}",
 "\n{'code': 'from scipy.stats import mean\\nmean = mean(arr1)'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'explanation': 'uses np.mean() library function to compute mean', 'level': 'intermediate'}",
 "\n{'code': 'import statistics\\nmean = statistics.mean(arr1)', 'explanation': 'uses statistics.mean() library function to compute mean', 'level': 'expert'}",
 "\n{'code': 'from collections import Counter\\nmean = sum(Counter(arr1).values()) / len(Counter(arr1))', 'explanation': 'uses Counter library function to compute mean', 'level': 'expert'}",
 "\n{'code': 'mean = sum(arr1) / len(arr1)', 'explanation': 'simple python implementation of mean', 'level': 'beginner'}",
 "\n{'code': 'sum = 0\\nfor i in arr1:\\n    sum += i\\nmean = sum / len(arr1)'}",
 "\n{'code': 'mean = sum(arr1) / len(arr1)'}",
 "\n{'code': '\\nfrom statistics import mean\\n\\ndef get_mean(arr):\\n    if len(arr) == 0:\\n        return 0\\n\\n    return mean(arr)\\n\\nmean = get_mean(arr1)'}",
 "\n{'code': 'import numpy as np\\na = np.array(arr1)\\nmean = np.mean(a)', 'level': 'beginner', 'explanation': 'This is a beginner-level example because it is the simplest way to compute the mean of a list of numbers. It uses the `numpy.mean()` function, which is a built-in function in the numpy library.', 'tags': ['numpy']}",
 "\n{'code': 'def get_mean(arr):\\n    sum_ = 0\\n    for x in arr:\\n        sum_ += x\\n    return sum_ / len(arr)\\n\\nmean = get_mean(arr1)', 'level': 'intermediate', 'explanation': 'This is an intermediate-level example because it uses a custom function to compute the mean of a list of numbers. The function first sums the values in the list, then divides the sum by the length of the list to get the mean.', 'tags': ['custom function']}",
 "\n{'code': 'def get_mean(arr):\\n    n = len(arr)\\n    sum_ = 0\\n    for i in range(n):\\n        sum_ += arr[i]\\n    return sum_ / n\\n\\nmean = get_mean(arr1)', 'level': 'expert', 'explanation': 'This is an expert-level example because it uses a custom function to compute the mean of a list of numbers. The function uses a for loop to iterate over the list, and then sums the values in the list. The function then divides the sum by the length of the list to get the mean.', 'tags': ['custom function', 'for loop']}",
 "\n{'code': 'def get_mean(arr):\\n    mean = sum(arr) / len(arr)\\n    return mean\\nmean = get_mean(arr1)', 'type': 'beginner'}",
 "\n{'code': 'mean = sum(arr1) / len(arr1)', 'type': 'intermediate'}",
 "\n{'code': 'import statistics\\nmean = statistics.mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'explanation': 'This is a simple example using the numpy.mean function to calculate the mean of an array.', 'level': 'beginner'}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)', 'explanation': 'This is another simple example using the statistics.mean function to calculate the mean of an array.', 'level': 'beginner'}",
 "\n{'code': 'import statistics\\ndef mean(array):\\n    if len(array) > 0:\\n        return sum(array) / len(array)\\nmean = mean(arr1)', 'explanation': 'This is an intermediate example using a custom function to calculate the mean of an array.', 'level': 'intermediate'}",
 "\n{'code': 'import numpy as np\\ndef mean(array):\\n    return sum(array) / len(array)\\nmean = mean(arr1)', 'explanation': 'This is an advanced example using a custom function and numpy to calculate the mean of an array.', 'level': 'expert'}",
 "\n{'code': 'def mean(array):\\n    return np.mean(array)\\nmean = mean(arr1)'}",
 "\n{'code': 'import numpy as np\\nmean = np.sum(arr1) / len(arr1)'}",
 "\n{'code': '\\nimport numpy as np\\n\\ncount = np.sum(arr1)\\nmean = count / np.size(arr1)\\n'}",
 "\n{'code': '\\ncount = 0\\nfor value in arr1:\\n    count += value\\nmean = count / np.size(arr1)\\n'}",
 "\n{'code': '\\nmean = np.average(arr1)\\n'}",
 "\n{'code': '\\nmean = sum(arr1) / np.size(arr1)\\n'}",
 "\n{'import numpy as np\\nmean=np.mean(arr1)'}",
 "\n{'import statistics\\nmean=statistics.mean(arr1)'}",
 "\n{'mean = sum(arr1) / len(arr1)'}",
 "\n{'mean = 0\\nfor x in arr1:\\n    mean += x\\nmean /= len(arr1)'}",
 "\n{'python': {'source': '\\ndef mean_(arr):\\n    sum = 0.\\n    for ele in arr:\\n        sum += ele\\n    return sum / len(arr)\\n\\nmean = mean_(arr1)\\n', 'imports': []}}",
 "\n{'python': {'source': '\\nfrom functools import reduce\\nimport operator\\n\\ndef mean_(arr):\\n    return reduce(operator.add, arr) / len(arr)\\n\\nmean = mean_(arr1)\\n', 'imports': ['operator']}}",
 "\n{'code': 'mean = sum(arr1) / len(arr1)', 'type': 'beginner'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'type': 'intermediate'}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'level': 'beginner'}",
 "\n{'code': 'import numpy as np\\nmean = np.sum(arr1) / len(arr1)', 'level': 'intermediate'}",
 "\n{'code': 'mean = (sum(arr1) / len(arr1)) ** 2', 'level': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'type': 'beginner'}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)', 'type': 'intermediate'}",
 "\n{'code': 'def my_mean(arr): return sum(arr) / len(arr)\\nmean = my_mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.average(arr1)'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1, axis=0)'}",
 "\n{'code': 'import statistics as st\\nmean = st.mean(arr1)'}",
 "\n{'code': 'from collections import Counter\\nmean = float(sum(Counter(arr1).values())) / len(arr1)'}",
 "\n{'code': 'import math\\nmean = sum(arr1) / len(arr1)'}",
 "\n{'code': '\\n            import statistics as st\\n            import numpy as np\\n            mean = st.mean(arr1)\\n            '}",
 "\n{'code': 'mean = np.mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'mean = sum(arr1) / float(len(arr1))', 'type': 'intermediate'}",
 "\n{'code': 'sum = 0.0\\nfor val in arr1:\\n    sum += val\\nmean = sum / len(arr1)', 'type': 'beginner'}",
 "\n{'code': 'n = len(arr1)\\nsum = 0.0\\nfor val in arr1:\\n    sum += val\\nmean = sum / float(n)', 'type': 'intermediate'}",
 "\n{'code': 'sum = 0.0\\nfor val in arr1:\\n    sum += val\\nmean = sum / float(len(arr1))\\nprint(mean)', 'type': 'intermediate'}",
 "\n{'code': 'mean = (sum(arr1) - arr1[0] - arr1[-1]) / (len(arr1) - 2)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.median(arr1)', 'lang': 'python'}",
 "\n{'code': 'mean = arr1.median()', 'lang': 'python'}",
 "\n{'code': 'import numpy as np\\nmean = np.median(arr1, axis=0)', 'lang': 'python'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1, axis=0, keepdims=False)\\nmean = np.mean(mean, axis=1, keepdims=False)', 'explanation': 'This code is similar to the original code, but it has been refactored to use a single `mean` function call.', 'level': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1, axis=0)\\nmean = np.mean(mean, axis=1)', 'explanation': 'This code is similar to the original code, but it has been refactored to use a single `mean` function call.', 'level': 'intermediate'}",
 "\n{'code': 'import numpy as np\\nmean = np.sum(arr1, axis=0) / len(arr1)\\nmean = np.sum(mean, axis=1) / len(mean)', 'explanation': 'This code is similar to the original code, but it has been refactored to use multiple `sum` and `len` function calls.', 'level': 'beginner'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'explanation': 'This code is the same as the original code.', 'level': 'beginner'}",
 "\n{'code': 'import numpy as np\\nmean = np.sum(arr1)/len(arr1)'}",
 "\n{'code': '\\ndef mean(arr):\\n    sum = 0\\n    length = len(arr)\\n    for i in range(length):\\n        sum += arr[i]\\n    return sum/length\\n\\nmean = mean(arr1)\\n'}",
 "\n{'code': '\\nimport statistics\\n\\nmean = statistics.mean(arr1)\\n'}",
 "\n{'code': '\\ndef mean(arr):\\n    length = len(arr)\\n    sum = 0\\n    for i in range(length):\\n        sum += arr[i]\\n    return sum / length\\n\\nmean = mean(arr1)\\n'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'explanation': 'Use numpy.mean() to calculate the mean.', 'level': 'expert'}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)', 'explanation': 'Use statistics.mean() to calculate the mean.', 'level': 'intermediate'}",
 "\n{'code': 'sum = 0\\nfor i in range(len(arr1)):\\n    sum += arr1[i]\\nmean = sum / len(arr1)', 'explanation': 'Calculate the sum of all elements in arr1. Then divide the sum by the length of arr1 to get the mean.', 'level': 'beginner'}",
 "\n{'code': 'def calc_mean(arr):\\n  return np.mean(arr)\\nmean = calc_mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = sum(arr1) / len(arr1)', 'level': 'expert'}",
 "\n{'code': 'mean = sum(arr1)/len(arr1)', 'type': 'intermediate'}",
 "\n{'code': 'def mean(arr): return sum(arr)/len(arr)\\nmean = mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'level': 'beginner', 'explanation': 'Import the numpy library and use the mean function to calculate the mean of arr1'}",
 "\n{'code': 'from statistics import mean\\nmean = mean(arr1)', 'level': 'intermediate', 'explanation': 'Import the statistics library and use the mean function to calculate the mean of arr1'}",
 "\n{'code': 'import numpy as np\\nmean = np.sum(arr1) / len(arr1)', 'level': 'expert', 'explanation': 'Calculate the mean of arr1 by summing all elements and dividing by the length of the array'}",
 "\n{'code': 'import numpy as np\\nmean = np.mean(arr1)', 'type': 'expert'}",
 "\n{'code': 'mean = (arr1[0] + arr1[1] + arr1[2] + arr1[3]) / 4', 'type': 'intermediate'}",
 "\n{'code': 'sum = 0\\nfor i in range(4):\\n    sum += arr1[i]\\nmean = sum / 4', 'type': 'beginner'}",
 "\n{'code': 'sum = 0\\nfor i in range(4):\\n    sum += arr1[i]\\nmean = round(sum / 4, 3)', 'type': 'intermediate'}",
 "\n{'code': 'count = 0\\nfor value in arr1:\\n    count += value\\nmean = count / len(arr1)', 'type': 'beginner'}"
]