Generating and plotting Poisson distributions
In the previous exercise, you calculated some probabilities. Now let's plot that distribution.
Recall that on a certain highway turn, there are 2 accidents per day on average. Assuming the number of accidents per day can be modeled as a Poisson random variable, let's plot the distribution.
This is a part of the course
“Foundations of Probability in Python”
Exercise instructions
- Import
poissonfromscipy.stats,matplotlib.pyplotasplt, andseabornassns. - Generate a Poisson distribution sample with
size=10000andmu=2. - Plot the sample generated.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import poisson, matplotlib.pyplot, and seaborn
from ____ import ____
import ____ as ____
import ____ as ____
# Create the sample
sample = poisson.___(mu=____, size=10000, random_state=13)
# Plot the sample
sns.distplot(____, kde=False)
plt.show()This exercise is part of the course
Foundations of Probability in Python
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
Until now we've been working with binomial distributions, but there are many probability distributions a random variable can take. In this chapter we'll introduce three more that are related to the binomial distribution: the normal, Poisson, and geometric distributions.
Exercise 1: Normal distributionsExercise 2: Range of valuesExercise 3: Plotting normal distributionsExercise 4: Within three standard deviationsExercise 5: Normal probabilitiesExercise 6: Restaurant spending exampleExercise 7: Smartphone battery exampleExercise 8: Adults' heights exampleExercise 9: Poisson distributionsExercise 10: ATM exampleExercise 11: Highway accidents exampleExercise 12: Generating and plotting Poisson distributionsExercise 13: Geometric distributionsExercise 14: Catching salmon exampleExercise 15: Free throws exampleExercise 16: Generating and plotting geometric distributionsWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.