Pandas Series append() Method
If we want to merge two Series we can use the Python pandas Series.append()
method, This method merges or concatenate two Series and returns a new Series.
The below is the syntax of the Series.append()
method.
Syntax
Series.append(to_append, ignore_index=False, verify_integrity=False)
Parameters
to_append: It can be a Series or list/tuple of Series. It indicates the Series to append with self.
ignore_index: It represents the bool(True or False), and the default False. If this parameter is True, the resulting axis will be labeled as 0, 1, …, n - 1.
verify_integrity: It represents the bool(True or False), and the default False. If this parameter is True, it raises an Exception on creating an index with duplicates.
Example: Append two Series in Pandas
We can append a Series to a Series using Series.append()
method. See the below example.
#importing pandas as pd
import pandas as pd
#creating Series
s1 = pd.Series(['Python','Java'])
s2 = pd.Series([1,2])
print(s1.append(s2))
0 Python
1 Java
0 1
1 2
dtype: object
Example 2: Append two Series in Pandas
In the previous example, when we append two Series, their index values are overlapped. We can avoid this by passing the parameter ignore_index=True
in the Series.append()
method. See the below example. Now the index will start from 0 to n-1.
#importing pandas as pd
import pandas as pd
#creating Series
s1 = pd.Series(['Python','Java'])
s2 = pd.Series([1,2])
print(s1.append(s2, ignore_index=True))
0 Python
1 Java
2 1
3 2
dtype: object
Example 3: Append two Series in Pandas
This will throw exceptions when the index value overlaps. See the below example.
#importing pandas as pd
import pandas as pd
#creating Series
s1 = pd.Series(['Python','Java'])
s2 = pd.Series([1,2])
print(s1.append(s2,verify_integrity=True))
ValueError: Indexes have overlapping values: Int64Index([0, 1], dtype='int64')
Conclusion
In this tutorial, we learned the python pandas DataFrame.append()
method. We understood the syntax, parameters of the DataFrame.append()
method and solved examples by applying this method to the Series.