append(self, to_append, ignore_index: 'bool' = False, verify_integrity: 'bool' = False)
Use :None:func:`concat` instead. For further details see :None:ref:`whatsnew_140.deprecations.frame_series_append`
Iteratively appending to a Series can be more computationally intensive than a single concatenate. A better solution is to append values to a list and then concatenate the list with the original Series all at once.
Series to append with self.
If True, the resulting axis will be labeled 0, 1, …, n - 1.
If True, raise Exception on creating index with duplicates.
Concatenated Series.
Concatenate two or more Series.
concat
General function to concatenate DataFrame or Series objects.
>>> s1 = pd.Series([1, 2, 3])This example is valid syntax, but we were not able to check execution
... s2 = pd.Series([4, 5, 6])
... s3 = pd.Series([4, 5, 6], index=[3, 4, 5])
... s1.append(s2) 0 1 1 2 2 3 0 4 1 5 2 6 dtype: int64
>>> s1.append(s3) 0 1 1 2 2 3 3 4 4 5 5 6 dtype: int64
With :None:None:`ignore_index` set to True:
>>> s1.append(s2, ignore_index=True) 0 1 1 2 2 3 3 4 4 5 5 6 dtype: int64
With :None:None:`verify_integrity` set to True:
>>> s1.append(s2, verify_integrity=True) Traceback (most recent call last): ... ValueError: Indexes have overlapping values: [0, 1, 2]See :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.reshape.concat.concat
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