Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about **How do I calculate PDF (probability density function) in Python** **in Python**. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

## How do I calculate PDF (probability density function) in Python?

**How do I calculate PDF (probability density function) in Python?**Unless you have a reason to implement this yourself. All these functions are available in scipy.stats.norm

**calculate PDF (probability density function) in Python**Unless you have a reason to implement this yourself. All these functions are available in scipy.stats.norm

## Method 1

Unless you have a reason to implement this yourself. All these functions are available in scipy.stats.norm

I think you asking for the cdf, then use this code:

from scipy.stats import norm

print(norm.cdf(x, mean, std))

## Method 2

If you want to write it from scratch:

class PDF(): def __init__(self,mu=0, sigma=1): self.mean = mu self.stdev = sigma self.data = [] def calculate_mean(self): self.mean = sum(self.data) // len(self.data) return self.mean def calculate_stdev(self,sample=True): if sample: n = len(self.data)-1 else: n = len(self.data) mean = self.mean sigma = 0 for el in self.data: sigma += (el - mean)**2 sigma = math.sqrt(sigma / n) self.stdev = sigma return self.stdev def pdf(self, x): return (1.0 / (self.stdev * math.sqrt(2*math.pi))) * math.exp(-0.5*((x - self.mean) / self.stdev) ** 2)

**Summery**

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

**Also, Read**