CODEWITHSUNDEEP
pythonpandasseries
Michael
Michael

Reputation: 16142

Add item to pandas.Series?

I want to add an integer to my pandas.Series
Here is my code:

import pandas as pd
input = pd.Series([1,2,3,4,5])
input.append(6)

When i run this, i get the following error:

Traceback (most recent call last):
  File "<pyshell#9>", line 1, in <module>
    f.append(6)
  File "C:\Python33\lib\site-packages\pandas\core\series.py", line 2047, in append
    verify_integrity=verify_integrity)
  File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 878, in concat
    verify_integrity=verify_integrity)
  File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 954, in __init__
    self.new_axes = self._get_new_axes()
  File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 1146, in _get_new_axes
    concat_axis = self._get_concat_axis()
  File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 1163, in _get_concat_axis
    indexes = [x.index for x in self.objs]
  File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 1163, in <listcomp>
    indexes = [x.index for x in self.objs]
AttributeError: 'int' object has no attribute 'index'

How can I fix that?

Upvotes: 26

Views: 79343

Answers (4)

pds
pds

Reputation: 2582

For Pandas >= 2.0:

series.append(s) was Deprecated since version 1.4.0. Removed since version 2.0 (2.0.0 (April 3, 2023))

Recommended approach is pd.concat(). Read about the reasoning in GH issue #35407.

Add new value to Series, becomes Series+Series using concat:

import pandas as pd
s1 = pd.Series( [1,2,3,4,5] )
s2 = pd.Series( 6 )

pd.concat([s1, s2], ignore_index=True)
>>>
0    1
1    2
2    3
3    4
4    5
5    6
dtype: int64

(However, beware of index conflicts by the default usage:).

pd.concat([s1, s2])
>>>
0    1
1    2
2    3
3    4
4    5
0    6
dtype: int64

Add new row to a DF, becomes DF + DF using concat:

my_column = 'a'
df = pd.DataFrame( s1, columns=[my_column] )
df
>>>
    a
0   1
1   2
2   3
3   4
4   5

pd.concat([ df, 
            s2.to_frame().rename({0:my_column},axis=1)
           ], 
           ignore_index=True)
>>>
    a
0   1
1   2
2   3
3   4
4   5
5   6

(Again, beware the default use case, causing conflicts in the index and specified column).

pd.concat( [ df, s2] )
>>>
    a       0
0   1.0     NaN
1   2.0     NaN
2   3.0     NaN
3   4.0     NaN
4   5.0     NaN
0   NaN     6.0

Upvotes: 6

alko
alko

Reputation: 48347

Convert appended item to Series:

>>> ds = pd.Series([1,2,3,4,5]) 
>>> ds.append(pd.Series([6]))
0    1
1    2
2    3
3    4
4    5
0    6
dtype: int64

or use DataFrame:

>>> df = pd.DataFrame(ds)
>>> df.append([6], ignore_index=True)
   0
0  1
1  2
2  3
3  4
4  5
5  6

and last option if your index is without gaps,

>>> ds.set_value(max(ds.index) + 1,  6)
0    1
1    2
2    3
3    4
4    5
5    6
dtype: int64

And you can use numpy as a last resort:

>>> import numpy as np
>>> pd.Series(np.concatenate((ds.values, [6])))

Update

In most recent versions, pandas.Series.append method has been deprecated, a decision that sparked some controversy. Consequently this answer is no longer valid, as well as the question. Consider using pandas.concat as a partial substitute.

Upvotes: 37

Attila.H
Attila.H

Reputation: 71

Using set_value generates the warning:

FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead

So you can instead use at like this:

input.at[input.index[-1]+1]=6

Upvotes: 6

Mak2006
Mak2006

Reputation: 171

here is a one-line answer It is dependent on how the array is defined. If we use Series is a one d array. Use the array notation like x[index] = new value

example

import pandas as pd
input = pd.Series([1,2,3,4,5])
newval = 7 # say
input[len(input)] = newval

or use append if the array is being directly defined.

#if input is defined as []
input2 = [1, 2]
#input2[len(input2)] = 3 # does not work
input2.append(3) #works
input2

Upvotes: -2

Related Questions