Pandas Data Series: Display most frequent value in a given series and replace everything else as ‘Other’ in the series

Pandas: Data Series Exercise-20 with Solution

Write a Pandas program to display most frequent value in a given series and replace everything else as ‘Other’ in the series.

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
num_series = pd.Series(np.random.randint(1, 5, [15]))
print("Original Series:")
print(num_series)
print("Top 2 Freq:", num_series.value_counts())
result = num_series[~num_series.isin(num_series.value_counts().index[:1])] = 'Other'
print(num_series)

Sample Output:

Original Series:
0     3
1     1
2     1
3     3
4     2
5     2
6     1
7     2
8     3
9     1
10    2
11    2
12    2
13    3
14    3
dtype: int64
Top 2 Freq: 2    6
3    5
1    4
dtype: int64
0     Other
1     Other
2     Other
3     Other
4         2
5         2
6     Other
7         2
8     Other
9     Other
10        2
11        2
12        2
13    Other
14    Other
dtype: object        

Explanation:

num_series = pd.Series(np.random.randint(1, 5, [15])): This line creates a Pandas Series object 'num_series' containing 15 random integers between 1 and 5 using the np.random.randint() method.

result = num_series[~num_series.isin(num_series.value_counts().index[:1])] = 'Other': This line creates a boolean mask using the .isin() method to check which values in the Pandas Series object 'num_series' are equal to the most frequent value in the Series object, which is obtained using the .value_counts() method and selecting the first index using the slicing notation [:1]. The tilde (~) operator is used to negate the boolean mask, resulting in a mask that selects all values that are not equal to the most frequent value.

Python-Pandas Code Editor:

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