AI & Data ScienceIntermediate

Master Pandas: Real-World Data Analysis with Python

Learn Pandas, one of the most powerful Python libraries for data analysis and manipulation. This course takes you from the fundamentals to practical data analysis techniques, helping you work confidently with real-world datasets. You will learn how to create and manipulate Series and DataFrames, import and export data, clean and transform datasets, filter and sort information, handle missing values, perform grouping and aggregation, merge and join datasets, and analyze data efficiently using Pandas.

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|12h 15m|21 lessons
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Master Pandas: Real-World Data Analysis with Python course

What's included

21

Lessons

12h 15m

Duration

Certificate

What you'll learn

Skills and outcomes you'll walk away with

Introduction to Pandas and Setup

Creating and Accessing a Pandas Series

Series Attributes and First Look

Missing Values and Dropping Items in a Series

Series Statistics and Unique Values

Sorting, Membership and Modifying a Series

Course curriculum

21 lessons • 12h 15m total

Master Pandas: Real-World Data Analysis with Python21 lessons
1

Introduction to Pandas and Setup

35m
2

Creating and Accessing a Pandas Series

35m
3

Series Attributes and First Look

35m
4

Missing Values and Dropping Items in a Series

35m
5

Series Statistics and Unique Values

35m
6

Sorting, Membership and Modifying a Series

35m
7

String Methods with the .str Accessor

35m
8

Creating a Pandas DataFrame

35m
9

Loading a DataFrame from CSV with read_csv

35m
10

Selecting Rows with loc, iloc, at and iat

35m
11

DataFrame Attributes and Shape

35m
12

Adding, Modifying, Renaming and Deleting Rows and Columns

35m
13

Indexing and Filtering a DataFrame

35m
14

Iterating Over a DataFrame

35m
15

Arithmetic Operations Between DataFrames

35m
16

Summary Statistics for a DataFrame

35m
17

Measuring Spread: Std, Variance, Quartiles and Skew

35m
18

Cumulative Functions, Correlation and Covariance

35m
19

Reshaping Data with pivot and pivot_table

35m
20

Handling Missing Data in a DataFrame

35m
21

Combining DataFrames and Grouping

35m

Certification path

Certification exam

63 multiple-choice questions • 70% passing score required

Verified certificate

Earn a verified PDF certificate with unique verification ID upon completion • ₹999

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