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Question

dfを複数の列内の1つの列を転置これは私が持っているデータがある：

  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 

私は簡潔にするために取り残されている他の記述の列があります。 [cmte_id]の値が列ヘッダーになり、[amount]の値が新しい列のそれぞれの値になるように変換したいと思います。私はこれがおそらく単純なピボット操作であることを知っています。このようになります（追加の列、例えば 'トランス'、fec_id、 'ST' などを除いて）

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 

所望の最終結果：私は次のことを試してみました

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 

んどのように私は最終製品に近づくことができるのか考えている人はいますか？

Answer 1

これを試してみてください：

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 

がUPDATE：

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

他の列の保全

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)