When we’re trying to describe and summarize a sample of data, we probably start by finding the mean (or average), the median, and the mode of the data. These are central tendency measures and are often our first look at a dataset.
In this tutorial, we’ll learn how to find or compute the mean, the median, and the mode in Python. We’ll first code a Python function for each measure followed by using Python’s statistics module to accomplish the same task.
With this knowledge, we’ll be able to take a quick look at our datasets and get an idea of the general tendency of data.
If we have a sample of numeric values, then its mean or the average is the total sum of the values (or observations) divided by the number of values.
Say we have the sample
[4, 8, 6, 5, 3, 2, 8, 9, 2, 5]. We can calculate its mean by performing the operation:
(4 + 8 + 6 + 5 + 3 + 2 + 8 + 9 + 2 + 5) / 10 = 5.2
The mean (arithmetic mean) is a general description of our data. Suppose you buy 10 pounds of tomatoes. When you count the tomatoes at home, you get 25 tomatoes. In this case, you can say that the average weight of a tomato is 0.4 pounds. That would be a good description of your tomatoes.
The mean can also be a poor description of a sample of data. Say you’re analyzing a group of dogs. If you take the cumulated weight of all dogs and divide it by the number of dogs, then that would probably be a poor description of the weight of an individual dog as different breeds of dogs can have vastly different sizes and weights.
How good or how bad the mean describes a sample depends on how spread the data is. In the case of tomatoes, they’re almost the same weight each and the mean is a good description of them. In the case of dogs, there is no topical dog. They can range from a tiny Chihuahua to a giant German Mastiff. So, the mean by itself isn’t a good description in this case.
Now it’s time to get into action and learn how we can calculate the mean using Python.
To calculate the mean of a sample of numeric data, we’ll use two of Python’s built-in functions. One to calculate the total sum of the values and another to calculate the length of the sample.
The first function is sum(). This built-in function takes an iterable of numeric values and returns their total sum.
The second function is len(). This built-in function returns the length of an object.
len() can take sequences (string, bytes, tuple, list, or range) or collections (dictionary, set, or frozen set) as an argument.
Here’s how we can calculate the mean:
>>> def my_mean(sample): ... return sum(sample) / len(sample) ... >>> my_mean([4, 8, 6, 5, 3, 2, 8, 9, 2, 5]) 5.2
We first sum the values in
sum(). Then, we divide that sum by the length of
sample, which is the resulting value of
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Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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Mean, median, and mode are fundamental topics of statistics. You can easily calculate them in Python, with and without the use of external libraries.
These three are the main measures of central tendency. The central tendency lets us know the “normal” or “average” values of a dataset. If you’re just starting with data science, this is the right tutorial for you.
By the end of this tutorial you’ll:
If you want a downloadable version of the following exercises, feel free to check out the GitHub repository.
Let’s get into the different ways to calculate mean, median, and mode.
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
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