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种子名称： [GigaCourse.Com] Udemy - The Data Analyst Course Complete Data Analyst Bootcamp 2022
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文件数目： 259个文件
文件大小： 5.1 GB
收录时间： 2022-12-27 12:10
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最近下载： 2024-11-27 10:21

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[GigaCourse.Com] Udemy - The Data Analyst Course Complete Data Analyst Bootcamp 2022.torrent

01 - Introduction to the Course/001 A Practical Example - What Will You Learn in This Course.mp458.11MB

01 - Introduction to the Course/002 What Does the Course Cover.mp460.77MB

02 - Introduction to Data Analytics/001 Introduction to the World of Business and Data.mp410.4MB

02 - Introduction to Data Analytics/002 Relevant Terms Explained.mp417.13MB

02 - Introduction to Data Analytics/003 Data Analyst Compared to Other Data Jobs.mp48.21MB

02 - Introduction to Data Analytics/004 Data Analyst Job Description.mp419.93MB

02 - Introduction to Data Analytics/005 Why Python.mp415.1MB

03 - Setting up the Environment/001 Introduction.mp413.81MB

03 - Setting up the Environment/002 Programming Explained in a Few Minutes.mp414.34MB

03 - Setting up the Environment/003 Jupyter - Introduction.mp48.2MB

03 - Setting up the Environment/004 Jupyter - Installing Anaconda.mp421.46MB

03 - Setting up the Environment/005 Jupyter - Intro to Using Jupyter.mp45.88MB

03 - Setting up the Environment/006 Jupyter - Working with Notebook Files.mp418.63MB

03 - Setting up the Environment/007 Jupyter - Using Shortcuts.mp46.67MB

03 - Setting up the Environment/008 Jupyter - Handling Error Messages.mp413.26MB

03 - Setting up the Environment/009 Jupyter - Restarting the Kernel.mp44.71MB

04 - Python Basics/001 Python Variables.mp414.08MB

04 - Python Basics/002 Types of Data - Numbers and Boolean Values.mp413.7MB

04 - Python Basics/003 Types of Data - Strings.mp419.73MB

04 - Python Basics/004 Basic Python Syntax - Arithmetic Operators.mp47.29MB

04 - Python Basics/005 Basic Python Syntax - The Double Equality Sign.mp42.72MB

04 - Python Basics/006 Basic Python Syntax - Reassign Values.mp41.87MB

04 - Python Basics/007 Basic Python Syntax - Add Comments.mp42.41MB

04 - Python Basics/008 Basic Python Syntax - Line Continuation.mp41.2MB

04 - Python Basics/009 Basic Python Syntax - Indexing Elements.mp42.37MB

04 - Python Basics/010 Basic Python Syntax - Indentation.mp42.8MB

04 - Python Basics/011 Operators - Comparison Operators.mp44.16MB

04 - Python Basics/012 Operators - Logical and Identity Operators.mp415.05MB

04 - Python Basics/013 Conditional Statements - The IF Statement.mp45.33MB

04 - Python Basics/014 Conditional Statements - The ELSE Statement.mp45.25MB

04 - Python Basics/015 Conditional Statements - The ELIF Statement.mp414.25MB

04 - Python Basics/016 Conditional Statements - A Note on Boolean Values.mp44.25MB

04 - Python Basics/017 Functions - Defining a Function in Python.mp43.23MB

04 - Python Basics/018 Functions - Creating a Function with a Parameter.mp410MB

04 - Python Basics/019 Functions - Another Way to Define a Function.mp46.46MB

04 - Python Basics/020 Functions - Using a Function in Another Function.mp43.24MB

04 - Python Basics/021 Functions - Combining Conditional Statements and Functions.mp46.1MB

04 - Python Basics/022 Functions - Creating Functions That Contain a Few Arguments.mp42.82MB

04 - Python Basics/023 Functions - Notable Built-in Functions in Python.mp48.5MB

04 - Python Basics/024 Sequences - Lists.mp49.53MB

04 - Python Basics/025 Sequences - Using Methods.mp47.93MB

04 - Python Basics/026 Sequences - List Slicing.mp419.19MB

04 - Python Basics/027 Sequences - Tuples.mp47.41MB

04 - Python Basics/028 Sequences - Dictionaries.mp410.14MB

04 - Python Basics/029 Iteration - For Loops.mp45.51MB

04 - Python Basics/030 Iteration - While Loops and Incrementing.mp49.15MB

04 - Python Basics/031 Iteration - Create Lists with the range() Function.mp47.25MB

04 - Python Basics/032 Iteration - Use Conditional Statements and Loops Together.mp47.13MB

04 - Python Basics/033 Iteration - Conditional Statements, Functions, and Loops.mp44.27MB

04 - Python Basics/034 Iteration - Iterating over Dictionaries.mp46.54MB

05 - Fundamentals for Coding in Python/001 Object-Oriented Programming (OOP).mp48.43MB

05 - Fundamentals for Coding in Python/002 Modules, Packages, and the Python Standard Library.mp413.61MB

05 - Fundamentals for Coding in Python/003 Importing Modules.mp47.41MB

05 - Fundamentals for Coding in Python/004 Introduction to Using NumPy and pandas.mp431.9MB

05 - Fundamentals for Coding in Python/005 What is Software Documentation.mp413.4MB

05 - Fundamentals for Coding in Python/006 The Python Documentation.mp443.94MB

06 - Mathematics for Python/002 Scalars and Vectors.mp48.39MB

06 - Mathematics for Python/003 Linear Algebra and Geometry.mp413.56MB

06 - Mathematics for Python/004 Arrays in Python.mp419MB

06 - Mathematics for Python/005 What Is a Tensor.mp411.62MB

06 - Mathematics for Python/006 Adding and Subtracting Matrices.mp422.1MB

06 - Mathematics for Python/007 Errors When Adding Matrices.mp45.76MB

06 - Mathematics for Python/008 Transpose.mp420.5MB

06 - Mathematics for Python/009 Dot Product of Vectors.mp411.36MB

06 - Mathematics for Python/010 Dot Product of Matrices.mp426.42MB

06 - Mathematics for Python/011 Why is Linear Algebra Useful.mp486.22MB

07 - NumPy Basics/001 The NumPy Package and Why We Use It.mp413.03MB

07 - NumPy Basics/002 InstallingUpgrading NumPy.mp43.92MB

07 - NumPy Basics/003 Ndarray.mp47.64MB

07 - NumPy Basics/004 The NumPy Documentation.mp415.82MB

08 - Pandas - Basics/001 Introduction to the pandas Library.mp414.22MB

08 - Pandas - Basics/002 Installing and Running pandas.mp437.73MB

08 - Pandas - Basics/003 Introduction to pandas Series.mp424.62MB

08 - Pandas - Basics/004 Working with Attributes in Python.mp426.84MB

08 - Pandas - Basics/005 Using an Index in pandas.mp415.73MB

08 - Pandas - Basics/006 Label-based vs Position-based Indexing.mp424.52MB

08 - Pandas - Basics/007 More on Working with Indices in Python.mp433.21MB

08 - Pandas - Basics/008 Using Methods in Python - Part I.mp417.04MB

08 - Pandas - Basics/009 Using Methods in Python - Part II.mp49.18MB

08 - Pandas - Basics/010 Parameters vs Arguments.mp416.78MB

08 - Pandas - Basics/011 the pandas Documentation.mp452.02MB

08 - Pandas - Basics/012 Introduction to pandas DataFrames.mp411.71MB

08 - Pandas - Basics/013 Creating DataFrames from Scratch - Part I.mp426.06MB

08 - Pandas - Basics/014 Creating DataFrames from Scratch - Part II.mp429.79MB

08 - Pandas - Basics/015 Additional Notes on Using DataFrames.mp412.41MB

09 - Working with Text Files/001 Working with Files in Python - An Introduction.mp411.73MB

09 - Working with Text Files/002 File vs File Object, Read vs Parse.mp49.23MB

09 - Working with Text Files/003 Structured vs Semi-Structured and Unstructured Data.mp410.85MB

09 - Working with Text Files/004 Data Connectivity through Text Files.mp410.57MB

09 - Working with Text Files/005 Principles of Importing Data in Python.mp416.45MB

09 - Working with Text Files/006 More on Text Files (.txt vs .csv).mp412.82MB

09 - Working with Text Files/007 Fixed-width Files.mp44.73MB

09 - Working with Text Files/008 Common Naming Conventions Used in Programming.mp48.22MB

09 - Working with Text Files/009 Importing Text Files in Python ( open() ).mp424.83MB

09 - Working with Text Files/010 Importing Text Files in Python ( with open() ).mp426.29MB

09 - Working with Text Files/011 Importing .csv Files with pandas - Part I.mp449.84MB

09 - Working with Text Files/012 Importing .csv Files with pandas - Part II.mp410.91MB

09 - Working with Text Files/013 Importing .csv Files with pandas - Part III.mp475.11MB

09 - Working with Text Files/014 Importing Data with the index_col Parameter.mp411.65MB

09 - Working with Text Files/015 Importing Data with NumPy - .loadtxt() vs genfromtxt().mp456.48MB

09 - Working with Text Files/016 Importing Data with NumPy - Partial Cleaning While Importing.mp430.51MB

09 - Working with Text Files/018 Importing .json Files.mp448.53MB

09 - Working with Text Files/019 Prelude to Working with Excel Files in Python.mp443.03MB

09 - Working with Text Files/020 Working with Excel Data (the .xlsx Format).mp411.55MB

09 - Working with Text Files/021 An Important Exercise on Importing Data in Python.mp442.97MB

09 - Working with Text Files/022 Importing Data with the pandas' Squeeze Parameter.mp411.58MB

09 - Working with Text Files/023 A Note on Importing Files in Jupyter.mp419.68MB

09 - Working with Text Files/024 Saving Your Data with pandas.mp427.68MB

09 - Working with Text Files/025 Saving Your Data with NumPy - np.save().mp418.93MB

09 - Working with Text Files/026 Saving Your Data with NumPy - np.savez().mp415.41MB

09 - Working with Text Files/027 Saving Your Data with NumPy - np.savetxt().mp420.84MB

09 - Working with Text Files/029 Working with Text Files - Conclusion.mp42.06MB

10 - Working with Text Data/001 Working with Text Data and Argument Specifiers.mp421.35MB

10 - Working with Text Data/002 Manipulating Python Strings.mp412.29MB

10 - Working with Text Data/003 Using Various Python String Methods - Part I.mp423.59MB

10 - Working with Text Data/004 Using Various Python String Methods - Part II.mp420.37MB

10 - Working with Text Data/005 String Accessors.mp430.62MB

10 - Working with Text Data/006 Using the .format() Method.mp421.66MB

11 - Must-Know Python Tools/001 Iterating Over Range Objects.mp411.06MB

11 - Must-Know Python Tools/002 Nested For Loops - Introduction.mp412.21MB

11 - Must-Know Python Tools/003 Triple Nested For Loops.mp419.41MB

11 - Must-Know Python Tools/004 List Comprehensions.mp443.2MB

11 - Must-Know Python Tools/005 Anonymous (Lambda) Functions.mp433.7MB

12 - Data GatheringData Collection/001 What is data gatheringdata collection.mp419.17MB

13 - APIs (POST requests are not needed for this course)/001 Overview of APIs.mp410.4MB

13 - APIs (POST requests are not needed for this course)/002 GET and POST Requests.mp46.27MB

13 - APIs (POST requests are not needed for this course)/003 Data Exchange Format for APIs JSON.mp45.7MB

13 - APIs (POST requests are not needed for this course)/004 Introducing the Exchange Rates API.mp425.19MB

13 - APIs (POST requests are not needed for this course)/005 Including Parameters in a GET Request.mp410.8MB

13 - APIs (POST requests are not needed for this course)/006 More Functionalities of the Exchange Rates API.mp416.6MB

13 - APIs (POST requests are not needed for this course)/007 Coding a Simple Currency Conversion Calculator.mp422.44MB

13 - APIs (POST requests are not needed for this course)/008 iTunes API.mp439.61MB

13 - APIs (POST requests are not needed for this course)/010 iTunes API Structuring and Exporting the Data.mp412.86MB

13 - APIs (POST requests are not needed for this course)/011 Pagination GitHub API.mp428.21MB

14 - Data Cleaning and Data Preprocessing/001 Data Cleaning and Data Preprocessing.mp416.47MB

15 - pandas Series/001 .unique(), .nunique().mp426.29MB

15 - pandas Series/002 Converting Series into Arrays.mp419.86MB

15 - pandas Series/003 .sort_values().mp413.19MB

15 - pandas Series/004 Attribute and Method Chaining.mp414.76MB

15 - pandas Series/005 .sort_index().mp415.69MB

16 - pandas DataFrames/001 A Revision to pandas DataFrames.mp417.82MB

16 - pandas DataFrames/002 Common Attributes for Working with DataFrames.mp429.78MB

16 - pandas DataFrames/003 Data Selection in pandas DataFrames.mp437.28MB

16 - pandas DataFrames/004 Data Selection - Indexing with .iloc[].mp423.53MB

16 - pandas DataFrames/005 Data Selection - Indexing with .loc[].mp421.62MB

16 - pandas DataFrames/006 A Few Comments on Using .loc[] and .iloc[].mp476.91MB

17 - NumPy Fundamentals/001 Indexing in NumPy.mp414.87MB

17 - NumPy Fundamentals/002 Assigning Values in NumPy.mp410.14MB

17 - NumPy Fundamentals/003 Elementwise Properties of Arrays.mp414.92MB

17 - NumPy Fundamentals/004 Types of Data Supported by NumPy.mp418.13MB

17 - NumPy Fundamentals/005 Characteristics of NumPy Functions Part 1.mp423.18MB

17 - NumPy Fundamentals/006 Characteristics of NumPy Functions Part 2.mp410.14MB

18 - NumPy DataTypes/001 ndarrays.mp429.33MB

18 - NumPy DataTypes/002 Arrays vs Lists.mp416.58MB

18 - NumPy DataTypes/003 Strings vs Object vs Number.mp424.78MB

19 - Working with Arrays/001 Basic Slicing in NumPy.mp426.56MB

19 - Working with Arrays/002 Stepwise Slicing in NumPy.mp413.98MB

19 - Working with Arrays/003 Conditional Slicing in NumPy.mp416.14MB

19 - Working with Arrays/004 Dimensions and the Squeeze Function.mp418.26MB

20 - Generating Data with NumPy/001 Arrays of 0s and 1s.mp416.16MB

20 - Generating Data with NumPy/002 _like functions in NumPy.mp48.74MB

20 - Generating Data with NumPy/003 A Non-Random Sequence of Numbers.mp419.98MB

20 - Generating Data with NumPy/004 Random Generators and Seeds.mp419.32MB

20 - Generating Data with NumPy/005 Basic Random Functions in NumPy.mp414.84MB

20 - Generating Data with NumPy/006 Probability Distributions in NumPy.mp431.54MB

20 - Generating Data with NumPy/007 Applications of Random Data in NumPy.mp429.41MB

21 - Statistics with NumPy/001 Using Statistical Functions in NumPy.mp421.25MB

21 - Statistics with NumPy/002 Minimal and Maximal Values in NumPy.mp419.95MB

21 - Statistics with NumPy/003 Statistical Order Functions in NumPy.mp427.37MB

21 - Statistics with NumPy/004 Averages and Variance in NumPy.mp414.57MB

21 - Statistics with NumPy/005 Covariance and Correlation in NumPy.mp48.74MB

21 - Statistics with NumPy/006 Histograms in NumPy (Part 1).mp422.1MB

21 - Statistics with NumPy/007 Histograms in NumPy (Part 2).mp411.52MB

21 - Statistics with NumPy/008 NAN Equivalent Functions in NumPy.mp416.77MB

22 - NumPy - Preprocessing/001 Checking for Missing Values in Ndarrays.mp447.88MB

22 - NumPy - Preprocessing/002 Substituting Missing Values in Ndarrays.mp434.32MB

22 - NumPy - Preprocessing/003 Reshaping Ndarrays.mp424.59MB

22 - NumPy - Preprocessing/004 Removing Values from Ndarrays.mp419.93MB

22 - NumPy - Preprocessing/005 Sorting Ndarrays.mp455.27MB

22 - NumPy - Preprocessing/006 Argument Sort in NumPy.mp429.52MB

22 - NumPy - Preprocessing/007 Argument Where in NumPy.mp451.52MB

22 - NumPy - Preprocessing/008 Shuffling Ndarrays.mp432.96MB

22 - NumPy - Preprocessing/009 Casting Ndarrays.mp440.24MB

22 - NumPy - Preprocessing/010 Striping Values from Ndarrays.mp418.41MB

22 - NumPy - Preprocessing/011 Stacking Ndarrays.mp465.14MB

22 - NumPy - Preprocessing/012 Concatenating Ndarrays.mp435.68MB

22 - NumPy - Preprocessing/013 Finding Unique Values in Ndarrays.mp427.75MB

23 - A Loan Data Example with NumPy/001 Setting Up Introduction to the Practical Example.mp420.53MB

23 - A Loan Data Example with NumPy/002 Setting Up Importing the Data Set.mp436.9MB

23 - A Loan Data Example with NumPy/003 Setting Up Checking for Incomplete Data.mp417.14MB

23 - A Loan Data Example with NumPy/004 Setting Up Splitting the Dataset.mp419.76MB

23 - A Loan Data Example with NumPy/005 Setting Up Creating Checkpoints.mp411.01MB

23 - A Loan Data Example with NumPy/006 Manipulating Text Data Issue Date.mp414.92MB

23 - A Loan Data Example with NumPy/007 Manipulating Text Data Loan Status and Term.mp425.16MB

23 - A Loan Data Example with NumPy/008 Manipulating Text Data Grade and Sub Grade.mp441.2MB

23 - A Loan Data Example with NumPy/009 Manipulating Text Data Verification Status & URL.mp426.67MB

23 - A Loan Data Example with NumPy/010 Manipulating Text Data State Address.mp426.23MB

23 - A Loan Data Example with NumPy/011 Manipulating Text Data Converting Strings and Creating a Checkpoint.mp48.66MB

23 - A Loan Data Example with NumPy/012 Manipulating Numeric Data Substitute Filler Values.mp427.86MB

23 - A Loan Data Example with NumPy/013 Manipulating Numeric Data Currency Change – The Exchange Rate.mp418.99MB

23 - A Loan Data Example with NumPy/014 Manipulating Numeric Data Currency Change - From USD to EUR.mp431.45MB

23 - A Loan Data Example with NumPy/015 Completing the Dataset.mp444.04MB

24 - The Absenteeism Exercise - Introduction/001 An Introduction to the Absenteeism Exercise.mp43.65MB

24 - The Absenteeism Exercise - Introduction/002 The Absenteeism Exercise from a Business Perspective.mp47.19MB

24 - The Absenteeism Exercise - Introduction/003 The Dataset.mp45.66MB

25 - Solution to the Absenteeism Exercise/001 How to Complete the Absenteeism Exercise.mp46.23MB

25 - Solution to the Absenteeism Exercise/002 Eyeball Your Data First.mp454.25MB

25 - Solution to the Absenteeism Exercise/003 Note Programming vs the Rest of the World.mp418.03MB

25 - Solution to the Absenteeism Exercise/004 Using a Statistical Approach to Solve Our Exercise.mp49.9MB

25 - Solution to the Absenteeism Exercise/005 Dropping the 'ID' Column.mp441.33MB

25 - Solution to the Absenteeism Exercise/006 Analysis of the 'Reason for Absence' Column.mp417.18MB

25 - Solution to the Absenteeism Exercise/007 Splitting the Reasons for Absence into Multiple Dummy Variables.mp463.76MB

25 - Solution to the Absenteeism Exercise/008 Working with Dummy Variables - A Statistical Perspective.mp45.82MB

25 - Solution to the Absenteeism Exercise/009 Grouping the Reason for Absence Columns.mp451.32MB

25 - Solution to the Absenteeism Exercise/010 Concatenating Columns in a pandas DataFrame.mp419.77MB

25 - Solution to the Absenteeism Exercise/011 Reordering Columns in a DataFrame.mp47.2MB

25 - Solution to the Absenteeism Exercise/012 Working on the 'Date' Column.mp426.06MB

25 - Solution to the Absenteeism Exercise/013 Extracting the Month Value from the 'Date' Column.mp437.05MB

25 - Solution to the Absenteeism Exercise/014 Creating the 'Day of the Week' Column.mp423.33MB

25 - Solution to the Absenteeism Exercise/015 Understanding the Meaning of 5 More Columns.mp412.25MB

25 - Solution to the Absenteeism Exercise/016 Modifying the 'Education' Column.mp419.66MB

25 - Solution to the Absenteeism Exercise/017 Final Remarks on the Absenteeism Exercise.mp414.91MB

26 - Data Visualization/001 What Is Data Visualization and Why Is It Important.mp413.97MB

26 - Data Visualization/002 Why Learn Data Visualization.mp426.44MB

26 - Data Visualization/003 Choosing the Right Visualization – What Are Some Popular Approaches and Framewor.mp443.8MB

26 - Data Visualization/004 Introduction into Colors and Color Theory.mp456.19MB

26 - Data Visualization/005 Bar Chart - Introduction - General Theory and Getting to Know the Dataset.mp410.81MB

26 - Data Visualization/006 Bar Chart - How to Create a Bar Chart Using Python.mp431.86MB

26 - Data Visualization/007 Bar Chart – Interpreting the Bar Graph. How to Make a Good Bar Graph.mp48.2MB

26 - Data Visualization/008 Pie Chart - Introduction - General Theory and Dataset.mp422.69MB

26 - Data Visualization/009 Pie Chart - How to Create a Pie Chart Using Python.mp416.29MB

26 - Data Visualization/010 Pie Chart – Interpreting the Pie Chart.mp49.74MB

26 - Data Visualization/011 Pie Chart - Why You Should Never Create a Pie Graph.mp446.37MB

26 - Data Visualization/012 Stacked Area Chart - Introduction - General Theory. Getting to Know the Dataset.mp47.61MB

26 - Data Visualization/013 Stacked Area Chart - How to Create a Stacked Area Chart Using Python.mp425.04MB

26 - Data Visualization/014 Stacked Area Chart - Interpreting the Stacked Area Graph.mp49.6MB

26 - Data Visualization/015 Stacked Area Chart - How to Make a Good Stacked Area Chart.mp412.62MB

26 - Data Visualization/016 Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp45.05MB

26 - Data Visualization/017 Line Chart - How to Create a Line Chart in Python.mp440.29MB

26 - Data Visualization/018 Line Chart - Interpretation.mp432.7MB

26 - Data Visualization/019 Line Chart - How to Make a Good Line Chart.mp427.18MB

26 - Data Visualization/020 Histogram - Introduction - General Theory. Getting to Know the Dataset.mp414.34MB

26 - Data Visualization/021 Histogram - How to Create a Histogram Using Python.mp414.59MB

26 - Data Visualization/022 Histogram – Interpreting the Histogram.mp44.88MB

26 - Data Visualization/023 Histogram – Choosing the Number of Bins in a Histogram.mp421.1MB

26 - Data Visualization/024 Histogram - How to Make a Good Histogram.mp421.69MB

26 - Data Visualization/025 Scatter Plot - Introduction - General Theory. Getting to Know the Dataset.mp48.74MB

26 - Data Visualization/026 Scatter Plot - How to Create a Scatter Plot Using Python.mp429.78MB

26 - Data Visualization/027 Scatter Plot – Interpreting the Scatter Plot.mp410.21MB

26 - Data Visualization/028 Scatter Plot - How to Make a Good Scatter Plot.mp418.63MB

26 - Data Visualization/029 Regression Plot - Introduction - General Theory. Getting to Know the Dataset.mp49.38MB

26 - Data Visualization/030 Regression Plot - How to Create a Regression Scatter Plot Using Python.mp421.75MB

26 - Data Visualization/031 Regression Plot – Interpreting the Regression Scatter Plot.mp417.43MB

26 - Data Visualization/032 Regression Plot - How to Make a Good Regression Plot.mp412.35MB

26 - Data Visualization/033 Bar and Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp49.35MB

26 - Data Visualization/034 Bar and Line Chart - How to Create a Combination Bar and Line Graph Using Python.mp426.31MB

26 - Data Visualization/035 Bar and Line Chart – Interpreting the Combination Bar and Line Graph.mp47.74MB

26 - Data Visualization/036 Bar and Line Chart – How to Make a Good Bar and Line Graph.mp416.13MB

27 - Conclusion/001 Conclusion.mp416.19MB