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type-error.json
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type-error.json
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[
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n d[i] = [function(i)]\n d[i].extend((function(i) for _ in range(array.count(i) - 1)))",
"array = [1, 2, 3, 1, 2, 3]\nd = {}\nfor i in set(array):\n d[i] = [function(i)]\n for _ in range(array.count(i) - 1):\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"array = [1, 2, 3, 1, 2, 3]\nkeys = set(array)\nd = {}\nfor key in keys:\n d[key] = [function(key)]\n for num in range(array.count(key) - 1):\n d[key].append(function(key))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n d.setdefault(i, []).append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {i: [] for i in array}\nfor i in array:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n d[i] = [function(i)]\n for _ in range(array.count(i) - 1):\n d[i].extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n d[i] = []\n for _ in range(array.count(i)):\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n d[i] = [function(i)]\n for _ in range(array.count(i)):\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n count = array.count(i)\n d[i] = [function(i)] * count\n if count > 1:\n d[i].extend([function(i) for _ in range(count - 1)])",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {i: [function(i)] * array.count(i) for i in unique_values}",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n count = array.count(i)\n d[i] = [function(i)]\n d[i].extend((function(i) for _ in range(count - 1)))",
"import numpy as np\nfrom collections import defaultdict\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = defaultdict(list)\nfor i in unique_values:\n d[i].extend((function(i) for _ in range(array.count(i))))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nunique_values = np.unique(array)\nd = {i: [] for i in unique_values}\nfor i in unique_values:\n count = array.count(i)\n d[i].extend([function(i)] * count)",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = [function(i)]\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nd = {i: [function(i)] for i in array}",
"import numpy as np\narray = [1, 2, 3, 1, 2, 3]\nd = {i: [] for i in array}\nfor i in array:\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(i)",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(i ** 2)",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(2 * i)",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor i in range(len(array)):\n d[array[i]].append(function(array[i]))",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nd = collections.defaultdict(list)\nfor (i, value) in enumerate(array):\n d[array[i]].append(function(array[i]))",
"from collections import defaultdict\narray = [1, 2, 3, 1, 2, 3]\nd = defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"array = [1, 2, 3, 1, 2, 3]\nkeys = list(set(array))\nd = {}\nfor key in keys:\n count = array.count(key)\n d[key] = [function(key)]\n for num in range(count - 1):\n d[key].append(function(key))",
"import collections\narray = [1, 2, 3, 1, 2, 3]\nkeys = collections.Counter(array)\nd = {}\nfor key in keys:\n count = keys[key]\n d[key] = [function(key)]\n for num in range(count - 1):\n d[key].append(function(key))",
"import collections\nfrom typing import List\ndef variation_of_original_code(array: List) -> collections.defaultdict:\n d = collections.defaultdict(list)\n for i in array:\n d[i].append(function(i))\n return d",
"import collections\nfrom typing import List\ndef variation_of_original_code(array: List) -> collections.defaultdict:\n d = collections.defaultdict(list)\n for i in range(len(array)):\n d[array[i]].append(function(array[i]))\n return d",
"from collections import defaultdict\ndef variation_of_original_code(array):\n d = defaultdict(list)\n for i in array:\n d[i].append(function(i))\n return d",
"from collections import defaultdict\ndef variation_of_original_code(array):\n d = defaultdict(list)\n for i in range(len(array)):\n d[array[i]].append(function(array[i]))\n return d",
"from collections import defaultdict\ndef variation_of_original_code(array):\n d = defaultdict(list)\n for (i, val) in enumerate(array):\n d[val].append(function(val))\n return d",
"array = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if not d.get(i):\n d[i] = []\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 4, 5]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in range(len(array)):\n if array[i] in d:\n d[array[i]].append(function(array[i]))\n else:\n d[array[i]] = [function(array[i])]",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in range(len(array)):\n num = array[i]\n if num in d:\n d[num].append(function(num))\n else:\n d[num] = [function(num)]",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in range(len(array)):\n num = array[i]\n if num in d.keys():\n d[num].append(function(num))\n else:\n d[num] = [function(num)]",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = [function(i)]\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {i: [function(i)] for i in array}\nfor i in array:\n if i in d:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].append(function(i))\n d[i].sort()",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]\n d[i].sort()",
"import math\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if math.cos(i) not in d:\n d[math.cos(i)] = []\n d[math.cos(i)].append(function(i))",
"import math\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].append(function(i))\n d[i].sort()\nd = dict(sorted(d.items()))",
"import itertools\narray = [1, 2, 3, 4, 5]\nd = dict.fromkeys(array, [])\nfor i in array:\n d[i].append(function(i))",
"import itertools\narray = [1, 2, 3, 4, 5]\nd = dict.fromkeys(array, [])\nfor i in itertools.permutations(array):\n d[i[0]].append(function(i[0]))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {i: [function(i)] for i in array}",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {i: [function(i)] for i in np.unique(array)}",
"import numpy as np\narray = np.array([1, 2, 3, 4, 5])\nd = {i: [function(i)] for i in np.unique(array)}",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d.keys():\n d.update({i: []})\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\n\ndef append_to_dict(dictionary, key, value):\n if key not in dictionary.keys():\n dictionary[key] = []\n dictionary[key].append(value)\nfor i in array:\n append_to_dict(d, i, function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\n\ndef check_and_append(dictionary, key, value):\n if key not in dictionary:\n dictionary[key] = []\n dictionary[key].append(value)\nfor i in array:\n check_and_append(d, i, function(i))",
"import pandas as pd\ndata = {'array': array, 'function': function}\ndf = pd.DataFrame(data)\ndf['d'] = df.groupby('array')['function'].transform(lambda x: list(x))\nd = df.drop_duplicates('array')[['array', 'd']].set_index('array').to_dict()['d']",
"from collections import Counter\nimport itertools\narray_counts = Counter(array)\nd = {i: [function(i)] * array_counts[i] for i in itertools.chain(array_counts)}",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = [function(i)]",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.unique(array)}",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.ndenumerate(array):\n if i[1] in d:\n d[i[1]].append(function(i[1]))\n else:\n d[i[1]] = [function(i[1])]",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.nditer(array):\n if i.item() in d:\n d[i.item()].append(function(i.item()))\n else:\n d[i.item()] = [function(i.item())]",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = list(map(function, array[array == i]))",
"import pandas as pd\narray = pd.Series(array)\nd = array.groupby(array).apply(lambda x: list(map(function, x))).to_dict()",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.nditer(array) if i % 2 == 0}",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.nditer(array) if i % 2 == 0 and i > 0}",
"d = {}\nfor i in array:\n if i not in d:\n d[i] = []\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\n(unique_values, counts) = np.unique(array, return_counts=True)\nd = dict(zip(unique_values, [function(i) for i in unique_values]))",
"d = {}\narray = [1, 2, 3, 4, 5]\nfor i in array:\n d[i] = [function(i)] if i not in d else d[i] + [function(i)]",
"from collections import defaultdict\nd = {}\narray = [1, 2, 3, 4, 5]\nd = defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"d = {}\narray = [1, 2, 3, 4, 5]\nfor i in array:\n d.setdefault(i, []).append(function(i))",
"d = {}\narray = [1, 2, 3, 4, 5]\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import numpy as np\narray = np.array(array)\nd = dict(zip(np.unique(array), [[function(i)] for i in np.unique(array)]))",
"import numpy as np\narray = np.array(array)\nd = {}\nunique_values = np.unique(array)\nfor i in unique_values:\n d[i] = [function(i)]",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = [function(i)]\ni = i\nd = d",
"import numpy as np\narray = np.array(array)\nd = dict.fromkeys(np.unique(array), [])\nfor i in np.unique(array):\n d[i].append(function(i))",
"import numpy as np\narray = np.array(array)\nunique_values = np.unique(array)\nd = {i: [function(i)] for i in unique_values}",
"import numpy as np\narray = np.array(array)\nunique_values = np.unique(array)\nd = {}\nfor i in unique_values:\n d[i] = [function(i)]",
"from collections import defaultdict\narray = [1, 2, 3, 4, 5]\nd = defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 4, 5]\nd = collections.defaultdict(list)\nfor i in array:\n result = function(i)\n d[i].append(result)",
"from collections import defaultdict\narray = [1, 2, 3, 4, 5]\nd = defaultdict(list)\nfor i in array:\n result = function(i)\n d[i].append(result)",
"import collections\narray = [1, 2, 3, 4, 5]\nd = collections.defaultdict(list)\nfor i in array:\n result = function(i)\n if result:\n d[i].append(result)",
"from collections import defaultdict\narray = [1, 2, 3, 4, 5]\nd = defaultdict(list)\nfor i in array:\n result = function(i)\n if result:\n d[i].append(result)",
"import collections\ndef function(i):\n return i\narray = [1, 2, 3, 4, 5]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 4, 5]\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(i * i)",
"from collections import defaultdict\narray = [1, 2, 3, 4, 5]\nfunction = lambda x: x ** 2\nd = defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"import collections\narray = [1, 2, 3, 4, 5]\nfunction = lambda x: x ** 2\nd = collections.defaultdict(list)\nfor i in array:\n d[i].append(function(i))",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = list(function(array == i))",
"import pandas as pd\nd = {}\narray = pd.Series(array)\nfor i in array.unique():\n d[i] = list(array[array == i].apply(function))",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n else:\n d[i].append(function(i))",
"array = list(array)\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n else:\n d[i].append(function(i))",
"import pandas as pd\narray = pd.Series(array)\nd = array.groupby(array).apply(lambda x: [function(i) for i in x]).to_dict()",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i) for i in array[array == i]] for i in np.unique(array)}",
"array = list(array)\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n else:\n d[i].append(function(i))",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = dict()\nfor i in array:\n if i not in d.keys():\n d[i] = [function(i)]\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = dict()\nfor i in array:\n if i not in d:\n d[i] = [function(i)]\n else:\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = [function(i)]\n else:\n d.get(i).append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = dict()\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = dict()\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d.get(i).append(function(i))",
"import numpy as np\narray = np.array(array)\nfunction = np.vectorize(function)\nresult = function(array)\nunique_values = np.unique(array)\noutput = {}\nfor value in unique_values:\n output[value] = result[array == value].tolist()\noutput",
"import numpy as np\ndef get_value(i):\n return [function(i)]\nd = np.vectorize(get_value)(array)",
"import numpy as np\narray_unique = np.unique(array)\nd = {i: [function(i)] for i in array_unique}",
"import pandas as pd\narray_df = pd.DataFrame(array, columns=['value'])\narray_df['result'] = array_df['value'].apply(function)\nd = array_df.groupby('value')['result'].apply(list).to_dict()",
"import numpy as np\n(values, counts) = np.unique(array, return_counts=True)\nd = dict(zip(values, [[] for _ in range(len(values))]))\nfor (count, i) in zip(counts, values):\n d[i].append(function(i))",
"from collections import defaultdict\nd = defaultdict(list)\n\ndef function(i):\n return i\nfor i in array:\n d[i].append(function(i))",
"d = {}\n\ndef function(i):\n return i\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import itertools\nd = {}\n\ndef function(i):\n return i\nkey_func = lambda x: x\nfor i in array:\n key = key_func(i)\n if key in d:\n d[key].append(function(i))\n else:\n d[key] = [function(i)]",
"from collections import defaultdict\nd = defaultdict(list)\nfor i in set(array):\n d[i].extend((function(i) for i in array if i == d))",
"import pandas as pd\nd = pd.DataFrame(columns=['i', 'd'])\nfor i in array:\n d.loc[len(d)] = (i, function(i))",
"import pandas as pd\nd = pd.DataFrame(columns=['i', 'd'])\nd['i'] = array\nd['d'] = [function(i) for i in array]",
"import pandas as pd\nd = pd.DataFrame(columns=['i', 'd'])\ni = 0\nwhile i < len(array):\n d.loc[len(d)] = (array[i], function(array[i]))\n i += 1",
"import pandas as pd\ndef create_dataframe(array, function):\n d = pd.DataFrame(columns=['i', 'd'])\n for i in array:\n d = d.append({'i': i, 'd': function(i)}, ignore_index=True)\n return d",
"import numpy as np\nd = {i: [function(i)] for i in np.unique(array)}",
"d = {}\nfor i in set(array):\n d[i] = list(filter(lambda x: x == i, array))",
"d = {}\nfor i in set(array):\n d[i] = [j for j in array if j == i]",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array.unique():\n d[i] = [function(j) for j in array if j == i]",
"import numpy as np\narray = np.array(array)\nd = {i: array[array == i] for i in set(array)}",
"import pandas as pd\narray_unique = pd.Series(array).unique()\nfor i in array_unique:\n if i not in d:\n initialize_dict(i)\n else:\n d[i].append(function(i))",
"array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nd = {}\n\ndef initialize_dict(x):\n d[x] = [function(x)]\nfor i in array:\n if i not in d:\n initialize_dict(i)\n else:\n d[i].append(function(i))",
"array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\ninitial_dict = {}\n\ndef initialize_dict(x):\n if x not in initial_dict:\n initial_dict[x] = [function(x)]\n else:\n initial_dict[x].append(function(x))\nfor element in array:\n initialize_dict(element)\nd = initial_dict",
"from collections import defaultdict\narray = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nd = defaultdict(list)\nfor element in array:\n if element not in d:\n d[element].append(function(element))",
"array = [1, 2, 3, 1, 2, 3]\nd = {i: [function(i)] for i in set(array)}",
"array = [3, 2, 1, 1, 2, 3]\nd = {i: [] for i in array}\nfor i in array:\n d[i].append(function(i))",
"d = {}",
"import pandas as pd\ndf = pd.DataFrame(array, columns=['col'])\ndf['function'] = df['col'].apply(function)\nd = df.groupby('col')['function'].apply(list).to_dict()",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = array[array == i].tolist()\n d[i] = list(map(function, d[i]))",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array.unique():\n d[i] = array[array == i].tolist()\n d[i] = list(map(function, d[i]))",
"import numpy as np\narray = np.array(array)\nd = {}\nunique_values = np.unique(array)\nfor i in unique_values:\n d[i] = array[array == i].tolist()\n d[i] = list(map(function, d[i]))",
"import collections\narray_counter = collections.Counter(array)\nd = {}\nfor i in set(array):\n d[i] = array_counter[i]",
"import numpy as np\narray_counts = np.unique(array, return_counts=True)\nd = {}\nfor i in set(array):\n d[i] = array_counts[1][np.where(array_counts[0] == i)]",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.unique(array):\n d[i] = list(array[array == i])\n for j in array[array == i]:\n d[i].append(function(j))",
"import numpy as np\narray = np.arange(10)\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"array = [5, 5, 5, 5, 5]\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import numpy as np\narray = np.array([2, 4, 6, 8, 10])\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.unique(array) if i in array}",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.unique(array) if i in np.unique(array)}",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.unique(array) if i in np.unique(array) and i in array}",
"import numpy as np\narray = np.array(array)\nd = {i: [function(i)] for i in np.unique(array) if i in np.unique(array) and i in array and (i > 0)}",
"import numpy as np\narray = np.array(array)\nd = {}\nfor i in np.ndindex(array.shape):\n if array[i] in d:\n d[array[i]].append(function(array[i]))\n else:\n d[array[i]] = [function(array[i])]",
"import collections\narray = list(array)\nd = collections.defaultdict(list)\nfor i in range(len(array)):\n d[array[i]].append(function(i))",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in range(len(array)):\n if array[i] in d:\n d[array[i]].append(function(array[i]))\n else:\n d[array[i]] = [function(array[i])]",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array.values:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array.unique():\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]\nd = {k: sorted(v) for (k, v) in d.items()}",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]\nd = {k: v for (k, v) in sorted(d.items(), key=lambda item: item[0])}",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array:\n if i in d:\n d[i].append(function(i))\n else:\n d[i] = [function(i)]\nd = dict(sorted(d.items()))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d.get(i).append(function(i))",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n d[i] = d.get(i, []) + [function(i)]",
"array = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d[i].extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {i: [] for i in array}\nfor i in array:\n d[i].extend([function(i)])",
"array = [1, 2, 3, 4, 5]\nd = {i: [] for i in array}\nfor i in array:\n if i not in d:\n d[i] = []\n d[i].extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in set(array):\n d[i] = []\nfor i in array:\n d[i].extend([function(i)])",
"array = [1, 2, 3, 4, 5]\nd = {}\nfor i in set(array):\n d[i] = []\nfor i in array:\n if i in d:\n d[i].extend([function(i)])\n else:\n d[i] = [function(i)]",
"array = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n d.setdefault(i, []).extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d.get(i).extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d.get(i).extend([function(i)])",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d.get(i).extend([function(i)])\ni = 5\nd[i].append(10)",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d.get(i).extend([function(i)])\ni = 5\nd[i].append(10)\nd[3].append(20)",
"import numpy as np\narray = [1, 2, 3, 4, 5]\nd = {}\nfor i in array:\n if i not in d:\n d[i] = []\n d.get(i).extend([function(i)])\ni = 5\nd[i].append(10)\nd[3].append(20)\ni = 3",
"import pandas as pd\narray = pd.Series(array)\nd = {}\nfor i in array:\n if i not in d.keys():\n d[i] = []\n d.get(i).extend([function(i)])"
]