concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False, 
    keys=None, levels=None, names=None, verify_integrity=False, copy=True): 

df1=DataFrame(np.random.randn(3,4),columns=['a','b','c','d']) 
 
df2=DataFrame(np.random.randn(2,3),columns=['b','d','a']) 
 
pd.concat([df1,df2]) 
 
     a     b     c     d 
0 -0.848557 -1.163877 -0.306148 -1.163944 
1 1.358759 1.159369 -0.532110 2.183934 
2 0.532117 0.788350 0.703752 -2.620643 
0 -0.316156 -0.707832    NaN -0.416589 
1 0.406830 1.345932    NaN -1.874817 
 
pd.concat([df1,df2],ignore_index=True) 
 
     a     b     c     d 
0 -0.848557 -1.163877 -0.306148 -1.163944 
1 1.358759 1.159369 -0.532110 2.183934 
2 0.532117 0.788350 0.703752 -2.620643 
3 -0.316156 -0.707832    NaN -0.416589 
4 0.406830 1.345932    NaN -1.874817 

merge(left, right, how='inner', on=None, left_on=None, right_on=None, 
left_index=False, right_index=False, sort=True, 
suffixes=('_x', '_y'), copy=True, indicator=False)

# 1.默认以重叠的列名当做连接键。
df1=DataFrame({'key':['a','b','b'],'data1':range(3)})  
df2=DataFrame({'key':['a','b','c'],'data2':range(3)})  
pd.merge(df1,df2)  #没有指定连接键，默认用重叠列名，没有指定连接方式 
 
  data1 key data2 
0   0  a   0 
1   1  b   1 
2   2  b   1 
 
# 2.默认做inner连接（取key的交集），连接方式还有（left,right,outer)，制定连接方式加参数：how=''
pd.merge(df2,df1) 
 
  data2 key data1 
0   0  a   0 
1   1  b   1 
2   1  b   2          #默认内连接，可以看见c没有连接上。 
 
pd.merge(df2,df1,how='left')  #通过how，指定连接方式 
 
  data2 key data1 
0   0  a   0 
1   1  b   1 
2   1  b   2 
3   2  c  NaN 
 
# 3.多键连接时将连接键组成列表传入，例：pd.merge(df1,df2,on=['key1','key2']
right=DataFrame({'key1':['foo','foo','bar','bar'], 
     'key2':['one','one','one','two'], 
     'lval':[4,5,6,7]}) 
left=DataFrame({'key1':['foo','foo','bar'], 
     'key2':['one','two','one'], 
     'lval':[1,2,3]}) 
right=DataFrame({'key1':['foo','foo','bar','bar'], 
     'key2':['one','one','one','two'], 
     'lval':[4,5,6,7]}) 
pd.merge(left,right,on=['key1','key2'],how='outer') #传出数组 
  
 key1 key2 lval_x lval_y 
0 foo one    1    4 
1 foo one    1    5 
2 foo two    2   NaN 
3 bar one    3    6 
4 bar two   NaN    7 
 
# 4.如果两个对象的列名不同，可以分别指定，例：pd.merge(df1,df2,left_on='lkey',right_on='rkey')
df3=DataFrame({'key3':['foo','foo','bar','bar'], #将上面的right的key 改了名字 
     'key4':['one','one','one','two'], 
     'lval':[4,5,6,7]}) 
pd.merge(left,df3,left_on='key1',right_on='key3') #键名不同的连接 
  
 key1 key2 lval_x key3 key4 lval_y 
0 foo one    1 foo one    4 
1 foo one    1 foo one    5 
2 foo two    2 foo one    4 
3 foo two    2 foo one    5 
4 bar one    3 bar one    6 
5 bar one    3 bar two    7 

join(self, other, on=None, how='left', lsuffix='', rsuffix='',sort=False):