Rice University

Python Data Analysis

Scott Rixner
Joe Warren

Instructors: Scott Rixner

Sponsored by EmployNV

39,095 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(884 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
95%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(884 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
95%
Most learners liked this course

Details to know

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Assessments

2 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Introduction to Scripting in Python 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 4 modules in this course

This module will teach you about Python's dictionary data type and its capabilities. Dictionaries are used to map keys to values within programs.

What's included

7 videos2 readings1 assignment

This module will teach you about storing tabular data within Python programs using lists and dictionaries.

What's included

4 videos2 readings1 assignment

This module will teach you the basics of CSV files and how to read them from Python programs. We will discuss the use of Python's csv module to help you access tabular data in CSV files.

What's included

8 videos4 readings2 app items

This module will teach you how to sort data in Python. You will organize and analyze tabular data.

What's included

6 videos3 readings1 app item

Instructors

Instructor ratings
4.8 (122 ratings)
Scott Rixner
Rice University
11 Courses391,163 learners

Offered by

Rice University

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Learner reviews

Showing 3 of 884

4.7

884 reviews

  • 5 stars

    76.24%

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    16.62%

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    4.97%

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    1.35%

  • 1 star

    0.79%

KT
4

Reviewed on Jun 1, 2020

SC
5

Reviewed on May 19, 2020

J
5

Reviewed on Jan 29, 2019

Recommended if you're interested in Computer Science

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