Pandas Crash Course for Beginners | Learn Pandas in One Video

In this Pandas Full Crash Course, you will learn the most important Pandas concepts required for Data Analysis and Data Science.

Dataset Used in This Video:

```python
import pandas as pd

data = {
"Student": ["Alex", "Bella", "Chris", "Diana", "Ethan", "Fiona", "George", "Hannah", "Ivan", "Julia", "Kevin", "Luna", "Mason", "Nora", "Oscar"],
"Batch": ["A", "B", "A", "C", "B", "A", "C", "B", "A", "C", "B", "A", "C", "B", "A"],
"City": ["Austin", "Boston", "Chicago", "Denver", "Austin", "Boston", "Chicago", "Denver", "Austin", "Boston", "Chicago", "Denver", "Austin", "Boston", "Chicago"],
"Python": [88, 76, 91, 64, 82, 95, 58, 73, 89, 67, 84, 92, 61, 78, 86],
"SQL": [81, 84, 79, 70, 88, 90, 62, 76, 85, 69, 80, 94, 65, 72, 83],
"Statistics": [79, 71, 88, 66, 85, 93, 55, 74, 90, 63, 82, 89, 60, 77, 81],
"Project": [86, 80, 92, 68, 87, 96, 59, 75, 91, 64, 83, 95, 62, 79, 88],
"Attendance": [92, 85, 96, 71, 88, 98, 64, 82, 94, 69, 86, 97, 66, 80, 90],
"Submitted_Assignment": ["Yes", "Yes", "Yes", "No", "Yes", "Yes", "No", "Yes", "Yes", "No", "Yes", "Yes", "No", "Yes", "Yes"],
"Enrollment_Date": ["2026-01-05", "2026-01-08", "2026-01-10", "2026-01-12", "2026-01-15", "2026-01-18", "2026-01-20", "2026-01-22", "2026-01-25", "2026-01-28", "2026-02-01", "2026-02-03", "2026-02-05", "2026-02-07", "2026-02-10"]
}

df = pd.DataFrame(data)
df

This tutorial is designed for beginners to intermediate learners who already know basic Python and NumPy and now want to start working with real-world data using Pandas.

In this video, we will use a simple student performance dataset and learn how Pandas is used for real data analysis tasks such as data cleaning, filtering, sorting, grouping, aggregation, pivot tables, crosstab, mapping values, creating new columns, date operations, string operations, and more.

By the end of this video, you will be comfortable using Pandas for data cleaning, data transformation, and basic data analysis.

Topics Covered:
✅ What is Pandas?
✅ Series vs DataFrame
✅ Creating a DataFrame
✅ Exploring data using head(), info(), describe(), shape
✅ Selecting rows and columns
✅ Filtering and sorting data
✅ Creating new columns
✅ Handling missing values
✅ Removing duplicates
✅ groupby and aggregation
✅ value_counts()
✅ pivot_table()
✅ crosstab()
✅ map() and apply()
✅ Date and string operations
✅ Mini data analysis project
✅ Interview-focused Pandas concepts

Видео Pandas Crash Course for Beginners | Learn Pandas in One Video канала Mohd Navaid