modifying numpy ndarray by index

Question

I'm stuck on trying to add values to the numbers column.

import pandas as pd

def twod_array(num):
    data = {"group": [-1, 0, 1, 2],
            'numbers': [[2], [14, 15], [16, 17], [19, 20, 21]],
            }
    df = pd.DataFrame(data=data)
    print(df)
    return 0

Currently it prints this:

   group       numbers
0     -1           [2]
1      0      [14, 15]
2      1      [16, 17]
3      2  [19, 20, 21]

What I'd like to do is to add a value based on the passed input, so for example if I pass 14.5 as a num, this is the output I'd like to see:

   group       numbers
0     -1           [2]
1      0      [14,14.5 15]
2      1      [16, 17]
3      2  [19, 20, 21]

I'm hoping someone can help with this. This is what I have so far but it fails at the insert line with the error "numpy.ndarray" object has no attribute 'insert'.

df = pd.DataFrame({"group": [-1, 0, 1, 2],
        'numbers': [[2], [14, 15], [16, 17], [19, 20, 21]],
        })
arr = df['numbers'].to_list()
num = 14.5

for i, sub_arr in enumerate(arr):
      for j, n in enumerate(sub_arr):
            if arr[i][j]>num:
                  if j!=0: 
                    arr[i].insert(j,num)
                  else: arr[i-1].insert(-1 ,num)

df['numbers'] = arr

Please explain somewhere what your goal is here... as is you have to fill in a lot of blanks and guess what your intention is. — BeRT2me
– BeRT2me, Commented Aug 10, 2022 at 2:13

BeRT2me · Accepted Answer · 2022-08-10 02:27:12Z

1

num = 14.5
mask = (df.numbers.apply(min).lt(num) &
        df.numbers.apply(max).gt(num))
index = mask[mask].index[0]
df.numbers.at[index].append(num)
df.numbers.at[index].sort()
print(df)

# Output:
   group         numbers
0     -1             [2]
1      0  [14, 14.5, 15]
2      1        [16, 17]
3      2    [19, 20, 21]

edited Aug 10, 2022 at 2:27

answered Aug 10, 2022 at 2:09

BeRT2me

13.3k2 gold badges18 silver badges39 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

stock_exchange Over a year ago

Perfect! and without looping through the values! Thanks a lot!

Sruthi · Accepted Answer · 2022-08-10 02:09:03Z

0

Iterate through the df and see if num lies between the first and last value of the numbers column. If it does, use the bisect module to insert num in a sorted fashion.

import bisect
for i in range(len(df)):
  if num >= df.loc[i,'numbers'][0] and num<= df.loc[i,'numbers'][-1]:
    bisect.insort(df.loc[i,'numbers'],num)
    
print(df)

   group         numbers
0     -1             [2]
1      0  [14, 14.5, 15]
2      1        [16, 17]
3      2    [19, 20, 21]

answered Aug 10, 2022 at 2:09

Sruthi

3,0281 gold badge14 silver badges26 bronze badges

Collectives™ on Stack Overflow

modifying numpy ndarray by index

2 Answers 2

1 Comment

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

1 Comment

Comments

Your Answer

Sign up or log in

Post as a guest

Related