Learn How To Code Python For Data Science, ML & Data Analysis, With 100+ Exercises and 4 Real Life Projects !
What you will learn
☑ Build a Solid Foundation in Data Analysis with Python
☑ You will be able to work with the Pandas Data Structures: Series, DataFrame and Index Objects
☑ Learn hundreds of methods and attributes across numerous pandas objects
☑ You will be able to analyze a large and messy data files
☑ You can prepare real world messy data files for AI and ML
☑ Manipulate data quickly and efficiently
☑ You will learn almost all the Pandas basics necessary to become a ‘Data Analyst’
Description
Hi, dear learning aspirants welcome to “Ultimate Python Bootcamp For Data Science & Machine Learning ” from beginner to advanced level. We love programming. Python is one of the most popular programming languages in today’s technical world. Python offers both object-oriented and structural programming features. Hence, we are interested in data analysis with Pandas in this course.
This course is for those who are ready to take their data analysis skill to the next higher level with the Python data analysis toolkit, i.e. “Pandas”.
This tutorial is designed for beginners and intermediates but that doesn’t mean that we will not talk about the advanced stuff as well. Our approach of teaching in this tutorial is simple and straightforward, no complications are included to make bored Or lose concentration.
In this tutorial, I will be covering all the basic things you’ll need to know about the ‘Pandas’ to become a data analyst or data scientist.
We are adopting a hands-on approach to learn things easily and comfortably. You will enjoy learning as well as the exercises to practice along with the real-life projects (The projects included are the part of large size research-oriented industry projects).
I think it is a wonderful platform and I got a wonderful opportunity to share and gain my technical knowledge with the learning aspirants and data science enthusiasts.
What you will learn:
You will become a specialist in the following things while learning via this course
“Data Analysis With Pandas”.
You will be able to analyze a large file
Build a Solid Foundation in Data Analysis with Python
After completing the course you will have professional experience on;
Pandas Data Structures: Series, DataFrame and Index Objects
Essential Functionalities
Data Handling
Data Pre-processing
Data Wrangling
Data Grouping
Data Aggregation
Pivoting
Working With Hierarchical Indexing
Converting Data Types
Time Series Analysis
Advanced Pandas Features and much more with hands-on exercises and practice works.
English
Language
Content
Getting Started
Course Introduction
How To Get Most Out Of This Course
Better To Know These Things
How To Install Python IPython And Jupyter Notebook
How To Install Anaconda For macOS And Linux Users
How To Work With The Jupyter Notebook Part-1
How To Work With The Jupyter Notebook Part-2
Pandas Building Blocks
How To Work With The Tabular Data
How To Read The Documentation In Pandas
Pandas_Data Structures
Theory On Pandas Data Structures
How To Construct The Pandas Series
How To Construct The DataFrame Objects
How To Construct The Pandas Index Objects
Practice Part 01
Practice Part 01 Solution
Data Indexing And Selection
Theory On Data Indexing And Selection
Data Selection In Series Part 1
Data Selection In Series Part 2
Indexers Loc And Iloc In Series
Data Selection In DataFrame Part 1
Data Selection In DataFrame Part 2
Accessing Values Using Loc Iloc And Ix In DataFrame Objects
Practice Part 02
Practice Part 02 Solution
Essential Functionalities
Theory On Essential Functionalities
How To Reindex Pandas Objects
How To Drop Entries From An Axis
Arithmetic And Data Alignment
Arithmetic Methods With Fill Values
Broadcasting In Pandas
Apply And Applymap In Pandas
How To Sort And Rank In Pandas
How To Work With The Duplicated Indices
Summarising And Computing Descriptive Statistics
Unique Values Value Counts And Membership
Practice_Part_03
Practice_Part_03 Solution
Data Handling
Theory On Data Handling
How To Read The Csv Files Part – 1
How To Read The Csv Files Part – 2
How To Read Text Files In Pieces
How To Export Data In Text Format
How To Use Python’s Csv Module
Practice_Part_04
Practice_Part_04 Solution
Data Cleaning And Preparation
Theory On Data Preprocessing
How To Handle Missing Values
How To Filter The Missing Values
How To Filter The Missing Values Part 2
How To Remove Duplicate Rows And Values
How To Replace The Non Null Values
How To Rename The Axis Labels
How To Descretize And Bin The Data Part – 1
How To Filter And Detect The Outliers
How To Reorder And Select Randomly
Converting The Categorical Variables Into Dummy Variables
How To Use ‘map’ Method
How To Manipulate With Strings
Using Regular Expressions
Working With The Vectorized String Functions
Practice_Part_05
Practice_Part_05 Solution
Data Wrangling
Theory On Data Wrangling
Hierarchical Indexing
Hierarchical Indexing Reordering And Sorting
Summary Statistics By Level
Hierarchical Indexing With DataFrame Columns
How To Merge The Pandas Objects
Merging On Row Index
How To Concatenate Along An Axis
How To Combine With Overlap
How To Reshape And Pivot Data In Pandas
Practice_Part_06
Practice_Part_06 Solution
Data Grouping And Aggregation
Thoery On Data Groupby And Aggregation
Groupby Operation
How To Iterate Over Groupby Object
How To Select Columns In Groupby Method
Grouping Using Dictionaries And Series
Grouping Using Functions And Index Level
Data Aggregation
Practice_Part_07
Practice_Part_07 Solution
Time Series Analysis
Theory On Time Series Analysis
Introduction To Time Series Data Types
How To Convert Between String And Datetime
Time Series Basics With Pandas Objects
Date Ranges Frequencies And Shifting
Date Ranges Frequencies And Shifting Part – 2
Time Zone Handling
Periods And Period Arithmetic’s
Practice_Part_08
Practice_Part_08 Solution
How To Analyse With The Part of Real Life Projects
A Brief Introduction To The Pandas Projects
Project_1 Description
Project_1 Solution Part – 1
Project_1 Solution Part – 2
Project_2 Description
Project_2 Solution
Project_3 Description
Project_3 Solution Part – 1
Project_3 Solution Part – 2
Project Assignment
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