スタック解除データフレームのみ

Question

私がデータフレーム以下います

data = {'year': [2010, 2010, 2011, 2012, 2011, 2012, 2010, 2011, 2012, 2013], 
      'store_number': ['1944', '1945', '1946', '1947', '1948', '1949', '1947', '1948', '1949', '1947'], 
      'retailer_name': ['Walmart','Walmart', 'CRV', 'CRV', 'CRV', 'Walmart', 'Walmart', 'CRV', 'CRV', 'CRV'], 
      'product': ['a', 'b', 'a', 'a', 'b', 'a', 'b', 'a', 'a', 'c'], 
      'amount': [5, 5, 8, 6, 1, 5, 10, 6, 12, 11], 
      'vat': [0.5, 0.5, 0.8, 0.6, 0.1, 0.5, 0.10, 0.6, 0.12, 0.11]} 

    stores = pd.DataFrame(data, columns=['retailer_name', 'store_number', 'year', 'product', 'amount', 'vat']) 
    stores.set_index(['retailer_name', 'store_number', 'year', 'product'], inplace=True) 
    df = stores.groupby(level=[0, 1, 2, 3]).sum().unstack('product') 
    mask = pd.IndexSlice['amount', :] 
    df.loc[:, mask] = df.loc[:, mask].fillna(0) 

そして、私は出力以下の取得：私は私の最終的な結果では、これらのvatの列を必要といけない

       amount   vat   
product        a b c  a b  c 
retailer_name store_number year         
CRV   1946   2011  8 0 0 0.80 NaN NaN 
       1947   2012  6 0 0 0.60 NaN NaN 
          2013  0 0 11 NaN NaN 0.11 
       1948   2011  6 1 0 0.60 0.1 NaN 
       1949   2012  12 0 0 0.12 NaN NaN 
Walmart  1944   2010  5 0 0 0.50 NaN NaN 
       1945   2010  0 5 0 NaN 0.5 NaN 
       1947   2010  0 10 0 NaN 0.1 NaN 
       1949   2012  5 0 0 0.50 NaN NaN 

を、私はそれらを削除する方法私のunstack ing？私にとって

Answer 1

は動作します：

df = stores.groupby(level=[0, 1, 2, 3]).sum().unstack('product') 

df = df['amount'].fillna(0) 
print (df) 
product        a  b  c 
retailer_name store_number year     
CRV   1946   2011 8.0 0.0 0.0 
       1947   2012 6.0 0.0 0.0 
          2013 0.0 0.0 11.0 
       1948   2011 6.0 1.0 0.0 
       1949   2012 12.0 0.0 0.0 
Walmart  1944   2010 5.0 0.0 0.0 
       1945   2010 0.0 5.0 0.0 
       1947   2010 0.0 10.0 0.0 
       1949   2012 5.0 0.0 0.0 

をすべて一緒：

df = stores.groupby(level=[0, 1, 2, 3]).sum().unstack('product')['amount'].fillna(0) 
print (df) 

product        a  b  c 
retailer_name store_number year     
CRV   1946   2011 8.0 0.0 0.0 
       1947   2012 6.0 0.0 0.0 
          2013 0.0 0.0 11.0 
       1948   2011 6.0 1.0 0.0 
       1949   2012 12.0 0.0 0.0 
Walmart  1944   2010 5.0 0.0 0.0 
       1945   2010 0.0 5.0 0.0 
       1947   2010 0.0 10.0 0.0 
       1949   2012 5.0 0.0 0.0 

別の解決策は、sumための選択欄amount次のとおりです。

df = stores.groupby(level=[0, 1, 2, 3])['amount'].sum().unstack('product').fillna(0) 
print (df) 
product        a  b  c 
retailer_name store_number year     
CRV   1946   2011 8.0 0.0 0.0 
       1947   2012 6.0 0.0 0.0 
          2013 0.0 0.0 11.0 
       1948   2011 6.0 1.0 0.0 
       1949   2012 12.0 0.0 0.0 
Walmart  1944   2010 5.0 0.0 0.0 
       1945   2010 0.0 5.0 0.0 
       1947   2010 0.0 10.0 0.0 
       1949   2012 5.0 0.0 0.0