How to Insert a Column at a Specific Column Index in Pandas

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

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

Pandas (python): How to add column to dataframe for index?

How about this:

from pandas import *

idx = Int64Index([171, 174, 173])
df = DataFrame(index = idx, data =([1,2,3]))
print df

It gives me:

     0
171  1
174  2
173  3

Is this what you are looking for?

how do I insert a column at a specific column index in pandas data frame? (Change column order in pandas data frame)

You can try df.insert + df.pop after getting location of B by get_loc

df.insert(df.columns.get_loc("B")+1,"F",df.pop("F"))
print(df)

---

     A  B    F    C  D    E
0  7.0  1  6.0  NaN  8  1.0
1  8.0  2  8.0  5.0  8  5.0
2  9.0  3  5.0  6.0  8  NaN
3  1.0  8  NaN  1.0  3  4.0
4  6.0  8  9.0  2.0  5  0.0
5  NaN  2  8.0  NaN  1  3.0

Insert a column at the beginning (leftmost end) of a DataFrame

DataFrame.insert

df = pd.DataFrame({'A': ['x'] * 3, 'B': ['x'] * 3})
df

   A  B
0  x  x
1  x  x
2  x  x

seq = ['a', 'b', 'c']

# This works in-place.
df.insert(0, 'C', seq)
df

   C  A  B
0  a  x  x
1  b  x  x
2  c  x  x

---

pd.concat

df = pd.concat([pd.Series(seq, index=df.index, name='C'), df], axis=1)
df

   C  A  B
0  a  x  x
1  b  x  x
2  c  x  x

---

DataFrame.reindex + assign
Reindex first, then assign will remember the position of the original column.

df.reindex(['C', *df.columns], axis=1).assign(C=seq)

   C  A  B
0  a  x  x
1  b  x  x
2  c  x  x

Pandas - add value at specific iloc into new dataframe column

There are two steps to created & populate a new column using only a row number...
(in this approach iloc is not used)

First, get the row index value by using the row number

rowIndex = df.index[someRowNumber]

Then, use row index with the loc function to reference the specific row and add the new column / value

df.loc[rowIndex, 'New Column Title'] = "some value"

These two steps can be combine into one line as follows

df.loc[df.index[someRowNumber], 'New Column Title'] = "some value"

How to add an empty column to a dataframe?

If I understand correctly, assignment should fill:

>>> import numpy as np
>>> import pandas as pd
>>> df = pd.DataFrame({"A": [1,2,3], "B": [2,3,4]})
>>> df
   A  B
0  1  2
1  2  3
2  3  4
>>> df["C"] = ""
>>> df["D"] = np.nan
>>> df
   A  B C   D
0  1  2   NaN
1  2  3   NaN
2  3  4   NaN

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