Data Science And Analysis: Make DataFrames in Pandas And Python

BY
Eduonix

Acquire the skills to write Python programmes and learn to utilize the Pandas data frame to analyze data.

Lavel

Beginner

Mode

Online

Fees

₹ 199 1990

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Data Science And Analysis: Make DataFrames in Pandas And Python online course aims to teach data science and analysis and use the data to generate data frames using Python and Pandas, an open-source library written in Python that provides high-performance and easy-to-use data structures and data analysis tools. Participants will be taught to create completely operational games tic-tac-toe and Blackjack. Participants will also study classes, methods, attributes, instancing, and class inheritance.

Data Science And Analysis: Make DataFrames in Pandas And Python online certification is developed by John Bura - Owner of Mammoth Interactive, Web & Game Developer and Instructor and is made available through Eduonix, an educational organization providing skill development courses and training to students around the country. Data Science And Analysis: Make DataFrames in Pandas And Python online training is divided into two major parts, part 1 deals with Python, how Python is utilized by the companies like YouTube and Instagram, and concepts like variables, functions, and if statements, data structures, handling user input & output and file input & output. Part 2 deals with the process to employ the Python expertise in the Pandas framework to create and modify a data frame and analyze the data.

The highlights

  • Self-paced course
  • English videos with subtitles
  • 21.51 hours of pre-recorded video content
  • 52 online lectures
  • 30-day money-back guarantee
  • Lifetime access
  • Accessible on portable devices

Program offerings

  • Self-paced course
  • English videos with subtitles
  • Pre-recorded video content
  • Online lectures
  • 30-day money-back guarantee
  • Accessible on portable devices.

Course and certificate fees

Fees information
₹ 199  ₹1,990

The fees for the course Data Science And Analysis: Make DataFrames in Pandas And Python is -

HeadAmount in INR
Original feesRs. 1,990
Discounted feesRs. 199
certificate availability

No

What you will learn

Data science knowledge Knowledge of python

After completing the Data Science And Analysis: Make DataFrames in Pandas And Python certification course, participants will learn about the Python & Pandas framework, as well as how to utilise them for data analysis and other data science tasks. Participants will be able to use their Python knowledge in the Pandas framework to create and enhance a data frame. Participants will also be able to extract values from data, handle NaN values, and read and write data from and to comma-separated values (CSV) files.

The syllabus

Section 1 : Introduction to Python

  • Introduction 

Section 2 : Basics of Programming

  • Variables
  • Functions 
  • IfStatements

Section 3 : Lists

  • Introduction to Lists

Section 4 : Loops

  • Introduction To And Examples Using For Loops 
  • Getting Familiar With While Loops
  • Breaking And Continuing In Loop
  • Making Shapes With Loops
  • Nested Loops And Printing A Tic-tac-toe Field

Section 5 : Sets and Dictionaries

  • Understanding Sets and Dictionaries
  • An example for an inventory list

Section 6 : Input and Output

  • Introduction and implementation of Input and Output
  • Introduction to and Integrating File Input and Output
  • An example for a tic-tac-toe game part 1
  • An example of a tic-tac-toe game part 2
  • An example writing participant data to file
  • An example reading participant data from file
  • Doing some simple statistics with participant data from file

Section 7 : Classes

  • A first look at classes
  • Inheritance and classes
  • An example of classes using pets
  • An example of classes using pets - dogs
  • An example of classes using pets - cats
  • Taking the pets example further and adding humans

Section 8 : Importing

  • Introduction to importing and the random Library
  • Another way of importing and using lists with random
  • Useing the time Library
  • Introduction to the math library
  • Creating a user guessing game with random
  • Making the computer guess a random number

Section 9 : Project - Blackjack game

  • Blackjack game Part 1: creating and shuffling a deck
  • Blackjack Game Part 2: Creating the Player Class
  • Blackjack game Part 3: Expanding the Player Class
  • Blackjack game Part 4: Implementing a bet and Win
  • Blackjack game Part 5: Implementing the Player moves
  • Blackjack game Part 6: Running the Game (Final)

Section 10 : Error Handling

  • Getting Started with Error Handling

Section 11 : Pandas

  • Setting up Pandas

Section 12 : Datastructures

  • Creating a Dataframe
  • Sorting and Series
  • Expanding a Dataframe

Section 13 : Manipulating Dataframes

  • Getting Values and dealing with NaN Values
  • Dropping rows and columns

Section 14 : Reading and Writing Data

  • Reading from CSV 
  • Writing to CSV

Section 15 : Analytical Approaches to Data

  • Starting with an analysis
  • Locating data by labels
  • Statistical description of data
  • Histogram plots in pandas
  • Starting an analysis of all our data
  • Continuing an analysis of all our data

Instructors

Mr John Bura
Instructor
Udemy

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