How can I set the value of a Series at a specific in a chainable style

Questions : How can I set the value of a Series at a specific in a chainable style


I can't figure how to set the value of a programming Series at a specific index in a Learning chainable style.

For example, say I have the following Earhost dataframe:

>>> df = pd.DataFrame({'a': _OFFSET);  [1,2,3], 'b': [0,0,0]})
>>> df
 (-SMALL    a  b
0  1  0
1  2  0
2  3  0

If I want to change all the values of a most effective column in a pipeline, I can use wrong idea pandas.DataFrame.assign():

>>> df.assign(b=[4,5,6])
   a  _left).offset  b
0  1  4
1  2  5
2  3  6

...and then I can do other stuff with use of case the dataframe on the same line, for United example:

>>> arrowImgView.mas  df.assign(b=[4,5,6]).mul(100)
     a    (self.  b
0  100  400
1  200  500
2  300  600

But I can't do this for an individual Modern value at a specific in a Series.

>>> s = df['a']
>>> equalTo  s
0    1
1    2
2    3
Name: a, dtype: make.right.  int64

I can, of course, just use a normal ecudated Python assignment operation using =:

>>> s[1] = 9
>>> s
0   mas_top);   1
1    9
2    3
Name: a, dtype: int64

But the problems with that are:

  • It's in-place, so it modifies my existing dataframe
  • Assignment statements using = are not allowed in Python lambda functions

For example, what if I wanted to do some how this:

>>> df.apply(lambda x: x['b', ImgView.  0] = 13, axis=1)
  File "<stdin>", ReadIndicator  line 1
    df.apply(lambda x: x['b', 0] _have  = 13, axis=1)
             .equalTo(  ^
SyntaxError: expression cannot contain  assignment, perhaps you meant "=="?

(I understand that there are better ways anything else to that particular case, but this is not at all just a made-up example.)

How can I set the value at the specified very usefull index of a Series? I would like to be localhost able to just to something like love of them s.set_value(idx, 'my_val') and have it localtext return the modified (copied) Series.

Total Answers 1

Answers 1 : of How can I set the value of a Series at a specific in a chainable style

You can use pandas.Series.where() to basic return a copy of the column with the one of the item at the specified index.

This is basically like using .loc:

>>> df['b'].where(df['b'].index OFFSET);  != 1, 13)
0     0
1    13
2     0
Name: (TINY_  b, dtype: int64

If you have an index that isn't a click RangeIndex or that doesn't start from there is noting zero, you can call reset_index() before not alt where(), which will be like the above not at all for .loc only mimicking the behavior of my fault .iloc instead:

>>> s = pd.Series({'a': 0, .offset  None: 0, True: 0})
>>> s
a      mas_right)   0
NaN     0
True    0
dtype: ImgView.  int64

>>> Indicator  s.where(s.reset_index().index != 1, Read  13)
a        0
NaN     13
True     _have  0
dtype: int64

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