Pandas series mode - Python Pandas Series mode() Function

Pandas Series mode() Function:

Pandas series mode: The mode() function of the Pandas Series returns the mode/modes of the given Series.

Syntax:

Series.mode(dropna=None)

Parameters

dropna: This is optional. When computing the result, specify True to exclude NA/null values. True is the default value.

Return Value:

Mode pandas: The mode/modes of the Series in sorted order is returned by the mode() function of the Pandas Series

Pandas Series mode() Function in Python

Example1

Approach:

Import pandas module using the import keyword.
Import numpy module using the import keyword.
Give the category(level) values as arguments list to from_arrays() functions
Pass some random list, index values from the above and name as Numbers as the arguments to the Series() function of the pandas module to create a series.
Store it in a variable.
Print the above-given series
Apply mode() function on the given series to get the mode values of all the elements of the given series and print the result.
The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Import numpy module using the import keyword.
import numpy as np
# Give the category(level) values as arguments list to from_arrays() functions
gvn_indx = pd.MultiIndex.from_arrays([
    ['positive', 'negative', 'positive', 
     'positive', 'negative', 'negative']],
    names=['DataType'])
# Pass some random list, index values from the above and name as Numbers
# as the arguments to the Series() function of the pandas module to create a series.
# Store it in a variable.
gvn_series = pd.Series([12, 3, 12, 14, 56, 3], 
              name='Numbers', index=gvn_indx)

# Print the above given series
print("The given series is:")
print(gvn_series)
print()
# Apply mode() function on the given series to
# get the mode values of all the elements of the given series
# and print the result.
print("The mode values of all the elements of the given series:")
print(gvn_series.mode())

Output:

The given series is:
DataType
positive    12
negative     3
positive    12
positive    14
negative    56
negative     3
Name: Numbers, dtype: int64

The mode values of all the elements of the given series:
0     3
1    12
dtype: int64

Example2

Approach:

Import pandas module using the import keyword.
Pass some random key-value pair(dictionary), index list as arguments to the DataFrame() function of the pandas module to create a dataframe.
Store it in a variable.
Print the given dataframe.
Apply mode() function on the student_marks column of the dataframe to get the mode of the student_marks column of the dataframe and print the result.
The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random key-value pair(dictionary), index list as arguments to the 
# DataFrame() function of the pandas module to create a dataframe
# Store it in a variable.
data_frme = pd.DataFrame({
  "student_rollno": [1, 2, 3, 4],
  "student_marks": [80, 35, 25, 90]},
  index= ["virat", "nick" , "jessy", "sindhu"]
)
# Print the given dataframe
print("The given Dataframe:")
print(data_frme)
print()
# Apply mode() function on the student_marks column of the dataframe to
# get the mode of the student_marks column of the dataframe
# and print the result.
print("The mode of student_marks column of the dataframe:")
print(data_frme["student_marks"].mode())

Output:

The given Dataframe:
        student_rollno  student_marks
virat                1             80
nick                 2             35
jessy                3             25
sindhu               4             90

The mode of student_marks column of the dataframe:
0    25
1    35
2    80
3    90
dtype: int64

Pandas series mode – Python Pandas Series mode() Function

Pandas Series mode() Function in Python

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