What Is Data Science (and How Is Python Actually Used in It)?

What is data science?

At its core, data science = 3 things:

1. Collecting data – from files, websites, APIs, databases.

2. Understanding the data – filtering it, cleaning it, analyzing it.

3. Using it to answer real questions – through charts, numbers, or predictions.

In other words, you use data science to answer questions such as:

“Hmm, I wonder what people buy most on Fridays?”
“How many subscribers do I gain each month?”
“Which city has the worst air pollution trends over the past 10 years?”

And Python is the tool to go find the answer.

---

So how does Python fit into all this?

Here’s where Python shines: it has libraries—tools—that make all the boring, repetitive stuff super fast.

Let me give you a real-world example:

---

Example: You're analyzing a CSV of customer orders

Step 1: Collect the data

import pandas as pd 

data = pd.read_csv("orders.csv")

Step 2: Understand the data

data.head()  # Preview first 5 rows  
data["country"].value_counts()  # See where most orders come from

Step 3: Answer the question

# What’s the average order size?
print(data["order_value"].mean())

You just did data science. It is the “science” of the data.

---

Python Tools Used in Data Science

Here’s what Python brings to the table:

• pandas – for data analysis and wrangling

• matplotlib / seaborn – for plotting and visualizing data

• numpy – for number crunching

• scikit-learn – for making predictions

• jupyter – for running experiments and sharing results

• requests / BeautifulSoup – for collecting data from websites

Each one is a tool. You don’t need to learn them all at once.
You just pick the right one for the job—when you need it.

---

So should you learn data science?

Only if:

• You like making sense of messy stuff

• You enjoy spotting patterns

• You want to work in fields like finance, marketing, sports, healthcare, or AI

• You enjoy asking “why?” and trying to prove it with numbers

If yes—start small.
And start with Python.
(You’re already in the right place.)

---

TL;DR

• Data science = using data to answer real questions.

• Python = the easiest way to do it.

• You don’t need to “master” Python first.

• Just start with a question and use code to chase the answer.

Want a project that gets your hands dirty with real data? I will sen one tomorrow and another on Friday.

— Ardit