Question

这是我的数据：

            cmte_id   trans   entity    st  amount    fec_id
date                        
2007-08-15  C00112250   24K     ORG     DC  2000    C00431569
2007-09-26  C00119040   24K     CCM     FL  1000    C00367680
2007-09-26  C00119040   24K     CCM     MD  1000    C00140715
2007-07-20  C00346296   24K     CCM     CA  1000    C00434571
2007-09-24  C00346296   24K     CCM     MA  1000    C00433136

为简洁起见，我遗漏了其他描述性专栏。我想对其进行转换，以使[cmte_id]中的值成为列标题，[amount]中的值成为新列中的相应值。我知道这可能是一个简单的枢轴操作。我尝试过以下方法：

dfy.pivot('cmte_id', 'amount')
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-203-e5d2cb89e880> in <module>()
----> 1 dfy.pivot('cmte_id', 'amount')

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/frame.py in pivot(self, index, columns, values)
   3761         """
   3762         from pandas.core.reshape import pivot
-> 3763         return pivot(self, index=index, columns=columns, values=values)
   3764 
   3765     def stack(self, level=-1, dropna=True):

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/reshape.py in pivot(self, index, columns, values)
    323         append = index is None
    324         indexed = self.set_index(cols, append=append)
--> 325         return indexed.unstack(columns)
    326     else:
    327         if index is None:

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/frame.py in unstack(self, level)
   3857         """
   3858         from pandas.core.reshape import unstack
-> 3859         return unstack(self, level)
   3860 
   3861     #----------------------------------------------------------------------

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/reshape.py in unstack(obj, level)
    402     if isinstance(obj, DataFrame):
    403         if isinstance(obj.index, MultiIndex):
--> 404             return _unstack_frame(obj, level)
    405         else:
    406             return obj.T.stack(dropna=False)

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/reshape.py in _unstack_frame(obj, level)
    442     else:
    443         unstacker = _Unstacker(obj.values, obj.index, level=level,
--> 444                                value_columns=obj.columns)
    445         return unstacker.get_result()
    446 

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/reshape.py in __init__(self, values, index, level, value_columns)
     96 
     97         self._make_sorted_values_labels()
---> 98         self._make_selectors()
     99 
    100     def _make_sorted_values_labels(self):

/home/jayaramdas/anaconda3/lib/python3.5/site-packages/pandas/core/reshape.py in _make_selectors(self)
    134 
    135         if mask.sum() < len(self.index):
--> 136             raise ValueError('Index contains duplicate entries, '
    137                              'cannot reshape')
    138 

ValueError: Index contains duplicate entries, cannot reshape

所需的最终结果（除了附加列，例如'trans'，fec_id，'st'等）看起来像这样：

    date    C00112250   C00119040   C00119040   C00346296   C00346296
2007-ago-15 2000                
2007-set-26             1000            
2007-set-26                           1000      
2007-lug-20                                        1000 
2007-set-24                                                    1000

有没有人知道如何更接近最终产品？

Answer 1

试试这个：

pvt = pd.pivot_table(df, index=df.index, columns='cmte_id',
                     values='amount', aggfunc='sum', fill_value=0)

保留其他列：

In [213]: pvt = pd.pivot_table(df.reset_index(), index=['index','trans','entity','st', 'fec_id'],
   .....:                      columns='cmte_id', values='amount', aggfunc='sum', fill_value=0) \
   .....:         .reset_index()

In [214]: pvt
Out[214]:
cmte_id       index trans entity  st     fec_id  C00112250  C00119040  \
0        2007-07-20   24K    CCM  CA  C00434571          0          0
1        2007-08-15   24K    ORG  DC  C00431569       2000          0
2        2007-09-24   24K    CCM  MA  C00433136          0          0
3        2007-09-26   24K    CCM  FL  C00367680          0       1000
4        2007-09-26   24K    CCM  MD  C00140715          0       1000

cmte_id  C00346296
0             1000
1                0
2             1000
3                0
4                0

In [215]: pvt.head()['st']
Out[215]:
0    CA
1    DC
2    MA
3    FL
4    MD
Name: st, dtype: object

<强>更新

import pandas as pd
import glob


# if you don't use ['cand_id'] column - remove it from `usecols` parameter
dfy = pd.concat([pd.read_csv(f, sep='|', low_memory=False, header=None,
                             names=['cmte_id', '2', '3', '4','5', 'trans_typ', 'entity_typ', '8', '9', 'state', '11', 'employer', 'occupation', 'date', 'amount', 'fec_id', 'cand_id', '18', '19', '20', '21', '22'],
                             usecols= ['date', 'cmte_id', 'trans_typ', 'entity_typ', 'state', 'amount', 'fec_id', 'cand_id'],
                             dtype={'date': str})
                 for f in glob.glob('/home/jayaramdas/anaconda3/Thesis/FEC_data/itpas2_data/itpas2**.txt')
                ],
                ignore_index=True) 

dfy['date'] = pd.to_datetime(dfy['date'], format='%m%d%Y')

# remove not needed column ASAP in order to save memory
del dfy['cand_id']

dfy = dfy[(dfy['date'].notnull()) & (dfy['date'] > '2007-01-01') & (dfy['date'] < '2014-12-31') ]

#df = dfy.set_index(['date'])

pvt = pd.pivot_table(dfy, index=['date','trans_typ','entity_typ','state','fec_id'],
                     columns='cmte_id', values='amount', aggfunc='sum', fill_value=0) \
        .reset_index()


print(pvt.info())

pvt.to_excel('out.xlsx', index=False)

熊猫：在多列df中转置一列

1 个答案: