Pandas Series min() Function:
The min() function of the Pandas Series returns the smallest(minimum) of the values along the chosen axis.
Syntax:
Series.min(axis=None, skipna=None, level=None, numeric_only=None)
Parameters
axis: This is optional. It indicates 0 or ‘index’. This is the axis on which the function will be applied.
skipna: This is optional. When computing the result, specify True to exclude NA/null values. The default value is True.
level: This is optional. It indicates the level (int or str). If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. The level name is specified by str.
numeric_only: This is optional. Pass True to include just float, int, or boolean data. False by default
Return Value:
If a level is given, it returns a scalar or a series.
- Python Pandas Series std() Function
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Pandas Series min() 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
- Printing the minimum value of all elements in the given series using the min() function.
- Printing the minimum value of each level of the series using level=’DataType’
- Printing the minimum value of each level of the series using level=0.
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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([20, 3, 15, 19, 56, 24], name='Numbers', index=gvn_indx) # Print the above given series print("The given series is:") print(gvn_series) print() # Printing the minimum value of all elements in the given series # using the min() function print("Minimum value of all elements in the given series : ") print(gvn_series.min()) print() # Printing the minimum value of each level of the series using level='DataType' print("Minimum value of all level values using level='DataType':") print(gvn_series.min(level='DataType')) print() # Printing the minimum value of each level of the series using level=0 print("Minimum value of all level values using level=0:") print(gvn_series.min(level=0))
Output:
The given series is: DataType positive 20 negative 3 positive 15 positive 19 negative 56 negative 24 Name: Numbers, dtype: int64 Minimum value of all elements in the given series : 3 Minimum value of all level values using level='DataType': DataType positive 15 negative 3 Name: Numbers, dtype: int64 Minimum value of all level values using level=0: DataType positive 15 negative 3 Name: Numbers, dtype: int64
Example2
Here, the min() function is used on a specific series/column in a DataFrame.
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 min() function on the student_marks column of the dataframe to get the minimum/smallest of all the values of the student_marks column and print the result.
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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 min() function on the student_marks column of the dataframe to # get the minimum/smallest of all the values of the student_marks column # and print the result. print("The minimum of student_marks column of the dataframe:") print(data_frme["student_marks"].min())
Output:
The given Dataframe: student_rollno student_marks virat 1 80 nick 2 35 jessy 3 25 sindhu 4 90 The minimum of student_marks column of the dataframe: 25