Data Analysis in Python with pandas & matplotlib in Spyder (Coursera)

Offered by Codio,
Data Analysis in Python with pandas & matplotlib in Spyder (Coursera)

Code and run your first Python script in minutes without installing anything! This course is designed for learners with no coding experience, providing a crash course in Python, which enables the learners to delve into core data analysis topics that can be transferred to other languages. In this course, you will learn how to import and organize your data, use functions to gather descriptive statistics, and perform statistical tests.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours. Finally, a longer-form lab at the end of the course will provide you an opportunity to apply all learned concepts within a real-world context.
Course 1 of 4 in the Data Science and Analysis Tools - from Jupyter to R Markdown Specialization.

What You Will Learn

  • Describe a numerical data set with statistics
  • Import and describe a mixed data set using pandas and matplotlib
  • Determine if populations are different using statistical tests
  • Describe relationships between variables using statistical tests

Syllabus

WEEK 1: Describing a Numerical Data Set
WEEK 2: Importing and Describing Mixed Data Sets (pandas)
WEEK 3: Statistical Tests to Determine if Populations are Different
WEEK 4: Statistical Tests to Describe Relationships
WEEK 5: Python Data Analysis Lab

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Design Computing: 3D Modeling in Rhinoceros with Python/Rhinoscript (Coursera) Coursera
University of Michigan

Design Computing: 3D Modeling in Rhinoceros with Python/Rhinoscript (Coursera)

Why should a designer learn to code? As our world is increasingly impacted by the use of algorithms, designers must learn how to use and create design computing programs. Designers must go beyond the narrowly focused use of computers in the automation of simple drafting/modeling tasks and instead explore the extraordinary potential digitalization holds for design culture/practice.

Sep 14th 2026
5-12 Weeks
Structural Equation Model and its Applications | 结构方程模型及其应用 (普通话) (Coursera) Coursera
The Chinese University of Hong Kong

Structural Equation Model and its Applications | 结构方程模型及其应用 (普通话) (Coursera)

在社会学、心理学、教育学、经济学、管理学、市场学等研究领域的数据分析中,结构方程建模是当前最前沿的统计方法中应用最广、研究最多的一个。它包含了方差分析、回归分析、路径分析和因子分析,弥补了传统回归分析和因子分析的不足,可以分析多因多果的联系、潜变量的关系,

Sep 14th 2026
5-12 Weeks
Estructuras de datos de Python (Coursera) Coursera
University of Michigan

Estructuras de datos de Python (Coursera)

Este curso presentará las estructuras de datos básicas del lenguaje de programación Python. Veremos los conceptos básicos de la programación de procedimientos y exploraremos cómo podemos usar las estructuras de datos integrados de Python, como listas, diccionarios y tuplas, para realizar análisis de datos cada vez más complejos. Este curso abarcará los capítulos 6 a 10 del libro de texto “Python para todos”. Este curso cubre Python 3.

Sep 14th 2026
5-12 Weeks
Comparing Genes, Proteins, and Genomes (Bioinformatics III) (Coursera) Coursera
University of California, San Diego

Comparing Genes, Proteins, and Genomes (Bioinformatics III) (Coursera)

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We will encounter a powerful algorithmic tool called dynamic programming that will help us determine the number of mutations that have separated the two genes/proteins.

Sep 14th 2026
5-12 Weeks
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Sep 14th 2026
4 Weeks
Infonomics II: Business Information Management and Measurement (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics II: Business Information Management and Measurement (Coursera)

Even decades into the Information Age, accounting practices yet fail to recognize the financial value of information. Moreover, traditional asset management practices fail to recognize information as an asset to be managed with earnest discipline. This has led to a business culture of complacence, and the inability for most organizations to fully leverage available information assets. This second course in the two-part Infonomics series explores how and why to adapt well-honed asset management principles and practices to information, and how to apply accepted and new valuation models to gauge information’s potential and realized economic benefits.

Sep 14th 2026
4 Weeks
Uso de bases de datos con Python (Coursera) Coursera
University of Michigan

Uso de bases de datos con Python (Coursera)

Este curso presentará a los estudiantes los conceptos básicos del lenguaje de consulta estructurado (Structured Query Language, SQL), así como el diseño básico de bases de datos para almacenar datos como parte de una iniciativa de varios pasos para recopilar, analizar y procesar datos. El curso utilizará SQLite3 como base de datos. También crearemos rastreadores web y procesos de visualización y recopilación de datos de varios pasos. Utilizaremos la biblioteca D3.js para realizar la visualización básica de datos.

Sep 14th 2026
5-12 Weeks
Interprofessional Healthcare Informatics (Coursera) Coursera
University of Minnesota

Interprofessional Healthcare Informatics (Coursera)

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network.

Sep 14th 2026
5-12 Weeks
Infonomics I: Business Information Economics and Data Monetization (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics I: Business Information Economics and Data Monetization (Coursera)

Thriving in the Information Age compels organizations to deploy information as an actual business asset, not as an IT asset or merely as a business byproduct. This demands creativity in conceiving and implementing new ways to generate economic benefits from the wide array of information assets available to an organization. Unfortunately, information too frequently is underappreciated and therefore underutilized.

Sep 14th 2026
4 Weeks
Matrix Methods (Coursera) Coursera
University of Minnesota

Matrix Methods (Coursera)

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction.

Sep 14th 2026
5-12 Weeks