Data analysis and visualization using Python

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.