DataAnalytics for Beginners (Learn by 750+ Programs)

##### DataAnalytics for Beginners ######

This app covers all the concepts that the programmers need to develop their skills:

 Contains 750+ learning and algorithm based programs with source code.

 Contains only programs source code and output snapshots (it doesn’t contain any theory, for theory there are many books available).

 We use Python Interpreter and libraries for DataAnalytics Programming.

 We use text editor PyCharm, which is popular among beginner and professional programmers and works well on all operating systems.

 Each chapter contains well planned and organized collection of programs.

 This app will also be very helpful for beginners, teachers and trainers of DataAnalytics programming.

 We use small variable or identifier names for better readability in digital media like kindle, ipad, tab and mobile.

 This app contains much simpler approach to coding.

 A simpler approach is used to organize the programs for beginners as well as professional.

-------- FEATURE ----------

- Contains 750+ DataAnalytics Tutorial Programs with Output.

- Very simple User Interface (UI).

- Step by Step examples to learn DataAnalytics Programming.

- This DataAnalytics Learning App is completely OFFLINE.

- This App also contains Links for all "Our Learning Apps".

----- DataAnalytics Learning Description -----

[CHAPTER LIST]

1. Python Introduction, Data Types & Operators

2. Selection, Iteration & Strings

3. List, Tuple, Dictionary & Set

4. Library Functions, Functions, Modules & Packages

5. Classes & Objects and Inheritance and Exception Handling

6. Lambda Function, List Comprehension, Map, Filter and Reduce

7. NumPy Introduction

8. Array Creation & Attributes

9. Arithmetic Operations

10. Indexing & Slicing

11. Mathematical Functions

12. String Functions

13. Statistical, Searching & Sorting Functions

14. Advanced Indexing & Broadcasting

15. Array Manipulation

16. Matplotlib Introduction

17. Line Charts

18. Scatter Charts

19. Bar Charts

20. Pie Charts

21. Histogram Charts

22. Box Plot Charts

23. Customizing Plots / Charts

24. Pandas Introduction

25. Series Attributes & Methods

26. Indexing & Slicing in Series

27. Series Operations

28. DataFrame Creation & Attributes

29. Indexing, Selection & Accessing Data

30. DataFrame Iteration & Operations

31. DataFrame Exporting & Importing

32. Statistical Operations

33. Handling Missing Data

34. Combining & Grouping DataFrames

35. Plotting Charts with DataFrame

------- Suggestions Invited -------

Please send your suggestions regarding this DataAnalytics Learning App by email at [email protected].

##### We wish you all the best !!! #####