将 lambda 函数应用于 pandas 数据帧时出现键盘错误

Question

我正在 pandas 数据帧上应用 K 均值聚类。聚类分配函数如下：

def assign_to_cluster(row):
    lowest_distance = -1
    closest_cluster = -1

    for cluster_id, centroid in centroids_dict.items():
        df_row = [row['PPG'],row['ATR']]
        euclidean_distance = calculate_distance(centroids, df_row)

        if lowest_distance == -1:
            lowest_distance = euclidean_distance
            closest_cluster = cluster_id
        elif euclidean_distance < lowest_distance:
            lowest_distance = euclidean_distance
            closest_cluster = cluster_id
    return closest_cluster

point_guards['CLUSTER'] = point_guards.apply(lambda row: assign_to_cluster(row), axis=1)

但是我在使用 lambda 函数时遇到以下错误:

   1945                 return self._engine.get_loc(key)
   1946             except KeyError:
-> 1947                 return         self._engine.get_loc(self._maybe_cast_indexer(key))
   1948 
   1949         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item     (pandas\hashtable.c:12368)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)()

KeyError: (0, 'occurred at index 0')

谁能解释一下错误的原因以及我该如何解决？如果您需要更多信息，请回复此 post。并为格式道歉。这是我第一次在 Whosebug 提问。

Answer 1

原来我犯了一个简单的语法错误。而不是在调用函数 'calculate_distance':

时使用字典 'centroid_dict.items()' 的 'centroid' 部分

for cluster_id, centroid in centroids_dict.items():
    df_row = [row['PPG'],row['ATR']]
    euclidean_distance = calculate_distance(centroid, df_row)
....

我用 'centroids' 代替：

for cluster_id, centroid in centroids_dict.items():
    df_row = [row['PPG'],row['ATR']]
    euclidean_distance = calculate_distance(centroids, df_row)

不过现在已经解决了

将 lambda 函数应用于 pandas 数据帧时出现键盘错误

Keyerror occuring while applying lambda function to pandas dataframe

python

lambda

k-means

pandas

index-error