Python | Pandas Series.append()

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.append() function is used to concatenate two or more series object.

Syntax: Series.append(to_append, ignore_index=False, verify_integrity=False)



Parameter :
to_append : Series or list/tuple of Series
ignore_index : If True, do not use the index labels.
verify_integrity : If True, raise Exception on creating index with duplicates

Returns : appended : Series

Example #1: Use Series.append() function to append the passed series object at the end of this series object.

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# importing pandas as pd
import pandas as pd
  
# Creating the first Series
sr1 = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])
  
# Create the first Index
index_1 = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'
  
# set the index of first series
sr1.index = index_1
  
# Creating the second Series
sr2 = pd.Series(['Chicage', 'Shanghai', 'Beijing', 'Jakarta', 'Seoul'])
  
# Create the second Index
index_2 = ['City 6', 'City 7', 'City 8', 'City 9', 'City 10'
  
# set the index of second series
sr2.index = index_2
  
# Print the first series
print(sr1)
  
# Print the second series
print(sr2)

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Output :

City 1    New York
City 2     Chicago
City 3     Toronto
City 4      Lisbon
City 5         Rio
dtype: object

City 6      Chicage
City 7     Shanghai
City 8      Beijing
City 9      Jakarta
City 10       Seoul
dtype: object

Now we will use Series.append() function to append sr2 at the end of sr1 series.

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# append sr2 at the end of sr1
result = sr1.append(sr2)
  
# Print the result
print(result)

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Output :

City 1     New York
City 2      Chicago
City 3      Toronto
City 4       Lisbon
City 5          Rio
City 6      Chicage
City 7     Shanghai
City 8      Beijing
City 9      Jakarta
City 10       Seoul
dtype: object

As we can see in the output, the Series.append() function has successfully append the sr2 object at the end of sr1 object.
 
Example #2: Use Series.append() function to append the passed series object at the end of this series object. Ignore the original index of the two series objects.

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# importing pandas as pd
import pandas as pd
  
# Creating the first Series
sr1 = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])
  
# Create the first Index
index_1 = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'
  
# set the index of first series
sr1.index = index_1
  
# Creating the second Series
sr2 = pd.Series(['Chicage', 'Shanghai', 'Beijing', 'Jakarta', 'Seoul'])
  
# Create the second Index
index_2 = ['City 6', 'City 7', 'City 8', 'City 9', 'City 10'
  
# set the index of second series
sr2.index = index_2
  
# Print the first series
print(sr1)
  
# Print the second series
print(sr2)

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Output :

City 1    New York
City 2     Chicago
City 3     Toronto
City 4      Lisbon
City 5         Rio
dtype: object

City 6      Chicage
City 7     Shanghai
City 8      Beijing
City 9      Jakarta
City 10       Seoul
dtype: object

Now we will use Series.append() function to append sr2 at the end of sr1 series. We are going to ignore the index of the given series object.

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# append sr2 at the end of sr1
# ignore the index
result = sr1.append(sr2, ignore_index = True)
  
# Print the result
print(result)

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Output :

0    New York
1     Chicago
2     Toronto
3      Lisbon
4         Rio
5     Chicage
6    Shanghai
7     Beijing
8     Jakarta
9       Seoul
dtype: object

As we can see in the output, the Series.append() function has successfully append the sr2 object at the end of sr1 object and it has also ignored the index.



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