Python for Data Analysis & Data Science

سرفصل های دوره

Hands-On Python Course for Data Analytics - Beginner to Advanced Level

1 - Introduction

1 -Course Introduction

2 -Course Structure

3 -Course RequirementPrerequisite

4 -Udemy Review System

5 -Application Download & Installation

6 -Install Python on Mac

7 -Install Python on Windows

8 -Adjusting Playback Rate

9 -Using Jupyter Notebook

10 -Python Files.zip

10 -Python Import Files

2 - Data Types & Variables

1 -Section Introduction

2 -Python as a Programming Language

3 -Data Types

4 -Variables

3 - Operators and Numbers in Python

1 -Section Introduction

2 -Operators

3 -Using Numbers in Python

4 - Using Strings in Python

1 -Section Introduction

2 -String Data Type

3 -String Methods

4 -String Operators

5 - Slicing, Format Functions & Casting

1 -Section Introduction

2 -Slice

3 -Format Function

4 -Change Data Types Using Functions - Casting

5 -Project 1 - Create a Bill Payment System

6 - List - Data Structure

1 -Section Introduction

2 -List

3 -List Methods

7 - Control Flow

1 -Section Introduction

2 -IF Statement

3 -Project 2 - Guessing Game - Part I

4 -While Loops

5 -Project 2 - Guessing Game - Part II

6 -For Loops

7 -Break & Continue Statement

8 - Tuple - Data Structure

1 -Section Introduction

2 -Tuples

9 - Dictionaries - Data Structure

1 -Section Introduction

2 -Dictionaries

3 -Dictionary Methods

4 -Create a List inside a Dictionary

5 -Project 3 - Concert Tickets

10 - Functions

1 -Section Introduction

2 -Pythons Built-In Functions

3 -User Defined Functions

4 -Variable Scope

5 -Packing & Unpacking Data - ARGS

6 -Packing & Unpacking Data - KWARGS

11 - Series

1 -Section Introduction

2 -Introduction to Series

3 -Create Series from a List

4 -Create Series from a Tuple

5 -Create Series from a Dictionary

6 -Create Series from a CSV Dataset

7 -Head & Tail Methods on a Series

8 -Count & Describe Methods on a Series

9 -Sort Values Method

10 -Inplace Parameter

11 -Sort Index Method

12 -Retrieve Records from a Series by Index Position

13 -Retrieve Records from a Series by Index Label

14 -Use Get Method to Retrieve Records from a Series

15 -Using Attributes on a Series

12 - Dataframe Part A

1 -Section Introduction

2 -Introduction to Dataframe

3 -Create Dataframe from a List

4 -Create Dataframe from a Dictionary of List

5 -Create Dataframe from an Imported File

6 -Retrieve Single Column from a Dataframe

7 -Retrieve Multiple Columns from a Dataframe

8 -Add a New Column to a Dataframe

9 -Delete Column(s) from a Dataframe

10 -Find the Sum of Null Values

11 -Drop Rows with Missing Values

12 -Replace Missing Value Using FILLNA Method

13 -Broadcasting Operation

14 -Count Unique Occurrences Using VALUE COUNT Method

15 -Sort Values in Dataframe Using SORT VALUES Method

16 -Sort Dataframe by Index Using SORT INDEX Method

17 -Remove and Replace Missing Values

18 -Change Data Types Using ASTYPE Method

13 - Dataframe Part B

1 -Optimizing Dataset

2 -Refine Records By a Condition

3 -Refine Records Using Multiple Conditions - AND Condition

4 -Select Specific Columns After a Condition

5 -Refine Dataframe Using Multiple Conditions - OR Condition

6 -Use The ISIN Method to Retrieve Row Having Specific Values

7 -Return Null and Not Null Values Using ISNULL AND NOTNULL Method

8 -Return Values Within Range Using BETWEEN Method

9 -Retrieve Duplicate Records Using DUPLICATED Method

10 -Delete Duplicate Records Using DROP DUPLICATES Method

11 -UNIQUE and NUNIQUE Methods

14 - Dataframe Part C

1 -Optimizing New Dataset

2 -SET IDEX and RESET INDEX Method

3 -Retrieve Rows by Index Label Using LOC[ ] Accessor

4 -Retrieve Rows by Index Position Using ILOC[ ] Accessor

5 -Return Specific Index Label Values

6 -Change Values in a Cell

7 -Change Values of Unique Groups

8 -Change Label or Column Name Using RENAME Method

9 -Delete Rows or Columns Using DROP Method

10 -Retrieve Random Sample From a Dataframe

11 -Retrieve Smallest or Largest Values

12 -Rank Values Using The RANK Method

13 -Create a Copy of Dataset

15 - Manipulating Text Data in a Dataframe

1 -Section Introduction

2 -Optimizing Text Dataset

3 -Change Text Case - Upper, Lower, Title, capitalize Method

4 -Remove White Spaces - Lstrip, Rstrip, Strip Method

5 -Replace Characters in a Column

6 -Filtering Dataframe for Specific Values - CONTAINS Method

7 -Split String Column - Part A

8 -Split String Column - Part B

16 - Multi Index in a Dataframe

1 -Section Introduction

2 -Create Multi-Index

3 -Sort Multi-Index

4 -Retrieve Rows from Multi-Index

5 -Stack & Unstack Method

6 -Aggregate Values Using PIVOT TABLE Method

17 - Groupby Object

1 -Section Introduction

2 -Groupby Object I

3 -Groupby Object II

4 -GET GROUP method

5 -Group by Multiple Columns

6 -Use The AGG Method to pass Different Operations

7 -For Loop & Groupby Object

18 - Data Relationship

1 -Section Introduction

2 -Data Relationship

3 -Normalization

4 -Introduction to JOIN

5 -Inner Join I

6 -Inner Join II

7 -Left Join

8 -Right Join

9 -Outer Join

10 -Merge More than 2 Dataframes

11 -Many to Many Data Relationship

12 -Left On & Right On

13 -Combine Dataframes Using PD.CONCAT

19 - Dates & Times Dataset

1 -Section Introduction

2 -Dates & Times

3 -Pandas Timestamp Object

4 -TO DATETIME Method

5 -PD.DATE RANGE Method

6 -PD.DATE RANGE II

7 -DT.Accessor

8 -Format Datetime Objects with DT.STRFTIME Method

9 -DT.STRFTIME Method

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