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Data analysis and visualization using Python - OneDDL - 12-13-2023
![[Image: 6a48ec45bf89ed58363c0c6ab46a7fbe.jpeg]](https://i122.fastpic.org/big/2023/1213/be/6a48ec45bf89ed58363c0c6ab46a7fbe.jpeg)
Free Download Data analysis and visualization using Python
Published 12/2023
Created by Ardian Grezda
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 92 Lectures ( 10h 39m ) | Size: 5.5 GB
The student will gain knowledge of Python libraries pandas and matplotlib and data analysis and vizualization
What you'll learn
Basics in pandas library
File reading and writing
Data visualization using matplotlib
Data wrangling
Data agreggation
Time series
Requirements
The student should have basic understanding of Python programming language
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.
Who this course is for
Aspiring data analyst
Data analyst
Students that want to have knowledge about pandas library
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