While we believe that this content benefits our community, we have not yet thoroughly reviewed it. If you have any suggestions for improvements, please let us know by clicking the “report an issue“ button at the bottom of the tutorial.

Hi Folks! In this article, we will have a look at the various **ways to find the average of a list in a Python List**.

In general, an average is a value that represents a whole set of data items or elements.

Formula: Average = summation of numbers/total count.

Either of the following techniques can be used to calculate the average/mean of a list in Python:

**Python mean() function****In-built sum() method****Python lambda and reduce() method****Python operator.add() method**

**Python 3** has `statistics module`

which contains an in-built function to calculate the mean or average of numbers. The `statistics.mean() function`

is used to calculate the **mean/average of input values or data set**.

The **mean() function** accepts the list, tuple or data-set containing numeric values as a parameter and returns the average of the data-items.

**Syntax:**

```
mean(data-set/input-values)
```

**Example:**

```
from statistics import mean
inp_lst = [12, 45, 78, 36, 45, 237.11, -1, 88]
list_avg = mean(inp_lst)
print("Average value of the list:\n")
print(list_avg)
print("Average value of the list with precision upto 3 decimal value:\n")
print(round(list_avg,3))
```

In the above snippet of code, we have used `statistics.round()`

method to **round off the output average up to a particular decimal value**.

**Syntax:**

```
statistics.round(value, precision value)
```

**Output:**

```
Average value of the list:
67.51375
Average value of the list with precision upto 3 decimal value:
67.514
```

Python `statistics.sum()`

function can also be used to find the average of data values in Python list.

The `statistics.len()`

function is used to calculate the length of the list i.e. the count of data items present in the list.

**Syntax:**

```
len(input-list)
```

Further, `statistics.sum()`

function is used to calculate the sum of all the data items in the list.

**Syntax:**

```
sum(input-list)
```

Note: **average = (sum)/(count)**.

**Example:**

```
from statistics import mean
inp_lst = [12, 45, 78, 36, 45, 237.11, -1, 88]
sum_lst = sum(inp_lst)
lst_avg = sum_lst/len(inp_lst)
print("Average value of the list:\n")
print(lst_avg)
print("Average value of the list with precision upto 3 decimal value:\n")
print(round(lst_avg,3))
```

**Output:**

```
Average value of the list:
67.51375
Average value of the list with precision upto 3 decimal value:
67.514
```

We can use **Python reduce()** function along with the **lambda()** function.

**Python reduce() function**: The `reduce() function`

is basically used to apply a particular(input) function to the set of elements passed to the function.

**Syntax:**

```
reduce(function,input-list/sequence)
```

- Initially, the reduce() function applies the passed function to the first two consecutive elements and returns the result.
- Further, we apply the same function to the result obtained in the previous step and the element succeeding the second element.
- This process continues until it reaches the end of the list.
- Finally, the result is returned to the terminal/screen as output.

**Python lambda() function:** The `lambda() function`

is used to build and form Anonymous functions i.e. function without a name or signature.

**Syntax:**

```
lambda arguments:function
```

**Example:**

```
from functools import reduce
inp_lst = [12, 45, 78, 36, 45, 237.11, -1, 88]
lst_len= len(inp_lst)
lst_avg = reduce(lambda x, y: x + y, inp_lst) /lst_len
print("Average value of the list:\n")
print(lst_avg)
print("Average value of the list with precision upto 3 decimal value:\n")
print(round(lst_avg,3))
```

**Output:**

```
Average value of the list:
67.51375
Average value of the list with precision upto 3 decimal value:
67.514
```

**The Python operator module** contains various functions to perform basic calculations and operations efficiently.

The `operator.add()`

function can be used to calculate the summation of all the data values present in the list with the help of **Python reduce() function**.

**Syntax:**

```
operator.add(value1, value2)
```

**Note: average = (sum)/(length or count of elements)**

**Example:**

```
from functools import reduce
import operator
inp_lst = [12, 45, 78, 36, 45, 237.11, -1, 88]
lst_len = len(inp_lst)
lst_avg = reduce(operator.add, inp_lst) /lst_len
print("Average value of the list:\n")
print(lst_avg)
print("Average value of the list with precision upto 3 decimal value:\n")
print(round(lst_avg,3))
```

**Output:**

```
Average value of the list:
67.51375
Average value of the list with precision upto 3 decimal value:
67.514
```

Python’s NumPy module has an in-built function to calculate the average/mean of the data items present in the data set or list.

The `numpy.average()`

method is used to calculate the average of the input list.

**Example:**

```
import numpy
inp_lst = [12, 45, 78, 36, 45, 237.11, -1, 88]
lst_avg = numpy.average(inp_lst)
print("Average value of the list:\n")
print(lst_avg)
print("Average value of the list with precision upto 3 decimal value:\n")
print(round(lst_avg,3))
```

**Output**:

```
Average value of the list:
67.51375
Average value of the list with precision upto 3 decimal value:
67.514
```

Thus, in this article, we have unveiled and understood various techniques to find the average of a Python List.

Thanks for learning with the DigitalOcean Community. Check out our offerings for compute, storage, networking, and managed databases.

Join our DigitalOcean community of over a million developers for free! Get help and share knowledge in our Questions & Answers section, find tutorials and tools that will help you grow as a developer and scale your project or business, and subscribe to topics of interest.

Sign up nowClick here to sign up and get $200 of credit to try our products over 60 days!