将Casout SAS表提取到熊猫数据框

时间:2020-02-11 14:40:17

标签: sas

我正在使用SAS的python API,并通过以下方式上传了表格:

s.upload("./data/hmeq.csv", casout=dict(name=tbl_name, replace=True))

我可以按s.tableinfo()查看该表的详细信息。

§ TableInfo
    Name    Rows    Columns IndexedColumns  Encoding    CreateTimeFormatted ModTimeFormatted    AccessTimeFormatted JavaCharSet CreateTime  ... Repeated    View    MultiPart   SourceName  SourceCaslib    Compressed  Creator Modifier    SourceModTimeFormatted  SourceModTime
0   HMEQ    5960    13  0   utf-8   2020-02-10T16:48:02-05:00   2020-02-10T16:48:02-05:00   2020-02-10T21:10:34-05:00   UTF8    1.896990e+09    ... 0   0   0           0   aforoo      2020-02-10T16:48:02-05:00   1.896990e+09
1 rows × 23 columns

但是,我无法在python中访问表的任何值。例如,假设我要获取行数和列数作为python标量。我知道我可以使用pandas将SAS表放入pd.DataFrame表中,但是它不适用于该表,并且得到:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
    346                                  dtype=dtype, copy=copy)
    347         elif isinstance(data, dict):
--> 348             mgr = self._init_dict(data, index, columns, dtype=dtype)
    349         elif isinstance(data, ma.MaskedArray):
    350             import numpy.ma.mrecords as mrecords

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in _init_dict(self, data, index, columns, dtype)
    457             arrays = [data[k] for k in keys]
    458 
--> 459         return _arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
    460 
    461     def _init_ndarray(self, values, index, columns, dtype=None, copy=False):

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in _arrays_to_mgr(arrays, arr_names, index, columns, dtype)
   7354     # figure out the index, if necessary
   7355     if index is None:
-> 7356         index = extract_index(arrays)
   7357 
   7358     # don't force copy because getting jammed in an ndarray anyway

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in extract_index(data)
   7391 
   7392         if not indexes and not raw_lengths:
-> 7393             raise ValueError('If using all scalar values, you must pass'
   7394                              ' an index')
   7395 

ValueError: If using all scalar values, you must pass an index

我在SAS中的任何其他casout表中都遇到相同的问题。感谢您的帮助或评论。

2 个答案:

答案 0 :(得分:1)

我在下面找到了解决方案,并且工作正常。例如,在这里我使用了dataSciencePilot.exploreData操作,可以通过以下方式获得结果:

casout = dict(name = 'out1', replace=True)
s.dataSciencePilot.exploreData(table=tbl_name, target='bad', casout=casout)
fetch_opts = dict(maxrows=100000000, to=1000000)
df = s.fetch(table='out1', **fetch_opts)['Fetch']
features = pd.DataFrame(df)
type(features)

返回pandas.core.frame.DataFrame

答案 1 :(得分:0)

我建议您直接使用熊猫来读取SAS。

另一个答案的参考:Read SAS file with pandas

这是另一个例子 https://www.marsja.se/how-to-read-sas-files-in-python-with-pandas/

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