How to replace only 1d values in 2d array after filter using numpy in pytho

[Ravi_exact]

How to replace only 1d values in 2d array after filter using numpy in python without loop i.e in pythonic way.

I want to filter only t2 rows and replace values in second column ( middle column ).

example:

>>> x = np.array([['t1',10,20],['t2',11,22],['t2',12,23], ['t3',21,32]])

>>> x
array([['t1', '10', '20'],
       ['t2', '11', '22'],
       ['t2', '12', '23'],
       ['t3', '21', '32']], 
      dtype='|S2')

replace_value_for_t2_col1 = [100,101]

so expected output is

array([['t1', '10', '20'],
       ['t2', '100', '22'],
       ['t2', '101', '23'],
       ['t3', '21', '32']], 
      dtype='|S2')

What i tried was,

Filter rows for t2

>>> x[x[:,0]=='t2']

array([['t2', '11', '22'],
       ['t2', '12', '23']], 
      dtype='|S2')

>>> x[x[:,0]=='t2'][:,1] = np.array([101,102])

Seems right, but not replacing. i guess it make a copy when we slice using [:,1], so its not changing in same array.

Please suggest me any brilliant ,simple and pythonic ideas, techniques.

[HiHe]

x[x[:,0]=='t2']
gives you a new array

[HiHe]

Look at
http://docs.scipy.org/doc/numpy/reference/generated/numpy.insert.html#numpy.insert

[vegaseat]

The pythonic way would be to use a loop.

[sneekula]

I would just temporarily convert back to a Python list:

import numpy as np

x = np.array([['t1',10,20],['t2',11,22],['t2',12,23], ['t3',21,32]])
print(x)  # test

# convert temporarily to Python list again
mylist = x.tolist()
mylist2 = ['100', '101']
n = 0
newlist = []
for line in mylist:
    if line[0] == 't2':
        line[1] = mylist2[n]
        n += 1
    newlist.append(line)

print(newlist)  # test

# convert back to numpy array
x = np.array(newlist)
print(x)  # show result