Pandas Series max() Function:
Dataframe max: The max() function of the Pandas Series returns the largest(maximum) of the values along the chosen axis.
Syntax:
Series.max(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. The maximum value is returned.
- Python Pandas Series std() Function
- Python Pandas Series var() Function
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Pandas Series max() 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 maximum value of all elements in the given series using the max() function.
- Printing the maximum value of each level of the series using level=’DataType’
- Printing the maximum value of each level of the series using level=0.
-
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 maximum value of all elements in the given series
# using the max() function
print("Maximum value of all elements in the given series : ")
print(gvn_series.max())
print()
# Printing the maximum value of each level of the series using level='DataType'
print("Maximum value of all level values using level='DataType':")
print(gvn_series.max(level='DataType'))
print()
# Printing the maximum value of each level of the series using level=0
print("Maximum value of all level values using level=0:")
print(gvn_series.max(level=0))
Output:
The given series is: DataType positive 20 negative 3 positive 15 positive 19 negative 56 negative 24 Name: Numbers, dtype: int64 Maximum value of all elements in the given series : 56 Maximum value of all level values using level='DataType': DataType positive 20 negative 56 Name: Numbers, dtype: int64 Maximum value of all level values using level=0: DataType positive 20 negative 56 Name: Numbers, dtype: int64
Example2
Here, the max() 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 max() function on the student_marks column of the dataframe to get the maximum/largest of all the values of the student_marks column 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 max() function on the student_marks column of the dataframe to
# get the maximum/largest of all the values of the student_marks column
# and print the result.
print("The maximum of student_marks column of the dataframe:")
print(data_frme["student_marks"].max())
Output:
The given Dataframe:
student_rollno student_marks
virat 1 80
nick 2 35
jessy 3 25
sindhu 4 90
The maximum of student_marks column of the dataframe:
90