KeyError，熊猫在做奇怪的事情

Question

关于这个错误，我已经找了好几天了，没有任何改进。似乎熊猫在重复数据，然后再重复一次。但是，当键在特定的迭代中迭代时，就会引发KeyError。可能是解释器出了问题，还是我的代码出错了？如有任何帮助，我们将不胜感激。

更多上下文：

https://www.transfernow.net/3yS7pE092020的

• 子集

传递给函数的

• 参数:将通过dataset

搜索的ID的np.array (dtype=int)

这里有代码：

def extract_features(id_arr):
features_df = pd.read_csv(r'D:\fma_metadata\features.csv', index_col=0, na_values=['NA'], encoding='utf-8')
features = np.array(features_df.columns)
id_arr = np.asarray(id_arr, dtype=int)

for id in id_arr:
    row_features = []

    for key, value in features_df.iteritems():
        number = float(features_df[key][id])
        row_features.append(round(number, 6))

    row_features = np.asarray(row_features)
    features = np.vstack((features, row_features))

features = np.delete(features, 0, 0)

return features


random_id = get_random_id()

extract_features(random_id)

错误：

  Traceback (most recent call last):
  File "C:/Users/*****/PycharmProjects/****/emotions-nn/deep-learning/input.py", line 65, in <module>
    print(extract_features(random_id))
  File "C:/Users/*****/PycharmProjects/****/emotions-nn/deep-learning/input.py", line 51, in extract_features
    number = float(features_df[key][id])
  File "C:\Users\*****\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\series.py", line 882, in __getitem__
    return self._get_value(key)
  File "C:\Users\*****\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\series.py", line 991, in _get_value
    loc = self.index.get_loc(label)
  File "C:\Users\*****\anaconda3\envs\tensorflow\lib\site-packages\pandas\core\indexes\base.py", line 2891, in get_loc
    raise KeyError(key) from err
KeyError: 800

Answer 1

我猜这可能是你的多层次索引。

# ids can be a list of integers too
def extract(ids: np.ndarray):
    # assuming the first 3 rows are "headers"
    df = pd.read_csv(r"C:\Users\danie\Downloads\features - subset.csv", header=[0,1,2], index_col=0, na_values=['NA'])

    # you can set a breakpoint here to see the current column order
    # print(df.columns)
    # and reorganize the way you want it

    # this is basically what you're trying to do if I'm not mistaken
    return df.loc[ids].round(6).to_numpy()

    # if there's a column order
    return df.loc[ids, order].round(6).to_numpy()