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 atul.soni09@gmail.com.
##### We wish you all the best !!! #####