pandas 中 to_dict 的用法

DataFrame.to_dict(orient='dict', into=<class 'dict'>)

参数:

orient  : str {‘dict’, ‘list’, ‘series’, ‘split’, ‘records’, ‘index’}   ‘dict’ (default) : {column -> {index -> value}} ‘list’ :  {column -> [values]} ‘series’ : {column -> Series(values)} ‘split’ : {‘index’ -> [index], ‘columns’ -> [columns], ‘data’ -> [values]} ‘records’ : [{column -> value}, … , {column -> value}] ‘index’ : {index -> {column -> value}} 也可以用缩写表示，  s 代表 series ，sp 代表 split. into  : class, 默认dict

Returns:

dict, list 或 collections.Mapping

 

例子：

>>> df = pd.DataFrame({'col1': [1, 2], ... 'col2': [0.5, 0.75]}, ... index=['row1', 'row2']) >>> df  col1 col2 row1 1 0.50 row2 2 0.75 >>> df.to_dict() {'col1': {'row1': 1, 'row2': 2}, 'col2': {'row1': 0.5, 'row2': 0.75}}

可以指定返回的类型

>>> df.to_dict('series') {'col1': row1 1  row2 2 Name: col1, dtype: int64, 'col2': row1 0.50  row2 0.75 Name: col2, dtype: float64} 

>>> df.to_dict('split') {'index': ['row1', 'row2'], 'columns': ['col1', 'col2'],  'data': [[1, 0.5], [2, 0.75]]} 

>>> df.to_dict('records') [{'col1': 1, 'col2': 0.5}, {'col1': 2, 'col2': 0.75}] 

>>> df.to_dict('index') {'row1': {'col1': 1, 'col2': 0.5}, 'row2': {'col1': 2, 'col2': 0.75}} 

>>> from collections import OrderedDict, defaultdict >>> df.to_dict(into=OrderedDict) OrderedDict([('col1', OrderedDict([('row1', 1), ('row2', 2)])),  ('col2', OrderedDict([('row1', 0.5), ('row2', 0.75)]))]) 

If you want a defaultdict, you need to initialize it:

>>> dd = defaultdict(list) >>> df.to_dict('records', into=dd) [defaultdict(<class 'list'>, {'col1': 1, 'col2': 0.5}),  defaultdict(<class 'list'>, {'col1': 2, 'col2': 0.75})]