Data analysis and visualization using Python
Basics in pandas library, File reading and writing, Data visualization using matplotlib, Data wrangling, Data aggregation, Time series
Python,Pandas,Python Pandas,Python Programming,Data Analysis
Lectures -92
Resources -81
Duration -10.5 hours
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Course Description
The course title is “Data analysis and visualization using Python” and it is using the pandas library.
It is divided into 7 chapters.
Chapter 1 talk about creation of pandas objects such as: Series, DataFrame, Index. This chapter includes basic arithmetic with pandas object. Also it describes other operations with pandas object such as: reindexing, deleting data from axis, filtering, indexing and sorting.
Chapter 2 describes statistical methods applied in pandas objects and manipulation with data inside pandas object. It describes pandas operations such as: unique values, value counting, manipulation with missing data, filtering and filling missing data.
Chapter 3 talks about reading and writing data from text file format and Microsoft Excel. Partial reading of large text files is also described with an example.
Chapter 4 describes data visualization using matplotlib library. It has example about the following graphs: line, scatter, bar and pie. Setting title, legend and labels in the graph is also describes with some practical examples. Drawing from pandas object is also described.
Chapter 5 talks about data wrangling. Merging Series object and DataFrame object is described with practical examples. Combining pandas objects and merging them is part of this chapter.
Chapter 6 talks about various forms of data aggregation and grouping. Creating and using pivot tables is also described.
Chapter 7 talks about time Series creation and manipulation. Classes DatetimeIndex and Period are included in the description of the chapter. Indexing and selection is described with practical examples.
Goals
The student will gain knowledge of Python libraries pandas and matplotlib and data analysis and vizualization
Prerequisites
The student should have basic understanding of Python programming language
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to pandas library
16 Lectures
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Series part 1 09:21 09:21
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Series Part 2 08:40 08:40
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DataFrame part 1 08:08 08:08
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DataFrame part 2 06:31 06:31
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Index object 02:20 02:20
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Reindexing 10:55 10:55
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Deleting data from the axis 06:41 06:41
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Indexing, selection and filtering Part 1 07:32 07:32
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Indexing, selection and filtering Part 2 09:34 09:34
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Indexing, selection and filtering Part 3 06:45 06:45
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Arithmetics with Series and DataFrames 09:21 09:21
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Functions and mapping 07:32 07:32
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Sorting in pandas 09:55 09:55
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Indexes with duplicate values 02:48 02:48
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Class work no 1 01:59 01:59
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Solution to class work no 1 07:24 07:24
Operations in pandas library
12 Lectures
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Reading and writing data to the file
8 Lectures
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Data visualization
12 Lectures
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Data wrangling in pandas
13 Lectures
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Data grouping and aggregation
13 Lectures
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Time series
18 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
Ardian Grezda
I have more than 15 years of experience in the following programming languages: C, C++, Python, .NET, etc.
I have also experience in various database systems: Oracle, MySQL, and Microsoft SQL-server.
I have 6 years of experience as a university lecturer in computer science subjects: Computer graphics, Image processing, Cryptography Data security, and Data structures.
Also, I have 6 years of experience as a Python instructor and lecturer in Data Analysis and Visualization.
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