Python：json_normalize为dict值列表提供AttributeError

rsl1atfo 于 2023-04-13 发布在 Python

关注(0)|答案(2)|浏览(153)

我有一个pandas dataframe，其中2列是具有十进制值的嵌套列：df.tail(1).to_dict('list')给出了这种数据

{'nested_col1': [array([{'key1': 'CO', 'key2': Decimal('8.940000000')}],
  dtype=object)], 'nested_col2': [array([{'key3': 'CO', 'key4': 'P14', 'key5': Decimal('8.940000000'), 'key6': None}],
  dtype=object)]}

我试图用这个来分解 Dataframe ：

df = (df.drop(cols, axis=1)
        .join(pd.concat(
            [pd.json_normalize(df[x].explode(), errors='ignore').applymap(
                lambda x: str(x) if isinstance(x, (int, float)) else x).add_prefix(f'{x}.') for x in
             cols],
            axis=1)))

在某些情况下，我会出现以下错误：

Traceback (most recent call last):
  File "data_load.py.py", line 365, in <module>
    df = prepare_data(data, transaction_id, cohort_no)
  File "data_load.py.py", line 274, in prepare_data
    df = flatten_dataframe(cols_to_explode, df)
  File "data_load.py.py", line 204, in flatten_dataframe
    df1 = pd.concat([pd.json_normalize(df[c].explode()) for c in cols],
  File "data_load.py.py", line 204, in <listcomp>
    df1 = pd.concat([pd.json_normalize(df[c].explode()) for c in cols],
  File "/project1/venv/lib/python3.6/site-packages/pandas/io/json/_normalize.py", line 270, in _json_normalize
    if any([isinstance(x, dict) for x in y.values()] for y in data):
  File "/project1/venv/lib/python3.6/site-packages/pandas/io/json/_normalize.py", line 270, in <genexpr>
    if any([isinstance(x, dict) for x in y.values()] for y in data):
AttributeError: 'float' object has no attribute 'values'
failed to run commands: exit status 1

我还错过了什么或者有什么更好的方法来做同样的事情吗？
预期输出应为：

nested_col1.key1,nested_col1.key2 nested_col2.key3 ... like this

JSON

来源：https://stackoverflow.com/questions/75977435/python-json-normalize-gives-attributeerror-for-list-of-dict-values

2条答案

按热度按时间

nxowjjhe1#

似乎每个嵌套列只有一个元素：

out = pd.concat([pd.json_normalize(df[x][0]).add_prefix(f'{x}.') 
                     for x in cols], axis=1)
out = out.apply(pd.to_numeric, errors='coerce').fillna(out)
print(out)

# Output
  nested_col1.key1  nested_col1.key2 nested_col2.key3 nested_col2.key4  nested_col2.key5 nested_col2.key6
0               CO              8.94               CO              P14              8.94             None

注意：如果每个嵌套列表中有多条记录，则可以将[0]替换为.explode()。

赞(0）回复(0）举报 2023-04-13

wgxvkvu92#

可以使用json_normalize和concat：

cols = ['nested_col1', 'nested_col2']

out = pd.concat([pd.json_normalize(df[c].explode()) for c in cols],
                keys=cols, axis=1)
out.columns = out.columns.map('.'.join)

输出：

nested_col1.key1 nested_col1.key2 nested_col2.key3 nested_col2.key4 nested_col2.key5 nested_col2.key6
0               CO      8.940000000               CO              P14      8.940000000             None

赞(0）回复(0）举报 2023-04-13

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Python：json_normalize为dict值列表提供AttributeError

2条答案

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