Normal Distribution Plot Statistics Python : By Govind Sharma
In Python, distribution plots are used to visualize the distribution of a dataset. There are several types of distribution plots available in Python, including histogram, KDE (Kernel Density Estimation) plot, and box plot. Here's a brief overview of each type of plot:
Histogram: A histogram is a plot that shows the frequency distribution of a dataset. In Python, you can use the hist() function from the matplotlib.pyplot library to create a histogram. Here's an example:
import matplotlib.pyplot as plt
import numpy as np
data = np.random.normal(0, 1, 1000) # Generate random data
plt.hist(data, bins=30) # Create a histogram with 30 bins
plt.show() # Display the plot
This code generates a normal distribution of 1000 random data points and creates a histogram with 30 bins.
import matplotlib.pyplot as plt
import numpy as np
data = np.random.normal(0, 1, 1000) # Generate random data
plt.boxplot(data) # Create a box plot
plt.show() # Display the plot
This code generates a normal distribution of 1000 random data points and creates a box plot.
#pythonforbeginners #datascience #python #python3 #machinelearning
#machinelearningprojects #machinelearningprojectsinpython #pythonforbeginners
#machinelearninginterviewquestions #python #pythonforbeginners #machinelearning #artificialintelligence #normaldistribution #machinelearningalgorithmsfordatascience #datascience
#machinelearning #interview #questions
#datasciencecourse #datasciencefullcourse
Tools Covered
Python
Excel
NumPy
Pandas
SciPy
And Many More..