26 Oct Append two Pandas Series

In this lesson, we will append two Pandas series using the append() method. This will append two series. With that, the ignore_index parameter of the append() will allow you to ignore or consider the index. If ignore_index is set to True, the original indexes are ignored and replaced by 0, 1, 2, etc. in the output. The default is False.

Note: The append() method deprecated since version Pandas 1.4.0.

We will see two examples:

1. Append two Pandas series considering the original index
2. Append two Pandas series ignoring the original index

Append two Pandas series considering the original index

To append two series, use the append() method. The ignore_index parameter is by default set to False. This will keep both series indexes alive even after the append. Let us see an example:

import pandas as pd
 
# Data to be stored in the Pandas Series
data1 = [10, 20, 40, 80, 100]
data2 = [150, 200]

# Create two Series using the Series() method
series1 = pd.Series(data1, index = ["RowA", "RowB", "RowC", "RowD", "RowE"])
series2 = pd.Series(data2, index = ["RowF", "RowG"])

# Display the Series
print("Series1 (with custom index labels): \n",series1)
print("\nSeries2 (with custom index labels): \n",series2)

# Append
# The ignore_index parameter is by default set to False:
result = series1.append(series2, ignore_index = False) 
  
# Print the result 
print("\nResult after appending (considering original indexes):\n",result)

Output

Series1 (with custom index labels): 
RowA     10
RowB     20
RowC     40
RowD     80
RowE    100
dtype: int64

Series2 (with custom index labels): 
RowF    150
RowG    200
dtype: int64

Result after appending (considering original indexes):
RowA     10
RowB     20
RowC     40
RowD     80
RowE    100
RowF    150
RowG    200
dtype: int64

Append two Pandas series ignoring the original index

To append two series, use the append() method. For ignoring the original indexes and replacing them with 0, 1, 2, etc, set the ignore_index to True as discussed above.

Let us see an example:

import pandas as pd
 
# Data to be stored in the Pandas Series
data1 = [10, 20, 40, 80, 100]
data2 = [150, 200]

# Create two Series using the Series() method
series1 = pd.Series(data1, index = ["RowA", "RowB", "RowC", "RowD", "RowE"])
series2 = pd.Series(data2, index = ["RowF", "RowG"])

# Display the Series
print("Series1 (with custom index labels): \n",series1)
print("\nSeries2 (with custom index labels): \n",series2)

# Append
# The ignore_index parameter is set to True for ignoring original indexes
result = series1.append(series2, ignore_index = True) 
  
# Print the result 
print("\nResult after appending (ignoring original indexes):\n",result)

Output

Series1 (with custom index labels): 
RowA     10
RowB     20
RowC     40
RowD     80
RowE    100
dtype: int64

Series2 (with custom index labels): 
RowF    150
RowG    200
dtype: int64

Result after appending (ignoring original indexes):
0     10
1     20
2     40
3     80
4    100
5    150
6    200
dtype: int64

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