Python 如何使用空值附加CSV文件数据

我是python和pandas数据集框架的新手。我正在尝试合并或附加两个csv文件数据。在第一步中，我能够读取CSV文件，但后来所需的输出并没有出现。我的CSV文件包含以下数据

physical.csv

digital.csv

预期输出：

darn  3.001  0.421  0.532  darn null null null null
ok  2.829  1.036  0.751  ok null null null null
three  1.115  1.146  2.921  three null null null null
darn null null null darn,0.631,1.321,0.951,1.751 
ok null null null ok,1.001,0.247,2.456,0.3216
three null null null three,0.285,1.283,0.924,956

import pandas as pd

a = pd.read_csv("D:/BMG/physical.csv")
physicalColumn = a.columns        
print("physical.csv : ", a)

b = pd.read_csv("D:/BMG/digital.csv")
b = b.dropna(axis=1)
digitalColumn = b.columns
print("digital.csv : ", b)

appendColumns = physicalColumn.append(digitalColumn)
print("appendColumns : ", appendColumns)

merged = a.append(b)
m_col = ['title','stage','jan','feb','mar','apr','may','jun']
merged.columns = m_col
print("merge data : ", merged)

我的Python代码是：

darn  3.001  0.421  0.532  darn null null null null
ok  2.829  1.036  0.751  ok null null null null
three  1.115  1.146  2.921  three null null null null
darn null null null darn,0.631,1.321,0.951,1.751 
ok null null null ok,1.001,0.247,2.456,0.3216
three null null null three,0.285,1.283,0.924,956

import pandas as pd

a = pd.read_csv("D:/BMG/physical.csv")
physicalColumn = a.columns        
print("physical.csv : ", a)

b = pd.read_csv("D:/BMG/digital.csv")
b = b.dropna(axis=1)
digitalColumn = b.columns
print("digital.csv : ", b)

appendColumns = physicalColumn.append(digitalColumn)
print("appendColumns : ", appendColumns)

merged = a.append(b)
m_col = ['title','stage','jan','feb','mar','apr','may','jun']
merged.columns = m_col
print("merge data : ", merged)

我从代码中获得的输出：

('merge data : ',    title  stage    jan       feb    mar    apr    may    jun
 0    NaN  0.532  0.421       NaN    NaN    NaN  3.001   darn
 1    NaN  0.751  1.036       NaN    NaN    NaN  2.829     ok
 2    NaN  2.921  1.146       NaN    NaN    NaN  1.115  three
 0  1.321    NaN    NaN    1.7510  0.631  0.951    NaN   darn
 1  0.247    NaN    NaN    0.3216  1.001  2.456    NaN     ok
 2  1.283    NaN    NaN  956.0000  0.285  0.924    NaN  three)

• 函数执行沿一个轴执行连接操作的所有繁重工作，同时在其他轴上执行索引（如果有的话）的可选集合逻辑（并集或交集）

Ex.

import pandas as pd
from io import StringIO


str1 = StringIO('''title,stage,jan,feb
darn,3.001,0.421,0.532
ok,2.829,1.036,0.751
three,1.115,1.146,2.921''')

a = pd.read_csv(str1,sep=',')
print("---a----")
print(a)

str2 = StringIO('''title,mar,apr,may,jun,
darn,0.631,1.321,0.951,1.751
ok,1.001,0.247,2.456,0.3216
three,0.285,1.283,0.924,956
''')

b = pd.read_csv(str2,sep=',')
b = b.dropna(axis=1)
print("---b---")
print(b)

print("-----output-------")
bigdata = pd.concat([a, b], ignore_index=True, sort =False)
print(bigdata)

O/p:

darn  3.001  0.421  0.532  darn null null null null
ok  2.829  1.036  0.751  ok null null null null
three  1.115  1.146  2.921  three null null null null
darn null null null darn,0.631,1.321,0.951,1.751 
ok null null null ok,1.001,0.247,2.456,0.3216
three null null null three,0.285,1.283,0.924,956

import pandas as pd

a = pd.read_csv("D:/BMG/physical.csv")
physicalColumn = a.columns        
print("physical.csv : ", a)

b = pd.read_csv("D:/BMG/digital.csv")
b = b.dropna(axis=1)
digitalColumn = b.columns
print("digital.csv : ", b)

appendColumns = physicalColumn.append(digitalColumn)
print("appendColumns : ", appendColumns)

merged = a.append(b)
m_col = ['title','stage','jan','feb','mar','apr','may','jun']
merged.columns = m_col
print("merge data : ", merged)

--a---

   title  stage    jan    feb
0   darn  3.001  0.421  0.532
1     ok  2.829  1.036  0.751
2  three  1.115  1.146  2.921

   title    mar    apr    may       jun
0   darn  0.631  1.321  0.951    1.7510
1     ok  1.001  0.247  2.456    0.3216
2  three  0.285  1.283  0.924  956.0000

   title  stage    jan    feb    mar    apr    may       jun
0   darn  3.001  0.421  0.532    NaN    NaN    NaN       NaN
1     ok  2.829  1.036  0.751    NaN    NaN    NaN       NaN
2  three  1.115  1.146  2.921    NaN    NaN    NaN       NaN
3   darn    NaN    NaN    NaN  0.631  1.321  0.951    1.7510
4     ok    NaN    NaN    NaN  1.001  0.247  2.456    0.3216
5  three    NaN    NaN    NaN  0.285  1.283  0.924  956.0000

--b---

   title  stage    jan    feb
0   darn  3.001  0.421  0.532
1     ok  2.829  1.036  0.751
2  three  1.115  1.146  2.921

   title    mar    apr    may       jun
0   darn  0.631  1.321  0.951    1.7510
1     ok  1.001  0.247  2.456    0.3216
2  three  0.285  1.283  0.924  956.0000

   title  stage    jan    feb    mar    apr    may       jun
0   darn  3.001  0.421  0.532    NaN    NaN    NaN       NaN
1     ok  2.829  1.036  0.751    NaN    NaN    NaN       NaN
2  three  1.115  1.146  2.921    NaN    NaN    NaN       NaN
3   darn    NaN    NaN    NaN  0.631  1.321  0.951    1.7510
4     ok    NaN    NaN    NaN  1.001  0.247  2.456    0.3216
5  three    NaN    NaN    NaN  0.285  1.283  0.924  956.0000

----输出---

   title  stage    jan    feb
0   darn  3.001  0.421  0.532
1     ok  2.829  1.036  0.751
2  three  1.115  1.146  2.921

   title    mar    apr    may       jun
0   darn  0.631  1.321  0.951    1.7510
1     ok  1.001  0.247  2.456    0.3216
2  three  0.285  1.283  0.924  956.0000

   title  stage    jan    feb    mar    apr    may       jun
0   darn  3.001  0.421  0.532    NaN    NaN    NaN       NaN
1     ok  2.829  1.036  0.751    NaN    NaN    NaN       NaN
2  three  1.115  1.146  2.921    NaN    NaN    NaN       NaN
3   darn    NaN    NaN    NaN  0.631  1.321  0.951    1.7510
4     ok    NaN    NaN    NaN  1.001  0.247  2.456    0.3216
5  three    NaN    NaN    NaN  0.285  1.283  0.924  956.0000

---

IIUC，OP还需要两个名为

title

的列。

合并[appendColumns]

？