将常量 numpy 数组值分配给 Pandas 数据框列

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?

Answer 1

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]