DataAnalytics for Beginners

##### 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 !!! #####