我有3个数据帧具有相同的列名。说:
df1
column1 column2 column3
a b c
d e f
df2
column1 column2 column3
g h i
j k l
df3
column1 column2 column3
m n o
p q r
每个数据帧具有不同的值但具有相同的列。我尝试追加和连接,以及合并外部但有错误。这是我试过的:
df_final = df1.append(df2, sort=True,ignore_index=True).append2(df3, sort=True,ignore_index=True)
我也尝试过:df_final = pd.concat([df1, df2, df3], axis=1)
但是我得到了这个错误:AssertionError: Number of manager items must equal union of block items# manager items: 61, # tot_items: 62
我用谷歌搜索了这个错误,但我似乎无法理解为什么它会发生在我的情况下。任何指导都非常感谢!
我认为在某些或所有DataFrame中存在重复列名称的问题。
#simulate error
df1.columns = ['column3','column1','column1']
df2.columns = ['column5','column1','column1']
df3.columns = ['column2','column1','column1']
df_final = pd.concat([df1, df2, df3])
AssertionError:经理项目数必须等于块项目的联合#manage项目:4,#tot_items:5
您可以找到重复的列名称:
print (df3.columns[df3.columns.duplicated(keep=False)])
Index(['column1', 'column1'], dtype='object')
可能的解决方案是按列表设置列名:
df3.columns = ['column1','column2','column3']
print (df3)
column1 column2 column3
0 m n o
1 p q r
或删除重复列的重复列:
df31 = df3.loc[:, ~df3.columns.duplicated()]
print (df31)
column2 column1
0 m n
1 p q
然后concat
或append
应该很好。
尝试不提供轴示例:
import pandas as pd
mydict1 = {'column1' : ['a','d'],
'column2' : ['b','e'],
'column3' : ['c','f']}
mydict2 = {'column1' : ['g','j'],
'column2' : ['h','k'],
'column3' : ['i','i']}
mydict3= {"column1":['m','p'],
"column2":['n','q'],
"column3":['o','r']}
df1=pd.DataFrame(mydict1)
df2=pd.DataFrame(mydict2)
df3=pd.DataFrame(mydict3)
pd.concat([df1,df2,df3],ignore_index=True)
产量
column1 column2 column3
0 a b c
1 d e f
0 g h i
1 j k i
0 m n o
1 p q r
您可以在代码中删除axis=1
import pandas as pd
a = {"column1":['a','d'],
"column2":['b','e'],
"column3":['c','f']}
b = {"column1":['g','j'],
"column2":['h','k'],
"column3":['i','l']}
c = {"column1":['m','p'],
"column2":['n','q'],
"column3":['o','r']}
df1 = pd.DataFrame(a)
df2 = pd.DataFrame(b)
df3 = pd.DataFrame(c)
df_final = pd.concat([df1, df2, df3]) #.reset_index()
print(df_final)
#output
column1 column2 column3
0 a b c
1 d e f
0 g h i
1 j k l
0 m n o
1 p q r