Pandas dataframe

pandas dataframe conversion

dict

dict -> dataframe

d1 = {"columns":["Apple","Pear"],"data":[[12,0], [8,7], [1, 9]]} df2 = pd.DataFrame(d1['data'])

  Apple  Pear

0 12 0 1 8 7 2 1 9

df2.columns=d1['columns'] Index(['Apple', 'Pear'], dtype='object')

dataframe -> dict

Syntax: DataFrame.to_dict(orient=’dict’, into=)\\

Parameters:

 * orient: String value, (‘dict’, ‘list’, ‘series’, ‘split’, ‘records’, ‘index’) Defines which dtype to convert Columns(series into). For example, ‘list’ would return a dictionary of lists with Key=Column name and Value=List (Converted series).
 * into: class, can pass an actual class or instance. For example in case of defaultdict instance of class can be passed. Default value of this parameter is dict.

Example

... df2.to_dict('split') {'index': [0, 1, 2], 'columns': ['Apple', 'Pear'], 'data': [[12, 0], [8, 7], [1, 9]]}

df2.to_dict('records') [{'Apple': 12, 'Pear': 0}, {'Apple': 8, 'Pear': 7}, {'Apple': 1, 'Pear': 9}]

list

list -> dataframe

　　See also: dict -> dataframe

dataframe -> list

   a1 = df1.values    # values方法将dataframe转为numpy.ndarray
   l1 = a1.tolist()
   l1[0]              # get frist value
   usys.utime(l1[0][7].value/10**9) 
 * P.S. 日期型的字段转换后格式：Timestamp('2017-04-13 13:48:32')，pandas._libs.tslibs.timestamps.Timestamp. 可以使用 usys.utime(l1[0][7].value/10**9) 转换。