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Python for Data Science Tutorial - Beginner Level in Telugu - Python - Numpy - Pandas

Sundeep Saradhi Kanthety via YouTube

Overview

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Embark on a comprehensive 9-hour Python for Data Science tutorial designed for beginners, delivered in Telugu. Learn the fundamentals of Python programming, including variables, data types, control structures, and functions. Explore essential libraries like NumPy for numerical computing and Pandas for data manipulation. Master techniques for creating and manipulating arrays, handling missing data, and performing data analysis. Gain practical skills in file handling, data filtering, and exporting dataframes. By the end of this extensive tutorial, acquire a solid foundation in Python programming and its applications in data science.

Syllabus

- Introduction to Python
- Applications of Python
- IDEs
- Introduction to Python Interpreter
- Indentation & Comments
- Keywords
- Variables – Identifiers
- Built-In types
- Assigning Values to Variables
- Input and Output Statements
- Operators
- Control Structures
- Math & Random Modules
- List
- Tuple
- Strings
- Set
- Dictionary
- Functions
- Files
- Libraries in Python
- INTRODUCTION TO NUMPY
- INSTALLING NUMPY
- IMPORTING NUMPY
- CREATING ARRAYS
- INITIALIZATION OF ARRAYS
- ARRAY PROPERTIES
- ARRAY OPERATIONS
- ARITHMETIC OPERATIONS
- ARRAY FUNCTIONS
- INTRODUCTION TO PANDAS
- INSTALLATION & IMPORT
- HOW TO DOWNLOAD DATASET
- CREATING DATAFRAME
- INDEXING & SLICING
- UNDERSTANDING LOC & ILOC
- SORTING DATAFRAME
- MANIPULATING DATAFRAME
- REMOVING DUPLICATES
- HANDLING MISSING DATA
- DATA FILTERING & CONDITIONAL CHANGES
- EXPORT DATAFRAME

Taught by

Sundeep Saradhi Kanthety

Reviews

5.0 rating, based on 1 Class Central review

Start your review of Python for Data Science Tutorial - Beginner Level in Telugu - Python - Numpy - Pandas

  • Profile image for C Balarama Krishna HSC
    C Balarama Krishna HSC
    Nice Explanation and easy to understand. He has explained about python modules Numpy and Pandas in a very nice environment with all possible examples.

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