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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