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Pluralsight Path - Python for Data Analysts
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[TutsNode.com] - Pluralsight Path. Python for Data Analysts (2020) (Size: 3.00 GB) (Files: 1144)
[TutsNode.com] - Pluralsight Path. Python for Data Analysts (2020)
B1. Importing Data. Python Data Playbook (Xavier Morera, 2018)
4. Import Data into Python from JSON and XML Files
2. Importing Data into Python from JSON Using the JSON Library.mp4
2. Importing Data into Python from JSON Using the JSON Library.vtt
3. Importing Data into Python from XML Using the ElementTree XML API.vtt
1. Importing Data into Python from JSON and XML Files.vtt
3. Importing Data into Python from XML Using the ElementTree XML API.mp4
1. Importing Data into Python from JSON and XML Files.mp4
3. Importing CSV Data into Python Using csv and pandas
3. Importing Text and CSV Files Using pandas.vtt
3. Importing Text and CSV Files Using pandas.mp4
2. Importing CSV Files Using the Python csv Module.vtt
1. Importing CSV Data into Python Using csv and pandas.vtt
2. Importing CSV Files Using the Python csv Module.mp4
1. Importing CSV Data into Python Using csv and pandas.mp4
5. Import Data into Python from Excel Files
2. Importing Excel Files Using pandas.vtt
1. Importing Data into Python from Excel Files.vtt
2. Importing Excel Files Using pandas.mp4
1. Importing Data into Python from Excel Files.mp4
2. Importing Text Data into Python Using NumPy
2. Importing Flat Files and Numeric Data Using NumPy.vtt
1. Importing Text Data into Python Using NumPy.vtt
2. Importing Flat Files and Numeric Data Using NumPy.mp4
1. Importing Text Data into Python Using NumPy.mp4
7. Import Data into Python from Relational Databases
4. Working with Databases Using SQLAlchemy.vtt
2. Importing sqlite Database Files.vtt
5. Importing Data from Relational Databases with pandas (MySQL).vtt
7. Importing Relational Data.vtt
6. Working with PostgreSQL with psycopg2 and SQLAlchemy.vtt
1. Importing Data into Python from Relational Databases.vtt
3. Taking Advantage of pandas DataFrames When Querying sqlite.vtt
2. Importing sqlite Database Files.mp4
5. Importing Data from Relational Databases with pandas (MySQL).mp4
4. Working with Databases Using SQLAlchemy.mp4
7. Importing Relational Data.mp4
6. Working with PostgreSQL with psycopg2 and SQLAlchemy.mp4
3. Taking Advantage of pandas DataFrames When Querying sqlite.mp4
1. Importing Data into Python from Relational Databases.mp4
6. Import Data into Python from Common Binary Data File Formats
2. Reading SAS Files with pandas.vtt
6. Reading Pickle Files.vtt
4. Reading HDF5 Files.vtt
3. Reading Stata Files with pandas.vtt
1. Importing Data into Python from Common Binary Data File Fo
5. Reading Matlab Files.vtt
6. Reading Pickle Files.mp4
2. Reading SAS Files with pandas.mp4
4. Reading HDF5 Files.mp4
3. Reading Stata Files with pandas.mp4
5. Reading Matlab Files.mp4
playlist.m3u
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
exercise.7z
C3. Leveraging Online Resources for Python Analytics (Janani Ravi, 2019)
2. Getting Started with Python Analytics
01. Version Check.mp4
01. Version Check.vtt
13. Demo - Writing a Python Script for a Classification Model.vtt
11. Demo - Sharing Visualizations Online Using Plotly.vtt
04. Python for Data Analysts.vtt
06. Demo - Exploring Online Resources.vtt
08. Demo - Cleaning Data.vtt
05. Python Resources for Analysts.vtt
07. Workflows in Data Analytics.vtt
10. Demo - Visualizing Relationships in Data.vtt
12. Demo - Prototyping a Classifier.vtt
06. Demo - Exploring Online Resources.mp4
09. Demo - Summary Statistics and Basic Analysis.vtt
03. Prerequisites and Course Outline.vtt
02. Module Overview.vtt
14. Module Summary.vtt
13. Demo - Writing a Python Script for a Classification Model.mp4
11. Demo - Sharing Visualizations Online Using Plotly.mp4
08. Demo - Cleaning Data.mp4
10. Demo - Visualizing Relationships in Data.mp4
04. Python for Data Analysts.mp4
07. Workflows in Data Analytics.mp4
05. Python Resources for Analysts.mp4
12. Demo - Prototyping a Classifier.mp4
09. Demo - Summary Statistics and Basic Analysis.mp4
02. Module Overview.mp4
14. Module Summary.mp4
03. Prerequisites and Course Outline.mp4
3. Leveraging Online Resources for Python Analytics with BigML
04. Demo - Configuring Data Sources and Creating Dat
05. Demo - Data Preparation and Visualization.vtt
09. Demo - Batch and Individual Predictions.vtt
10. Demo - Clustering.vtt
07. Demo - Building Models.vtt
11. Demo - Anomaly Detection.vtt
02. Introducing Big ML.vtt
06. Demo - Splitting into Training and Test Subsets.
08. Demo - Evaluating Models.vtt
03. Demo - Getting Started with Big ML.vtt
12. Module Summary.vtt
01. Module Overview.vtt
05. Demo - Data Preparation and Visualization.mp4
09. Demo - Batch and Individual Predictions.mp4
07. Demo - Building Models.mp4
10. Demo - Clustering.mp4
11. Demo - Anomaly Detection.mp4
08. Demo - Evaluating Models.mp4
02. Introducing Big ML.mp4
03. Demo - Getting Started with Big ML.mp4
12. Module Summary.mp4
01. Module Overview.mp4
4. Working with Interactive Environment Using Google Colab
05. Demo - Interactive Forms.vtt
08. Demo - Building a Regression Model.vtt
07. Demo - Widgets.vtt
03. Demo - Introducing the Google Colab Interface.vtt
04. Demo - Colab Notebooks—Similar yet Different.vtt
06. Demo - Accessing Google Drive Contents from Colab.vt
09. Demo - Integrating with Github.vtt
02. Introducing Google Colab.vtt
10. Summary and Further Study.vtt
01. Module Overview.vtt
08. Demo - Building a Regression Model.mp4
07. Demo - Widgets.mp4
05. Demo - Interactive Forms.mp4
03. Demo - Introducing the Google Colab Interface.mp4
09. Demo - Integrating with Github.mp4
06. Demo - Accessing Google Drive Contents from Colab.mp
04. Demo - Colab Notebooks—Similar yet Different.mp4
02. Introducing Google Colab.mp4
10. Summary and Further Study.mp4
01. Module Overview.mp4
playlist.m3u
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
exercise.7z
A3. Programming Python Using an IDE (Xavier Morera, 2019)
3. Improving Your Productivity Programming in Python with an IDE
5. Running and Debugging Python Code with an IDE.vtt
1. Improving Your Productivity Programming in Python with an IDE.
4. Organizing, Navigating, Refactoring, and Styling Code.mp4
6. Integrating with Version Control Using an IDE.vtt
4. Organizing, Navigating, Refactoring, and Styling Code.vtt
3. Features That Improve Productivity Coding with an IDE.vtt
2. Customizing IDEs.vtt
5. Running and Debugging Python Code with an IDE.mp4
6. Integrating with Version Control Using an IDE.mp4
7. Working with Databases in Python Using an IDE.vtt
8. Unit Testing with an IDE.vtt
9. Takeaway.vtt
2. Customizing IDEs.mp4
3. Features That Improve Productivity Coding with an IDE.mp4
7. Working with Databases in Python Using an IDE.mp4
8. Unit Testing with an IDE.mp4
9. Takeaway.mp4
2. Programming Python Using an IDE! But Why And Which One
4. Configuring Python Features for Specific Code Editors.vtt
3. Overview of Available Code Editors for Python.vtt
4. Configuring Python Features for Specific Code Editors.mp4
3. Overview of Available Code Editors for Python.mp4
1. Programming Python Using an IDE! But Why And Which One.vtt
2. Code Editors vs. Integrated Development Environments.vtt
5. Takeaway.vtt
1. Programming Python Using an IDE! But Why And Which One.mp4
2. Code Editors vs. Integrated Development Environments.mp4
5. Takeaway.mp4
5. Final Takeaway
1. Final Takeaway.vtt
1. Final Takeaway.mp4
4. Leveraging a Python IDE for Data Science
6. Cloudera Data Science Workbench for Data Science at Scale.vtt
4. Using Jupyter Notebook for Data Science.vtt
3. Working with an IDE Built for Scientific Python - Spyder.vtt
5. Using Apache Zeppelin for Data Science.vtt
7. Takeaway.vtt
1. Leveraging a Python IDE for Data Science.vtt
2. Leveraging Data Science and Scientific Tools in PyCharm.vtt
6. Cloudera Data Science Workbench for Data Science at Scale.mp4
4. Using Jupyter Notebook for Data Science.mp4
2. Leveraging Data Science and Scientific Tools in PyCharm.mp4
3. Working with an IDE Built for Scientific Python - Spyder.mp4
5. Using Apache Zeppelin for Data Science.mp4
1. Leveraging a Python IDE for Data Science.mp4
7. Takeaway.mp4
playlist.m3u
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
exercise.7z
A1. Building Your First Python Analytics Solution (Janani Ravi, 2019)
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
2. Getting Started with Python for Analytics
01. Module Overview.vtt
02. Prerequisites and Course Outline.vtt
13. Module Summary.vtt
03. Python for Data Analytics.vtt
04. Python Development Environments.vtt
05. Python Packages.vtt
06. Demo - Windows - Installing Python and Using Pip to Install Packages.
08. Demo - MacOS - Using Pip to Install Packages.vtt
12. Demo - Using Online Editors to Write Python Code.vtt
07. Demo - MacOS - Using Brew to Install Python 3.vtt
10. Demo - Editing a Python Script Using Nano and Vim.vtt
09. Demo - Installing and Working with Virtual Environments.vtt
11. Demo - Editing a Python Script Using SublimeText.vtt
07. Demo - MacOS - Using Brew to Install Python 3.mp4
03. Python for Data Analytics.mp4
08. Demo - MacOS - Using Pip to Install Packages.mp4
09. Demo - Installing and Working with Virtual Environments.mp4
04. Python Development Environments.mp4
12. Demo - Using Online Editors to Write Python Code.mp4
11. Demo - Editing a Python Script Using SublimeText.mp4
05. Python Packages.mp4
10. Demo - Editing a Python Script Using Nano and Vim.mp4
13. Module Summary.mp4
01. Module Overview.mp4
02. Prerequisites and Course Outline.mp4
3. Working with Python Using Anaconda
01. Module Overview.vtt
12. Module Summary.vtt
04. Demo - Mac OS Installing Anaconda and Running Jupyter Notebooks.vtt
11. Demo - Wrangling and Visualizing Data.vtt
08. Demo - Exploring Magic Commands.vtt
07. Demo - Restarting and Switching Kernels.vtt
09. Demo - Line Magic and Cell Magic Commands.vtt
06. Demo - Executing Code in Jupyter.vtt
10. Demo - Exploring Interactive Widgets.vtt
02. Introducing Jupyter Notebooks.vtt
05. Demo - Installing the Python 2 Kernel along with Python 3.vtt
03. Demo - Windows Installing Anaconda and Running Jupyter Notebooks.vtt
04. Demo - Mac OS Installing Anaconda and Running Jupyter Notebooks.mp4
11. Demo - Wrangling and Visualizing Data.mp4
08. Demo - Exploring Magic Commands.mp4
07. Demo - Restarting and Switching Kernels.mp4
10. Demo - Exploring Interactive Widgets.mp4
05. Demo - Installing the Python 2 Kernel along with Python 3.mp4
09. Demo - Line Magic and Cell Magic Commands.mp4
03. Demo - Windows Installing Anaconda and Running Jupyter Notebooks.mp4
06. Demo - Executing Code in Jupyter.mp4
02. Introducing Jupyter Notebooks.mp4
12. Module Summary.mp4
01. Module Overview.mp4
4. Working with Python Using Other IDEs
04. Demo - Running and Debugging Code with IDLE.vtt
06. Demo - Running and Debugging Code with Eclipse.vtt
01. Module Overview.vtt
09. Demo - Working with Spyder.vtt
08. Demo - Running and Debugging Code with PyCharm.vtt
10. Module Summary.vtt
03. Demo - Installing and Setting up IDLE.vtt
05. Demo - Installing Eclipse and Setting up the PyDev Plugin.vtt
07. Demo - Installing and Setting up PyCharm.vtt
02. Exploring Popular IDEs for Python.vtt
08. Demo - Running and Debugging Code with PyCharm.mp4
06. Demo - Running and Debugging Code with Eclipse.mp4
09. Demo - Working with Spyder.mp4
04. Demo - Running and Debugging Code with IDLE.mp4
05. Demo - Installing Eclipse and Setting up the PyDev Plugin.mp4
07. Demo - Installing and Setting up PyCharm.mp4
03. Demo - Installing and Setting up IDLE.mp4
02. Exploring Popular IDEs for Python.mp4
01. Module Overview.mp4
10. Module Summary.mp4
5. Working with Python on the Cloud
6. Demo - Building a Simple Regression Model on Datalab.vtt
1. Module Overview.vtt
5. Demo - Setting up and Connecting to Cloud Datalab on the GCP.vtt
9. Summary and Further Study.vtt
8. Demo - Executing Code to Integrate with S3 Buckets.vtt
4. Demo - Analyzing and Visualizing Data on Azure Notebooks.vtt
3. Demo - Getting Started with Azure Notebooks.vtt
7. Demo - Setting up a SageMaker Notebook Instance on AWS.vtt
2. Jupyter on the Cloud.vtt
4. Demo - Analyzing and Visualizing Data on Azure Notebooks.mp4
5. Demo - Setting up and Connecting to Cloud Datalab on the GCP.mp4
8. Demo - Executing Code to Integrate with S3 Buckets.mp4
6. Demo - Building a Simple Regression Model on Datalab.mp4
7. Demo - Setting up a SageMaker Notebook Instance on AWS.mp4
3. Demo - Getting Started with Azure Notebooks.mp4
2. Jupyter on the Cloud.mp4
9. Summary and Further Study.mp4
1. Module Overview.mp4
playlist.m3u
exercise.7z
B2. Data Wrangling with Python (Pratheerth Padman, 2020)
5. Reshaping Data with Python
7. Summary.mp4
2. Introduction to Data Reshaping.vtt
5. Reshape Data Using the Stack and Unstack Functions.vtt
3. Reshape Long Data to Wide Data with the Pivot Function.vtt
4. Reshape Wide Data to Long Using the Melt Function.vtt
6. Reshaping and Aggregation with Pivot Table.vtt
1. Module Introduction.vtt
7. Summary.vtt
3. Reshape Long Data to Wide Data with the Pivot Function.mp4
5. Reshape Data Using the Stack and Unstack Functions.mp4
2. Introduction to Data Reshaping.mp4
4. Reshape Wide Data to Long Using the Melt Function.mp4
6. Reshaping and Aggregation with Pivot Table.mp4
1. Module Introduction.mp4
2. Concatenating and Merging Data from Different Sources
3. Concatenating Datasets.vtt
4. Merging Datasets.vtt
6. The How Parameter.vtt
5. Merge Keys.vtt
7. Demo - Disambiguating Merged Columns and Updating Dataframes.vtt
1. Course and Module Introduction.vtt
2. Software and Course Prerequisites.vtt
8. Summary.vtt
3. Concatenating Datasets.mp4
4. Merging Datasets.mp4
6. The How Parameter.mp4
5. Merge Keys.mp4
7. Demo - Disambiguating Merged Columns and Updating Dataframes.mp4
1. Course and Module Introduction.mp4
8. Summary.mp4
2. Software and Course Prerequisites.mp4
6. Data Encoding with Python
5. Create Frequency Table with the Crosstab Function.vtt
4. Create Dummy Variables with Pandas.vtt
3. Demo - Convert Categorical Values Using One-hot Encoding.vtt
2. One-hot Encoding.vtt
6. Summary and Feedback.vtt
1. Module Introduction.vtt
5. Create Frequency Table with the Crosstab Function.mp4
3. Demo - Convert Categorical Values Using One-hot Encoding.mp4
4. Create Dummy Variables with Pandas.mp4
2. One-hot Encoding.mp4
6. Summary and Feedback.mp4
1. Module Introduction.mp4
3. Combining Data into Groups
3. Demo - Why and How to Use the GroupBy Function.vtt
4. Filter and Transform with GroupBy.vtt
2. The GroupBy Function.vtt
5. Demo - Grouping Multi-index Data.vtt
1. Module Introduction.vtt
3. Demo - Why and How to Use the GroupBy Function.mp4
4. Filter and Transform with GroupBy.mp4
5. Demo - Grouping Multi-index Data.mp4
2. The GroupBy Function.mp4
1. Module Introduction.mp4
4. Normalizing Data with Pandas
6. Points to Consider for Data Normalization and Summary.vtt
5. Z-score Normalization.vtt
2. Normalizing Data - What and Why.vtt
4. Min-max Scaling.vtt
3. Simple Feature Scaling.vtt
1. Module Introduction.vtt
6. Points to Consider for Data Normalization and Summary.mp4
5. Z-score Normalization.mp4
3. Simple Feature Scaling.mp4
4. Min-max Scaling.mp4
2. Normalizing Data - What and Why.mp4
1. Module Introduction.mp4
playlist.m3u
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
exercise.7z
B4. Pygal. Python Data Playbook (Kishan Iyer, 2019)
3. Plotting Basic Pygal Charts
10. Summary.mp4
05. Defining Styles and Configs.vtt
09. Exploring Real Data with XY Plots.vtt
02. Construct a Basic Pie Chart.vtt
04. Chart, Serie, and Value Configurations.vtt
06. Introducing Line and Datetimeline Charts.vtt
03. Donut and Half Pie Charts.vtt
07. Plotting Real Data with Line and Dateline Charts.vtt
08. Introducing XY Plots.vtt
01. Overview.vtt
10. Summary.vtt
09. Exploring Real Data with XY Plots.mp4
02. Construct a Basic Pie Chart.mp4
04. Chart, Serie, and Value Configurations.mp4
05. Defining Styles and Configs.mp4
06. Introducing Line and Datetimeline Charts.mp4
07. Plotting Real Data with Line and Dateline Charts.mp4
03. Donut and Half Pie Charts.mp4
08. Introducing XY Plots.mp4
01. Overview.mp4
4. Visualizing Complex Data with Advanced Charts
10. Constructing a Dot Plot.vtt
05. Constructing a Map Visualization.vtt
06. Generating Radar Plots.vtt
12. Building a Treemap Visualization.vtt
01. Overview.mp4
04. Visualizing Distributions with Box Plots.vtt
08. Creating Gauge Plots.vtt
03. Pyramid Charts.vtt
07. Constructing a Funnel Visualization.vtt
09. Solid Gauge Plots.vtt
02. Plotting Histograms.vtt
13. Summary.mp4
11. Representing Negative Values in a Dot Plot.vtt
01. Overview.vtt
13. Summary.vtt
06. Generating Radar Plots.mp4
10. Constructing a Dot Plot.mp4
05. Constructing a Map Visualization.mp4
04. Visualizing Distributions with Box Plots.mp4
12. Building a Treemap Visualization.mp4
08. Creating Gauge Plots.mp4
03. Pyramid Charts.mp4
07. Constructing a Funnel Visualization.mp4
02. Plotting Histograms.mp4
09. Solid Gauge Plots.mp4
11. Representing Negative Values in a Dot Plot.mp4
2. Getting Data into Pygal
7. Plot Data from a CSV File.vtt
5. Install Pygal.vtt
6. Interacting with Pygal Charts.vtt
8. Stacked Bar Charts.vtt
3. Vector and Raster Images.vtt
4. The SVG Format.vtt
2. Introducing Pygal.vtt
1. Overview.vtt
7. Plot Data from a CSV File.mp4
6. Interacting with Pygal Charts.mp4
5. Install Pygal.mp4
3. Vector and Raster Images.mp4
8. Stacked Bar Charts.mp4
2. Introducing Pygal.mp4
4. The SVG Format.mp4
1. Overview.mp4
5. Rendering Out Charts
2. Rendering Charts to Image Files.vtt
6. Building a Flask App to Render Pygal Charts.vtt
4. PyQuery and Pygal.vtt
3. Rendering Charts to Specialized Formats.vtt
5. Building Sparklines.vtt
7. Testing the Flask App.vtt
8. Summary.vtt
1. Overview.vtt
3. Rendering Charts to Specialized Formats.mp4
2. Rendering Charts to Image Files.mp4
4. PyQuery and Pygal.mp4
6. Building a Flask App to Render Pygal Charts.mp4
5. Building Sparklines.mp4
7. Testing the Flask App.mp4
8. Summary.mp4
1. Overview.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
exercise.7z
C1. Understanding Databases with SQLAlchemy. Python Data Playbook (Xavier Morera, 2019)
2. Up and Running with SQLAlchemy
6. Takeaway.vtt
3. Loading Data Using SQLAlchemy.vtt
5. Visualizing and Graphing Data with Matplotlib.vtt
2. Installing and Importing SQLAlchemy.vtt
4. Using Pandas and SQLAlchemy to Load, Work, and View Your Data.v
1. Up and Running with SQLAlchemy.vtt
3. Loading Data Using SQLAlchemy.mp4
2. Installing and Importing SQLAlchemy.mp4
5. Visualizing and Graphing Data with Matplotlib.mp4
4. Using Pandas and SQLAlchemy to Load, Work, and View Your Data.m
1. Up and Running with SQLAlchemy.mp4
6. Takeaway.mp4
3. Querying with SQLAlchemy
06. The Declarative API.vtt
07. More Querying and Database Functions.vtt
05. Object-relational Mapper (ORM) and Classical Mapping.vtt
03. Connecting to Databases - Connectors and the Connection String.vtt
02. Picking a Database.vtt
09. Working with Hierarchical Tables.vtt
10. Takeaway.vtt
01. Querying with SQLAlchemy.vtt
08. Using Joins.vtt
04. Querying with SQL.vtt
07. More Querying and Database Functions.mp4
06. The Declarative API.mp4
03. Connecting to Databases - Connectors and the Connection String.mp4
05. Object-relational Mapper (ORM) and Classical Mapping.mp4
02. Picking a Database.mp4
09. Working with Hierarchical Tables.mp4
04. Querying with SQL.mp4
08. Using Joins.mp4
10. Takeaway.mp4
01. Querying with SQLAlchemy.mp4
4. Creating Your Database
4. Primary Keys, Constraints, and Data Defaults.vtt
5. Inserting Data - Single and Multiple Rows.vtt
3. Creating Tables.vtt
2. Creating Databases.vtt
6. Loading a CSV into a Table.vtt
1. Creating Databases with SQLAlchemy.vtt
7. Takeaway.vtt
4. Primary Keys, Constraints, and Data Defaults.mp4
5. Inserting Data - Single and Multiple Rows.mp4
3. Creating Tables.mp4
2. Creating Databases.mp4
6. Loading a CSV into a Table.mp4
1. Creating Databases with SQLAlchemy.mp4
7. Takeaway.mp4
5. Manipulating Your Database
2. Updating Data in a Database.vtt
4. Deleting Data from a Database.vtt
5. Deleting Tables.vtt
6. Takeaway.vtt
3. Correlated Updates.vtt
1. Manipulating Databases with SQLAlchemy.vtt
2. Updating Data in a Database.mp4
4. Deleting Data from a Database.mp4
5. Deleting Tables.mp4
3. Correlated Updates.mp4
6. Takeaway.mp4
1. Manipulating Databases with SQLAlchemy.mp4
6. Final Takeaway
1. Final Takeaway.vtt
1. Final Takeaway.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
exercise.7z
A2. Python for Data Analysts (Janani Ravi, 2019)
exercise.7z
4. Using Python for Complex Interconnected Calculations
10. Demo - Conditional Looping Using While Loops.vtt
04. Demo - If Else Statements.vtt
02. Transactional and Analytical Processing.vtt
07. Demo - Iterating over List Elements Using a For Loop.vtt
01. Module Overview.vtt
03. Demo - If Statements for Conditional Branching.vtt
11. Demo - Break.vtt
13. Module Summary.vtt
12. Demo - Continue and Pass.vtt
08. Demo - Using For Loops with the Range Function.vtt
06. Demo - If-elif for Multiple Conditional Checks.vtt
05. Demo - Using if with Lists and Dictionary Elements.vtt
09. Demo - Iterating over Dictionary Elements Using a For Loop.vtt
10. Demo - Conditional Looping Using While Loops.mp4
04. Demo - If Else Statements.mp4
07. Demo - Iterating over List Elements Using a For Loop.mp4
02. Transactional and Analytical Processing.mp4
03. Demo - If Statements for Conditional Branching.mp4
11. Demo - Break.mp4
12. Demo - Continue and Pass.mp4
06. Demo - If-elif for Multiple Conditional Checks.mp4
05. Demo - Using if with Lists and Dictionary Elements.mp4
08. Demo - Using For Loops with the Range Function.mp4
09. Demo - Iterating over Dictionary Elements Using a For Loop.mp4
01. Module Overview.mp4
13. Module Summary.mp4
5. Implementing Code Reuse Using Functions in Python
02. Demo - Defining and Invoking Custom Functions.vtt
09. Demo - First Class Functions.vtt
05. Demo - Reassignment of Variables within Functions.vtt
07. Demo - Invoking Functions with Keyword Arguments.vtt
04. Demo - Returning Values from Functions.vtt
01. Module Overview.vtt
10. Module Summary.vtt
06. Demo - Modification of Complex Types within Functions.vtt
03. Demo - Passing Input Arguments to Functions.vtt
08. Demo - Assigning Default Values for Input Arguments.vtt
05. Demo - Reassignment of Variables within Functions.mp4
02. Demo - Defining and Invoking Custom Functions.mp4
09. Demo - First Class Functions.mp4
07. Demo - Invoking Functions with Keyword Arguments.mp4
04. Demo - Returning Values from Functions.mp4
06. Demo - Modification of Complex Types within Functions.mp4
08. Demo - Assigning Default Values for Input Arguments.mp4
03. Demo - Passing Input Arguments to Functions.mp4
01. Module Overview.mp4
10. Module Summary.mp4
6. Loading and Saving Data Using Python
5. Demo - Working with the Command Line Processes and Environment Variables.vtt
7. Demo - Overwriting and Appending Content to a File.vtt
6. Demo - Reading the Contents of a File.vtt
8. Demo - Working with CSV and JSON Files.vtt
3. Demo - Introducing NumPy.vtt
1. Module Overview.vtt
9. Module Summary.vtt
2. Demo - Working with the Math Module.vtt
4. Demo - Introducing Pandas.vtt
5. Demo - Working with the Command Line Processes and Environment Variables.mp4
7. Demo - Overwriting and Appending Content to a File.mp4
6. Demo - Reading the Contents of a File.mp4
8. Demo - Working with CSV and JSON Files.mp4
3. Demo - Introducing NumPy.mp4
2. Demo - Working with the Math Module.mp4
4. Demo - Introducing Pandas.mp4
9. Module Summary.mp4
1. Module Overview.mp4
3. Leveraging Built-in Functions and Complex Data Types
2. Demo - Introducing Built-in Functions.vtt
3. Demo - String Functions, Return Values, and Nested Function Invocations.vtt
8. Demo - Introducing Dictionaries.vtt
4. Demo - Introducing Lists.vtt
1. Module Overview.vtt
9. Module Summary.vtt
5. Demo - List Slicing Operations and List Functions.vtt
7. Demo - Introducing Tuples.vtt
6. Demo - Concatenating and Copying Lists.vtt
2. Demo - Introducing Built-in Functions.mp4
3. Demo - String Functions, Return Values, and Nested Function Invocations.mp4
8. Demo - Introducing Dictionaries.mp4
4. Demo - Introducing Lists.mp4
5. Demo - List Slicing Operations and List Functions.mp4
7. Demo - Introducing Tuples.mp4
6. Demo - Concatenating and Copying Lists.mp4
1. Module Overview.mp4
9. Module Summary.mp4
2. Getting Started with Python for Data Analysis
07. Demo - Simple Expressions.vtt
09. Demo - Variables.vtt
01. Module Overview.vtt
02. Prerequisites and Course Outline.vtt
04. Essential Analytical Building Blocks.vtt
12. Module Summary.vtt
05. Demo - Installing Anaconda Python on MacOS.vtt
08. Demo - Logical Operations.vtt
10. Demo - Basic Types and Type Conversions.vtt
06. Demo - Installing Anaconda Python on Windows.vtt
11. Demo - Simple Strings and Multi-line Strings.vtt
03. Python for Data Analysts.vtt
07. Demo - Simple Expressions.mp4
09. Demo - Variables.mp4
05. Demo - Installing Anaconda Python on MacOS.mp4
06. Demo - Installing Anaconda Python on Windows.mp4
08. Demo - Logical Operations.mp4
10. Demo - Basic Types and Type Conversions.mp4
04. Essential Analytical Building Blocks.mp4
11. Demo - Simple Strings and Multi-line Strings.mp4
03. Python for Data Analysts.mp4
12. Module Summary.mp4
01. Module Overview.mp4
02. Prerequisites and Course Outline.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
C2. Web Scraping. Python Data Playbook (Ian Ozsvald, 2019)
3. Understanding Your Scraped Data
05. Extracting Information from a Scraped Division.vtt
11. Adding a Test to Verify Our Regular Expression Processing.vtt
02. Understanding the HTML, CSS and Structure of Our Target Page.vtt
08. Building the Scraper Module Using PyCharm.vtt
01. A Primer on HTML and CSS.vtt
04. Using BeautifulSoup4 to Navigate Our Scraped Data.vtt
06. Using Selectors as an Alternative to the Find Method.vtt
03. Coming up with a Strategy for a More Complicated Web Page.vtt
07. Advice and Strategy for Scraping.vtt
10. Refactoring Our Code and Caching Our Scraped Data.vtt
09. Dealing with Missing Data during the Scrape.vtt
04. Using BeautifulSoup4 to Navigate Our Scraped Data.mp4
08. Building the Scraper Module Using PyCharm.mp4
11. Adding a Test to Verify Our Regular Expression Processing.mp4
02. Understanding the HTML, CSS and Structure of Our Target Page.mp4
10. Refactoring Our Code and Caching Our Scraped Data.mp4
09. Dealing with Missing Data during the Scrape.mp4
05. Extracting Information from a Scraped Division.mp4
03. Coming up with a Strategy for a More Complicated Web Page.mp4
06. Using Selectors as an Alternative to the Find Method.mp4
01. A Primer on HTML and CSS.mp4
07. Advice and Strategy for Scraping.mp4
2. Setting Up BeautifulSoup
2. Reviewing Our Target Auto-MPG Web Page.vtt
3. The Complicated Difference between Dynamic and Static Web Pages.vtt
1. General Strategies for Scraping Web Pages.vtt
2. Reviewing Our Target Auto-MPG Web Page.mp4
3. The Complicated Difference between Dynamic and Static Web Pages.mp4
1. General Strategies for Scraping Web Pages.mp4
4. Making Scraped Data Usable
3. Exploratory Data Analysis Strategy.vtt
4. Reviewing Our Hypothesis.vtt
5. Investigating Relationships between MPG and Weight.vtt
9. Telling a Data Story to Explain Our Discoveries.vtt
2. Getting a Data Overview with Pandas.vtt
1. Exporting Scraped Data to a CSV File.vtt
8. Understanding Brands and Territories with Text Processing.vtt
7. Looking at MPG over the Years.vtt
6. Understanding How Cylinders and Displacement Are Related.vtt
3. Exploratory Data Analysis Strategy.mp4
1. Exporting Scraped Data to a CSV File.mp4
5. Investigating Relationships between MPG and Weight.mp4
4. Reviewing Our Hypothesis.mp4
2. Getting a Data Overview with Pandas.mp4
9. Telling a Data Story to Explain Our Discoveries.mp4
8. Understanding Brands and Territories with Text Processing.mp4
7. Looking at MPG over the Years.mp4
6. Understanding How Cylinders and Displacement Are Related.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
exercise.7z
scr.png
A4. Create and Share Analytics with Jupyter Notebooks (Janani Ravi, 2019)
4. Creating Shareable Analyses in Jupyter Notebooks
3. Demo - Exploring Interactive Widgets.vtt
2. Demo - Analyzing and Visualizing Data.vtt
4. Demo - Adding Interactivity to Custom Functions.vtt
6. Demo - Share Notebooks on Github.vtt
5. Demo - Save, Checkpoint, and Export Notebooks.vtt
1. Module Overview.vtt
7. Module Summary.vtt
6. Demo - Share Notebooks on Github.mp4
2. Demo - Analyzing and Visualizing Data.mp4
3. Demo - Exploring Interactive Widgets.mp4
4. Demo - Adding Interactivity to Custom Functions.mp4
5. Demo - Save, Checkpoint, and Export Notebooks.mp4
7. Module Summary.mp4
1. Module Overview.mp4
3. Understanding Jupyter Notebooks
8. Demo - Exploring Line and Cell Magic Commands.vtt
2. Demo - Exploring the Notebook Interface.vtt
3. Demo - Restarting the Kernel.vtt
6. Demo - Using Python 2 and Python 3 Kernels.vtt
5. Demo - Notebook Limits and Shutting down Kernels.vtt
4. Demo - Customizing Shortcuts.vtt
7. Demo - Using R and Python 3 Kernels.vtt
1. Module Overview.vtt
9. Module Summary.vtt
8. Demo - Exploring Line and Cell Magic Commands.mp4
2. Demo - Exploring the Notebook Interface.mp4
6. Demo - Using Python 2 and Python 3 Kernels.mp4
4. Demo - Customizing Shortcuts.mp4
5. Demo - Notebook Limits and Shutting down Kernels.mp4
3. Demo - Restarting the Kernel.mp4
7. Demo - Using R and Python 3 Kernels.mp4
9. Module Summary.mp4
1. Module Overview.mp4
2. Getting Started with Jupyter Notebooks
03. Introducing Jupyter Notebooks.vtt
04. Demo - Windows - Installing Anaconda and Jupyter Notebooks.vtt
06. Demo - MacOS - Installing Anaconda and Jupyter Notebooks.vtt
08. Demo - Running Jupyter Notebooks and Jupyter Lab in Docker Container
09. Demo - MacOS - Installing Jupyter Lab Using Pip.vtt
05. Demo - Windows - Installing Jupyter Notebooks Using Pip.vtt
07. Demo - MacOS - Installing Anaconda and Jupyter Notebooks Using the C
10. Module Summary.vtt
01. Module Overview.vtt
02. Prerequisites and Course Outline.vtt
06. Demo - MacOS - Installing Anaconda and Jupyter Notebooks.mp4
09. Demo - MacOS - Installing Jupyter Lab Using Pip.mp4
04. Demo - Windows - Installing Anaconda and Jupyter Notebooks.mp4
05. Demo - Windows - Installing Jupyter Notebooks Using Pip.mp4
03. Introducing Jupyter Notebooks.mp4
01. Module Overview.mp4
10. Module Summary.mp4
02. Prerequisites and Course Outline.mp4
5. Working with Cloud-hosted Jupyter Notebooks
3. Demo - Creating and Working with Notebook Instances on Amazon Sa
6. Demo - Hosted Notebooks on a GCP Deep Learning Virtual Machine.v
2. Running Hosted Jupyter Notebooks on the Cloud.vtt
5. Demo - Exploring and Working with Azure Notebooks.vtt
1. Module Overview.vtt
4. Demo - Uploading Notebooks to SageMaker and Using the Terminal W
7. Demo - Uploading Files and Running Code on GCP.vtt
8. Summary and Further Study.vtt
6. Demo - Hosted Notebooks on a GCP Deep Learning Virtual Machine.m
5. Demo - Exploring and Working with Azure Notebooks.mp4
7. Demo - Uploading Files and Running Code on GCP.mp4
2. Running Hosted Jupyter Notebooks on the Cloud.mp4
1. Module Overview.mp4
8. Summary and Further Study.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
exercise.7z
B3. Cleaning Data. Python Data Playbook (Chris Achard, 2018)
5. Handling Bad, Missing, and Duplicate Data
6. Identifying and Dropping Duplicate Data.vtt
3. Replacing Bad Data with NaN.vtt
5. Dropping Rows of Data.vtt
1. Introduction.vtt
7. Review.vtt
2. Stripping White Space.vtt
4. Filling Missing Data with a Value.vtt
6. Identifying and Dropping Duplicate Data.mp4
3. Replacing Bad Data with NaN.mp4
5. Dropping Rows of Data.mp4
2. Stripping White Space.mp4
4. Filling Missing Data with a Value.mp4
7. Review.mp4
1. Introduction.mp4
4. Indexing and Filtering Datasets
5. Filtering Data with str.contains.vtt
4. Using .iloc to Access Specific Rows or Columns.vtt
3. Data Indexing with .loc.vtt
2. Direct Filtering with Square Brackets.vtt
6. Review.vtt
1. Introduction.vtt
5. Filtering Data with str.contains.mp4
4. Using .iloc to Access Specific Rows or Columns.mp4
2. Direct Filtering with Square Brackets.mp4
3. Data Indexing with .loc.mp4
6. Review.mp4
1. Introduction.mp4
2. Understanding Your Data
2. Viewing and Converting Types.vtt
5. Transforming Data.vtt
1. Introduction.vtt
3. Aggregating Data.vtt
4. Normalizing Data.vtt
6. Filtering Data.vtt
7. Review.vtt
2. Viewing and Converting Types.mp4
3. Aggregating Data.mp4
5. Transforming Data.mp4
4. Normalizing Data.mp4
6. Filtering Data.mp4
1. Introduction.mp4
7. Review.mp4
3. Removing and Fixing Columns with pandas
4. Renaming Columns.vtt
2. Dropping Columns.vtt
1. Introduction.vtt
3. Changing Column Casing.vtt
5. Review.vtt
2. Dropping Columns.mp4
4. Renaming Columns.mp4
3. Changing Column Casing.mp4
1. Introduction.mp4
5. Review.mp4
1. Course Overview
1. Course Overview.vtt
1. Course Overview.mp4
playlist.m3u
exercise.7z
TutsNode.com.txt
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