Assign constant numpy array value to pandas dataframe column

Question

I would like to assign constant numpy array value to pandas dataframe column.

Here is what I tried:

import pandas as pd
import numpy as np

my_df = pd.DataFrame({'col_1': [1,2,3], 'col_2': [4,5,6]})
my_df['new'] = np.array([]) # did not work
my_df['new'] = np.array([])*len(df) # did not work

Here is what worked:

my_df['new'] = my_df['new'].apply(lambda x: np.array([]))

I am curious why it works with simple scalar, but does not work with numpy array. Is there simpler way to assign numpy array value?

For list-like values it expects to set as column series, so expects equal lengths. apply method is like forloop setting for each row. — Zero
– Zero, Commented Oct 16, 2017 at 15:44
You want your data-frame column to contain a bunch of empty numpy.ndarray objects? — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Oct 16, 2017 at 15:46
@juanpa.arrivillaga correct. It is like a placeholder, I will be concatenating to it later. — user1700890
– user1700890, Commented Oct 16, 2017 at 15:49
This would be incredibly inefficient from many perspectives. It doesn't sound like you should be using pandas/numpy at all. — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Oct 16, 2017 at 15:50
@user1700890 Maybe you should open a seperate question describing what your problem is that you actually trying to solve, what you did so far and give some sample data. — P.Tillmann
– P.Tillmann, Commented Oct 16, 2017 at 16:06

halfer · Accepted Answer · 2018-08-22 12:48:02Z

2

Your "new" column will contains arrays, so it must be a object type column.

The simplest way to initialize it is :

my_df = pd.DataFrame({'col_1': [1,2,3], 'col_2': [4,5,6]})
my_df['new']=None

You can then fill it as you want. For example :

for index,(a,b,_)  in my_df.iterrows():
    my_df.loc[index,'new']=np.arange(a,b)
#     
#    col_1  col_2        new
# 0      1      4  [1, 2, 3]
# 1      2      5  [2, 3, 4]
# 2      3      6  [3, 4, 5]

edited Aug 22, 2018 at 12:48

halfer

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answered Oct 16, 2017 at 17:02

B. M.

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