Hey, folks! In this article, we will be focusing on the Binary representation of a data value using the Python bin() function.
Getting started with Python bin() function
Python has various in-built functions to deal and perform manipulations on the numeric data.
Python bin() function
is used to convert the decimal numeric data values into its binary format.
Syntax:
bin(number)
The bin() function
returns the binary representation value of the integer passed to it as an argument with a prefix ‘0b’ attached to it.
Example 1: Converting a positive numeric value to its binary form
num = 3
res_bin = bin(num)
print(res_bin)
Output:
0b11
Example 2: Converting a negative numeric value to its binary format
num = -3
res_bin = bin(num)
print(res_bin)
Output:
-0b11
Binary representation of elements in NumPy
Python numpy.binary_repr() function
is used to convert the data values of an array to the binary form in an element wise fashion in NumPy.
Syntax:
numpy.binary_repr(array[value],width)
width
: This parameter defines the length of the returned string representing the binary format.- If a negative value is passed to the function and width is not specified, then a minus(‘-‘) sign is added prior to the result. In case the width is specified, two’s complement of the number is represented as the absolute value.
Example 1:
import numpy as N
arr = [3,5,6,2]
res_arr = N.binary_repr(arr[1])
print(res_arr)
Output:
101
Example 2:
import numpy as N
arr = [3,5,6,2]
res_arr = N.binary_repr(arr[1],width=5)
print(res_arr)
Output:
00101
Binary representation of data elements in Pandas
It is possible for us to represent the elements of the dataset in Pandas in a binary format. The format() function can be used to represent an integer value in a dataset to its equivalent binary format.
We can simply use the apply() function
and create an anonymous function to imply the manipulation of every data value using Python lambda and format() function.
Syntax:
data['column'].apply(lambda element: format(int(element), 'b'))
Dummy dataset:

Example:
import pandas as PD
data = PD.read_csv("C:/marketing_tr.csv")
data_few = PD.DataFrame(data['custAge'].iloc[2:4])
data_few['custAge'].apply(lambda i: format(int(i), '05b'))
In the above piece of code, we have used the format(value, ‘b’) function to convert the data values into binary form. Further, we have created a function to achieve the same functionality using lambda expression. The ’05b’ represents the length of the return string i.e. length = 5.
Output:
2 101010
3 110111
Name: custAge, dtype: object
Conclusion
Thus, in this article, we have understood the way to represent the integer value to a binary form using the Python bin() function.
References
- Python bin() function — JournalDev