What is Pandas and Why Every Data Analyst Loves It

Written by: Marlon Colca
Posted on 10 May 2025 - 4 months ago
python pandas analytics

Learn what Pandas is, why it's essential in data science, and how to load your first dataset with it.

What is Pandas and Why Every Data Analyst Loves It 🐼

If you’re just getting started with data science or data analysis using Python, you’ve probably heard of Pandas.
No, not the animal — the library. But it is a pretty magical tool.

Pandas is a powerful and flexible Python library that makes working with structured data fast and intuitive. Think of it as a mix between a spreadsheet (like Excel) and a database — right inside your Python code.

🧠 Why should you learn Pandas?

Because:

• You can read and explore data from CSV, Excel, JSON, SQL, and more in seconds.
• You can filter, group, clean, reshape, and summarize data without writing SQL.
• It’s the entry point to machine learning, data visualization, and business analytics.

✨ First Look: Reading a CSV File

Let’s say you have a file called prices_sample.csv. Here’s how you load it using Pandas:

import pandas as pd

# Read the file
df = pd.read_csv("prices_sample.csv")

# Show the first 5 rows
print(df.head())

This is the usual Pandas workflow:

1. Load your data
2. Explore it (head(), info(), describe())
3. Clean, filter, or transform
4. Analyze, visualize, or export

🛠️ What can you do with Pandas?

Some things you’ll learn in this series:

• Clean up messy or incomplete data
• Group and summarize (e.g. average price per category)
• Filter specific rows or columns
• Handle dates, join tables, and plot data quickly

💡 A Quick Example

# Filter products with price greater than 50
expensive = df[df["price"] > 50]

# Group by category and calculate average price
averages = df.groupby("category")["price"].mean()

print(averages)

🚀 What’s Next?

In the next post, we’ll dive into basic data exploration (EDA) using tools like .describe(), .value_counts(), and more.

Get ready to really look into your data.
See you in the next one 🐼

🔜 Coming up next

11 May 2025 - 4 months ago

Exploring Your Data Like a Pro with Pandas

Learn how to explore and understand your dataset using Pandas. From `.head()` to `.describe()` and `.value_counts()`, this post walks you through the essential tools.