Exploring Python and Its Significance in Data Science
                     Exploring Python and Its Significance 
in Data Science
www.infosectrain.com | [email protected]
As the world entered the era of big data in the last few 
decades, the need for better and more efficient data storage 
became a significant challenge. Organizations that use big data 
have primarily focused on developing frameworks that can 
store large amounts of data. Then frameworks such as Hadoop 
were developed, which aided in the storage of massive 
amounts of data.
www.infosectrain.com | [email protected]
After resolving the storage issue, the attention turned to processing the data that had been 
stored. Data science emerged as the way of the future for data processing and analysis at this 
point. Data science is now an essential component of all organizations that work with large 
amounts of data. Today’s organizations employ data scientists and professionals to take raw data 
and turn it into useful information.
www.infosectrain.com | [email protected]
What is Data Science?
Finding and exploring data in the real world and applying that knowledge to 
solve an organization’s problems is the epitome of data science. Here are 
some examples of the diverse applications of data science:
 Predictions from Customers: A system can be trained to predict the 
likelihood of a customer purchasing a product based on the customer’s 
behavior patterns.
 Service Planning: Restaurants can forecast how many customers will 
visit over the weekend and stock up on food to meet demand.
www.infosectrain.com | [email protected]
Now that you understand what data science is, let us discuss the fundamental 
skills required for data science before delving into the topic of data science 
with Python. Here are the basic skills:
 Programming Language (Python or R)
 Database and Big Data Skills (SQL)
 Machine Learning Skills
 Mathematics
 Data Visualization
 Statistics
 Big Data
 Data Wrangling
www.infosectrain.com | [email protected]
Programming Language for Data Science
A successful data science project necessitates some level of programming 
language. According to research, Python is the most popular data science 
programming language with 87 percent of all languages’ popularity. Python is 
particularly popular due to its ease of use and support for a wide range of data 
science and machine learning libraries. In this article, we’ll look at Python and how 
it can help in data science. Python is a widely-used programming language for the 
following reasons:
 Python is an accessible and highly interpretable programming language. It is 
open-source software that anyone can use.
 Errors in the code are easy to understand because Python explains the error 
statement in detail, highlighting the line number where the error occurs.
 Writing Python programs is similar to writing sentences in English. It also 
facilitates debugging and exception handling.
 Scikit-Learn, NumPy, Pandas, and Matplotlib are examples of Python libraries 
that can be used to solve data science and machine learning problems.
https://youtu.be/pD8YM2kea4M
www.infosectrain.com | [email protected]
Why Python?
Python has grown in popularity as a programming language in recent years. Its use in 
data science, IoT, AI, and other technologies has increased its popularity. Python is a 
programming language that data scientists recommend because it is user-friendly, has 
a large community, and has a good library availability.  It is one of the primary reasons 
that data scientists all over the world use Python. Other reasons why Python is one of 
the most popular programming languages for data science include:
1.Speed: Python is a relatively fast programming language when compared to other 
programming languages.
2.Availability: There are many packages available that have been developed by other 
users and can be reused.
3.Design Goal: Python syntax roles are intuitive and straightforward to grasp, which 
aids in developing applications with a readable codebase.
4.Choice of Libraries: Python has a massive library like NumPy, Pandas, and SciPy. 
Many of these collections are also easily accessible in the form of tutorials.
5.Visualization and Graphics: Python provides several different visualization options.
www.infosectrain.com | [email protected]
Python Libraries for Data Analysis
Python is a simple programming language to learn, and you can do some basic things with it, such as 
adding and printing statements. However, you’ll need to import specific libraries if you want to do data 
analysis. Here are a few examples:
www.infosectrain.com | [email protected]
Let’s take a closer look at a few of the most important Python libraries:
NumPy: An essential Python package for scientific computing is NumPy. It includes 
the following:
 Arry objective with powerful N-dimensional
 C/C++ and Fortran code integration tools
 It has linear algebra, Fourier transform, and random number capabilities that are 
all useful
SciPy: It’s a scientific library with some unique features, as the name suggests.
 Special functions, integration, ODE solvers, gradient optimization, and other 
features are available
 It includes fully functional linear algebra modules
 NumPy is used to create it
www.infosectrain.com | [email protected]
Pandas: Pandas is used to perform structured data operations and 
manipulations.
 Python’s most valuable data analysis library
 Contributing to the increased use of Python in the data science 
community
 Data mugging and preparation are common uses for this tool
Data Wrangling Using Pandas
The process of cleaning and unifying messy and complicated data sets is 
referred to as data wrangling. Some of the advantages of data wrangling are 
as follows:
 More data about your information is revealed
 Enhances the organization’s decision-making abilities
 Assists in the collection of valuable and precise data for the organization
www.infosectrain.com | [email protected]
In reality, most of the data generated by an organization will be 
sloppy and contain missing values. There are several options for 
filling in the blanks. The business scenario will determine which 
parameters to use when filling them in. To see if your data has 
any missing values, do the following:
 Dtypes can be used to check the data types for each column.
 Use simple concatenation and merge methods to combine 
and merge data frames.
www.infosectrain.com | [email protected]
Conclusion
Python is an essential tool in the Data Analyst’s toolbox because it is designed 
to perform repetitive tasks and data manipulation. Anyone who has worked 
with large amounts of data knows how often repetition occurs. Because a 
tool handles the grunt work, Data Analysts can focus on their jobs making it 
more exciting and rewarding.
Get Started
Check out InfosecTrain’s Data Science with Python Certification Course if you 
want to get a head start in data science. Our Data Science with Python 
Certification Course will show you how to use Python to master data science 
and analytics techniques. With this course, you’ll learn the fundamentals of 
Python programming and gain in-depth, helpful knowledge in data analytics, 
data visualization, Exploratory Data Analysis(EDA), Statistics, machine 
learning and deep learning.
www.infosectrain.com | [email protected]
About InfosecTrain
• Established in 2016, we are one of the finest 
Security and Technology Training and 
Consulting company
• Wide range of professional training programs, 
certifications & consulting services in the IT 
and Cyber Security domain
• High-quality technical services, certifications 
or customized training programs curated with 
professionals of over 15 years of combined 
experience in the domain
www.infosectrain.com | [email protected]
Our Endorsements
www.infosectrain.com | [email protected]
Why InfosecTrain Global Learning Partners
Certified and Flexible modes Access to the 
Experienced Instructors of Training recorded 
sessions
Post training Tailor Made 
completion Training
www.infosectrain.com | [email protected]
Our Trusted Clients
www.infosectrain.com | [email protected]

Contact us
Get your workforce reskilled 
by our certified and 
experienced instructors!
IND: 1800-843-7890 (Toll Free) / US: +1 657-221-
1127  / UK : +44 7451 208413
[email protected]
www.infosectrain.com