how do I insert a column at a specific column index in pandas?

Can I insert a column at a specific column index in pandas?

import pandas as pd
df = pd.DataFrame({'l':['a','b','c','d'], 'v':[1,2,1,2]})
df['n'] = 0

This will put column n as the last column of df, but isn't there a way to tell df to put n at the beginning?

see docs: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.insert.html

using loc = 0 will insert at the beginning

df.insert(loc, column, value)

---

df = pd.DataFrame({'B': [1, 2, 3], 'C': [4, 5, 6]})

df
Out: 
   B  C
0  1  4
1  2  5
2  3  6

idx = 0
new_col = [7, 8, 9]  # can be a list, a Series, an array or a scalar   
df.insert(loc=idx, column='A', value=new_col)

df
Out: 
   A  B  C
0  7  1  4
1  8  2  5
2  9  3  6

If you want a single value for all rows:

df.insert(0,'name_of_column','')
df['name_of_column'] = value

Edit:

You can also:

df.insert(0,'name_of_column',value)

You could try to extract columns as list, massage this as you want, and reindex your dataframe:

>>> cols = df.columns.tolist()
>>> cols = [cols[-1]]+cols[:-1] # or whatever change you need
>>> df.reindex(columns=cols)

   n  l  v
0  0  a  1
1  0  b  2
2  0  c  1
3  0  d  2

EDIT: this can be done in one line ; however, this looks a bit ugly. Maybe some cleaner proposal may come...

>>> df.reindex(columns=['n']+df.columns[:-1].tolist())

   n  l  v
0  0  a  1
1  0  b  2
2  0  c  1
3  0  d  2

df.insert(loc, column_name, value)

This will work if there is no other column with the same name. If a column, with your provided name already exists in the dataframe, it will raise a ValueError.

You can pass an optional parameter allow_duplicates with True value to create a new column with already existing column name.

Here is an example:

>>> df = pd.DataFrame({'b': [1, 2], 'c': [3,4]})
>>> df
   b  c
0  1  3
1  2  4
>>> df.insert(0, 'a', -1)
>>> df
   a  b  c
0 -1  1  3
1 -1  2  4
>>> df.insert(0, 'a', -2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python39\lib\site-packages\pandas\core\frame.py", line 3760, in insert
    self._mgr.insert(loc, column, value, allow_duplicates=allow_duplicates)
  File "C:\Python39\lib\site-packages\pandas\core\internals\managers.py", line 1191, in insert
    raise ValueError(f"cannot insert {item}, already exists")
ValueError: cannot insert a, already exists
>>> df.insert(0, 'a', -2,  allow_duplicates = True)
>>> df
   a  a  b  c
0 -2 -1  1  3
1 -2 -1  2  4

Here is a very simple answer to this(only one line).

You can do that after you added the 'n' column into your df as follows.

import pandas as pd
df = pd.DataFrame({'l':['a','b','c','d'], 'v':[1,2,1,2]})
df['n'] = 0

df
    l	v	n
0	a	1	0
1	b	2	0
2	c	1	0
3	d	2	0

# here you can add the below code and it should work.
df = df[list('nlv')]
df

    n	l	v
0	0	a	1
1	0	b	2
2	0	c	1
3	0	d	2



However, if you have words in your columns names instead of letters. It should include two brackets around your column names. 

import pandas as pd
df = pd.DataFrame({'Upper':['a','b','c','d'], 'Lower':[1,2,1,2]})
df['Net'] = 0
df['Mid'] = 2
df['Zsore'] = 2

df

	Upper	Lower	Net	Mid	Zsore
0	a	    1	    0	2	2
1	b	    2	    0	2	2
2	c	    1	    0	2	2
3	d	    2	    0	2	2

# here you can add below line and it should work 
df = df[list(('Mid','Upper', 'Lower', 'Net','Zsore'))]
df

   Mid	Upper	Lower	Net	Zsore
0	2	a	    1	    0	2
1	2	b	    2	    0	2
2	2	c	    1	    0	2
3	2	d	    2	    0	2

A general 4-line routine

You can have the following 4-line routine whenever you want to create a new column and insert into a specific location loc.

df['new_column'] = ... #new column's definition
col = df.columns.tolist()
col.insert(loc, col.pop()) #loc is the column's index you want to insert into
df = df[col]

In your example, it is simple:

df['n'] = 0
col = df.columns.tolist()
col.insert(0, col.pop()) 
df = df[col]