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问题描述
我有一个类似于以下内容的数据集:
I have a dataset similar to the following:
df_lenght = 240
df = pd.DataFrame(np.random.randn(df_lenght,2), columns=['a','b'] )
df['datetime'] = pd.date_range('23/06/2017', periods=df_lenght, freq='H')
unique_jobs = ['job1','job2','job3',]
job_id = [unique_jobs for i in range (1, int((df_lenght/len(unique_jobs))+1) ,1) ]
df['job_id'] = sorted( [val for sublist in job_id for val in sublist] )
df.set_index(['job_id','datetime'], append=True, inplace=True)
print(df[:5])
返回:
a b
job_id datetime
0 job1 2017-06-23 00:00:00 -0.067011 -0.516382
1 job1 2017-06-23 01:00:00 -0.174199 0.068693
2 job1 2017-06-23 02:00:00 -1.227568 -0.103878
3 job1 2017-06-23 03:00:00 -0.847565 -0.345161
4 job1 2017-06-23 04:00:00 0.028852 3.111738
如何创建多个dataframes
,每个job_id
值一个?那些输入字典的内容是否易于检索?谢谢
How can I create multiple dataframes
, one for each value of job_id
? Can those fed into a dictionary to be easy retrieved?Thanks
推荐答案
您可以将groupby
对象解压缩成字典:
You could unpack a groupby
object into a dictionary:
dfs = {job: df for job, df in df.groupby(level='job_id')}
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