By the end of this course, learners will be able to manipulate NumPy arrays, implement gradient descent, clean and transform retail datasets using Pandas, create pivot tables and groupby aggregations, manage string and datetime data, and export results for business reporting. This hands-on case study–driven program begins with NumPy foundations to establish strong numerical computing skills, then transitions into Pandas for retail data management and analysis.
NumPy & Pandas: Analyze & Manage Retail Data
NumPy & Pandas: Analyze & Manage Retail Data
This course is part of Data Analysis with NumPy and Pandas Specialization
Instructor: EDUCBA
Included with 
Gain insight into a topic and learn the fundamentals.
8 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Manipulate arrays, linear algebra, and gradient descent in NumPy.
Clean, transform, and analyze retail datasets with Pandas.
Build pivot tables, groupby reports, and export business insights.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
October 2025
Assessments
12 assignments
Taught in English
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This course is part of the Data Analysis with NumPy and Pandas Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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- Gain a foundational understanding of a subject or tool
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There are 3 modules in this course
This module introduces learners to the foundations of NumPy, the core numerical computing library in Python. Students will explore array operations, slicing, broadcasting, linear algebra concepts, and optimization techniques such as gradient descent. By the end, they will be able to manipulate arrays effectively and apply numerical methods to analytical problems.
What's included
10 videos4 assignments1 plugin
This module focuses on learning Pandas fundamentals using a retail dataset. Learners will gain skills in importing, cleaning, transforming, sorting, and combining data. Through practical exercises, they will acquire the ability to manage and prepare datasets for business insights.
What's included
9 videos4 assignments
This module advances learners into powerful Pandas features such as groupby aggregations, pivot tables, string manipulation, datetime handling, encoding, and reshaping. Students will master advanced techniques to derive actionable insights from retail datasets and prepare results for reporting.
What's included
9 videos4 assignments
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