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Language: English
Category: Tutorials
Title: Udemy - Learning Python for Data Analysis and Visualization
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[FreeCourseLab.com] Udemy - Learning Python for Data Analysis and Visualization 1. Intro to Course and Python
  • 1. Course Intro.mp4 (5.9 MB)
  • 1. Course Intro.vtt (5.2 KB)
  • 2. Course FAQs.html (6.9 KB)
10. Machine Learning
  • 1. Introduction to Machine Learning with SciKit Learn.mp4 (17.9 MB)
  • 1. Introduction to Machine Learning with SciKit Learn.vtt (17.8 KB)
  • 10. Multi Class Classification Part 1 - Logistic Regression.mp4 (26.8 MB)
  • 10. Multi Class Classification Part 1 - Logistic Regression.vtt (20.8 KB)
  • 11. Multi Class Classification Part 2 - k Nearest Neighbor.mp4 (30.6 MB)
  • 11. Multi Class Classification Part 2 - k Nearest Neighbor.vtt (25.5 KB)
  • 12. Support Vector Machines Part 1.mp4 (23.5 MB)
  • 12. Support Vector Machines Part 1.vtt (16.7 KB)
  • 13. Support Vector Machines - Part 2.mp4 (36.0 MB)
  • 13. Support Vector Machines - Part 2.vtt (31.1 KB)
  • 14. Naive Bayes Part 1.mp4 (14.0 MB)
  • 14. Naive Bayes Part 1.vtt (12.8 KB)
  • 15. Naive Bayes Part 2.mp4 (23.2 MB)
  • 15. Naive Bayes Part 2.vtt (15.0 KB)
  • 16. Decision Trees and Random Forests.mp4 (152.9 MB)
  • 16. Decision Trees and Random Forests.vtt (37.5 KB)
  • 17. Natural Language Processing Part 1.mp4 (43.9 MB)
  • 17. Natural Language Processing Part 1.vtt (9.7 KB)
  • 18. Natural Language Processing Part 2.mp4 (59.7 MB)
  • 18. Natural Language Processing Part 2.vtt (18.6 KB)
  • 19. Natural Language Processing Part 3.mp4 (92.6 MB)
  • 19. Natural Language Processing Part 3.vtt (25.0 KB)
  • 2. Linear Regression Part 1.mp4 (24.2 MB)
  • 2. Linear Regression Part 1.vtt (10.9 MB)
  • 20. Natural Language Processing Part 4.mp4 (67.1 MB)
  • 20. Natural Language Processing Part 4.vtt (18.5 KB)
  • 3. Linear Regression Part 2.mp4 (22.5 MB)
  • 3. Linear Regression Part 2.vtt (22.5 MB)
  • 4. Linear Regression Part 3.mp4 (27.2 MB)
  • 4. Linear Regression Part 3.vtt (23.3 KB)
  • 5. Linear Regression Part 4.mp4 (30.9 MB)
  • 5. Linear Regression Part 4.vtt (29.5 KB)
  • 6. Logistic Regression Part 1.mp4 (25.0 MB)
  • 6. Logistic Regression Part 1.vtt (18.3 KB)
  • 7. Logistic Regression Part 2.mp4 (20.8 MB)
  • 7. Logistic Regression Part 2.vtt (16.8 KB)
  • 8. Logistic Regression Part 3.mp4 (16.5 MB)
  • 8. Logistic Regression Part 3.vtt (13.0 KB)
  • 9. Logistic Regression Part 4.mp4 (35.3 MB)
  • 9. Logistic Regression Part 4.vtt (24.5 KB)
11. Appendix Statistics Overview
  • 1. Intro to Appendix B.mp4 (3.0 MB)
  • 1. Intro to Appendix B.vtt (4.2 KB)
  • 1.1 Viewer Link For Stats Notes.txt (0.1 KB)
  • 10. Chi Square Test and Distribution.mp4 (5.6 MB)
  • 10. Chi Square Test and Distribution.vtt (3.9 KB)
  • 11. Bayes Theorem.mp4 (14.5 MB)
  • 11. Bayes Theorem.vtt (12.7 KB)
  • 2. Discrete Uniform Distribution.mp4 (8.7 MB)
  • 2. Discrete Uniform Distribution.vtt (9.2 KB)
  • 3. Continuous Uniform Distribution.mp4 (9.9 MB)
  • 3. Continuous Uniform Distribution.vtt (9.8 KB)
  • 4. Binomial Distribution.mp4 (17.0 MB)
  • 4. Binomial Distribution.vtt (17.6 KB)
  • 5. Poisson Distribution.mp4 (16.0 MB)
  • 5. Poisson Distribution.vtt (15.5 KB)
  • 6. Normal Distribution.mp4 (8.3 MB)
  • 6. Normal Distribution.vtt (8.7 KB)
  • 7. Sampling Techniques.mp4 (8.1 MB)
  • 7. Sampling Techniques.vtt (7.1 KB)
  • 8. T-Distribution.mp4 (6.7 MB)
  • 8. T-Distribution.vtt (7.1 KB)
  • 9. Hypothesis Testing and Confidence Intervals.mp4 (30.7 MB)
  • 9. Hypothesis Testing and Confidence Intervals.vtt (25.2 KB)
12. Appendix SQL and Python
  • 1. Introduction to SQL with Python.mp4 (16.4 MB)
  • 1. Introduction to SQL with Python.vtt (14.9 KB)
  • 2. SQL - SELECT,DISTINCT,WHERE,AND & OR.mp4 (13.5 MB)
  • 2. SQL - SELECT,DISTINCT,WHERE,AND & OR.vtt (13.8 KB)
  • 3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.mp4 (11.7 MB)
  • 3. SQL WILDCARDS, ORDER BY, GROUP BY and Aggregate Functions.vtt (11.8 KB)
13. Appendix Web Scraping with Python
  • 1. Web Scraping Part 1.mp4 (14.5 MB)
  • 1. Web Scraping Part 1.vtt (16.3 KB)
  • 2. Web Scraping Part 2.mp4 (17.4 MB)
  • 2. Web Scraping Part 2.vtt (14.6 KB)
14. Appendix Python Special Offers
  • 1. Python Overview Part 1.mp4 (17.4 MB)
  • 1. Python Overview Part 1.vtt (20.8 KB)
  • 2. Python Overview Part 2.mp4 (11.1 MB)
  • 2. Python Overview Part 2.vtt (14.7 KB)
  • 3. Python Overview Part 3.mp4 (9.8 MB)
  • 3. Python Overview Part 3.vtt (12.9 KB)
15. BONUS SPECIAL DISCOUNT COUPONS
  • 1. Bonus Lecture Coupons.html (6.0 KB)
2. Setup
  • 1. Installation Setup and Overview.mp4 (24.4 MB)
  • 1. Installation Setup and Overview.vtt (8.9 KB)
  • 1.1 Link for FAQ.html (0.1 KB)
  • 1.2 Link to Code Notebooks for Course!.html (0.1 KB)
  • 2. IDEs and Course Resources.mp4 (30.3 MB)
  • 2. IDEs and Course Resources.vtt (13.8 KB)
  • 2.1 Link to Code Notebooks for Course!.html (0.1 KB)
  • 3. iPythonJupyter Notebook Overview.mp4 (39.4 MB)
  • 3. iPythonJupyter Notebook Overview.vtt (19.4 KB)
  • 3.1 Lecture 4 Info.txt (0.2 KB)
  • 3.2 Link to Code Notebooks for Course!.html (0.1 KB)
3. Learning Numpy
  • 1. Intro to numpy.html (0.9 KB)
  • 2. Creating arrays.mp4 (6.7 MB)
  • 2. Creating arrays.vtt (8.8 KB)
  • 3. Using arrays and scalars.mp4 (4.1 MB)
  • 3. Using arrays and scalars.vtt (5.9 KB)
  • 4. Indexing Arrays.mp4 (13.3 MB)
  • 4. Indexing Arrays.vtt (17.0 KB)
  • 5. Array Transposition.mp4 (3.7 MB)
  • 5. Array Transposition.vtt (4.5 KB)
  • 6. Universal Array Function.mp4 (6.4 MB)
  • 6. Universal Array Function.vtt (7.0 KB)
  • 7. Array Processing.mp4 (20.5 MB)
  • 7. Array Processing.vtt (21.9 KB)
  • 8. Array Input and Output.mp4 (7.1 MB)
  • 8. Array Input and Output.vtt (8.7 KB)
4. Intro to Pandas
  • 1. Series.mp4 (12.6 MB)
  • 1. Series.vtt (15.0 KB)
  • 10. Missing Data.mp4 (9.9 MB)
  • 10. Missing Data.vtt (13.0 KB)
  • 11. Index Hierarchy.mp4 (12.2 MB)
  • 11. Index Hierarchy.vtt (15.9 KB)
  • 2. DataFrames.mp4 (21.8 MB)
  • 2. DataFrames.vtt (18.9 KB)
  • 3. Index objects.mp4 (4.6 MB)
  • 3. Index objects.vtt (5.3 KB)
  • 4. Reindex.mp4 (15.8 MB)
  • 4. Reindex.vtt (15.8 MB)
  • 5. Drop Entry.mp4 (5.0 MB)
  • 5. Drop Entry.vtt (6.2 KB)
  • 6. Selecting Entries.mp4 (9.6 MB)
  • 6. Selecting Entries.vtt (10.6 KB)
  • 7. Data Alignment.mp4 (9.5 MB)
  • 7. Data Alignment.vtt (11.0 KB)
  • 8. Rank and Sort.mp4 (4.9 MB)
  • 8. Rank and Sort.vtt (6.8 KB)
  • 9. Summary Statistics.mp4 (21.9 MB)
  • 9. Summary Statistics.vtt (26.6 KB)
5. Working with Data Part 1
  • 1. Reading and Writing Text Files.mp4 (10.4 MB)
  • 1. Reading and Writing Text Files.vtt (11.9 KB)
  • 2. JSON with Python.mp4 (4.3 MB)
  • 2. JSON with Python.vtt (5.2 KB)
  • 3. HTML with Python.mp4 (5.7 MB)
  • 3. HTML with Python.vtt (5.1 KB)
  • 4. Microsoft Excel files with Python.mp4 (3.7 MB)
  • 4. Microsoft Excel files with Python.vtt (4.9 KB)
6. Working with Data Part 2
  • 1. Merge.mp4 (18.6 MB)
  • 1. Merge.vtt (20.9 KB)
  • 10. Rename Index.mp4 (5.2 MB)
  • 10. Rename Index.vtt (6.6 KB)
  • 11. Binning.mp4 (6.3 MB)
  • 11. Binning.vtt (7.2 KB)
  • 12. Outliers.mp4 (7.5 MB)
  • 12. Outliers.vtt (7.6 KB)
  • 13. Permutation.mp4 (4.6 MB)
  • 13. Permutation.vtt (5.7 KB)
  • 2. Merge on Index.mp4 (12.3 MB)
  • 2. Merge on Index.vtt (13.2 KB)
  • 3. Concatenate.mp4 (9.8 MB)
  • 3. Concatenate.vtt (11.5 KB)
  • 4. Combining DataFrames.mp4 (9.6 MB)
  • 4. Combining DataFrames.vtt (11.5 KB)
  • 5. Reshaping.mp4 (7.1 MB)
  • 5. Reshaping.vtt (8.2 KB)
  • 6. Pivoting.mp4 (7.1 MB)
  • 6. Pivoting.vtt (7.8 KB)
  • 7. Duplicates in DataFrames.mp4 (5.5 MB)
  • 7. Duplicates in DataFrames.vtt (7.1 KB)
  • 8. Mapping.mp4 (3.9 MB)
  • 8. Mapping.vtt (4.7 KB)
  • 9. Replace.mp4 (2.7 MB)
  • 9. Replace.vtt (4.1 KB)
7. Working with Data Part 3
  • 1. GroupBy on DataFrames.mp4 (17.2 MB)
  • 1. GroupBy on DataFrames.vtt (20.0 KB)
  • 2. GroupBy on Dict and Series.mp4 (11.8 MB)
  • 2. GroupBy on Dict and Series.vtt (13.9 KB)
  • 3. Aggregation.mp4 (18.6 MB)
  • 3. Aggregation.vtt (16.5 KB)
  • 4. Splitting Applying and Combining.mp4 (10.6 MB)
  • 4. Splitting Applying and Combining.vtt (11.0 KB)
  • 5. Cross Tabulation.mp4 (4.5 MB)
  • 5. Cross Tabulation.vtt (6.2 KB)
8. Data Visualization
  • 1. Installing Seaborn.mp4 (2.4 MB)
  • 1. Installing Seaborn.vtt (2.5 KB)
  • 2. Histograms.mp4 (9.4 MB)
  • 2. Histograms.vtt (11.5 KB)
  • 3. Kernel Density Estimate Plots.mp4 (27.0 MB)
  • 3. Kernel Density Estimate Plots.vtt (30.7 KB)
  • 4. Combining Plot Styles.mp4 (5.7 MB)
  • 4. Combining Plot Styles.vtt (7.6 KB)
  • 5. Box and Violin Plots.mp4 (8.7 MB)
  • 5. Box and Violin Plots.vtt (10.1 KB)
  • 6. Regression Plots.mp4 (17.4 MB)
  • 6. Regression Plots.vtt (22.5 KB)
  • 7. Heatmaps and Clustered Matrices.mp4 (18.3 MB)
  • 7. Heatmaps and Clustered Matrices.vtt (19.9 KB)
9. Example Projects
  • 1. Data Projects Preview.mp4 (25.8 MB)
  • 1. Data Projects Preview.vtt (4.8 KB)
  • 10. Data Project - Stock Market Analysis Part 3.mp4 (16.6 MB)
  • 10. Data Project - Stock Market Analysis Part 3.vtt (13.6 KB)
  • 11. Data Project - Stock Market Analysis Part 4.mp4 (9.8 MB)
  • 11. Data Project - Stock Market Analysis Part 4.vtt (8.8 KB)
  • 12. Data Project - Stock Market Analysis Part 5.mp4 (36.8 MB)
  • 12. Data Project - Stock Market Analysis Part 5.vtt (33.2 KB)
  • 13. Data Project - Intro to Election Analysis.mp4 (14.9 MB)
  • 13. Data Project - Intro to Election Analysis.vtt (14.9 MB)
  • 14. Data Project - Election Analysis Part 1.mp4 (19.4 MB)
  • 14. Data Project - Election Analysis Part 1.vtt (22.1 KB)
  • 15. Data Project - Election Analysis Part 2.mp4 (24.9 MB)
  • 15. Data Project - Election Analysis Part 2.vtt (25.3 KB)
  • 16. Data Project - Election Analysis Part 3.mp4 (17.1 MB)
  • 16. Data Project - Election Analysis Part 3.vtt (19.4 KB)
  • 17. Data Project - Election Analysis Part 4.mp4 (82.1 MB)
  • 17. Data Project - Election Analysis Part 4.vtt (26.7 KB)
  • 2. Intro to Data Projects.mp4 (6.7 MB)
  • 2. Intro to Data Projects.vtt (6.8 KB)
  • 2.1 First Data Project.txt (0.3 KB)
  • 3. Titanic Project - Part 1.mp4 (18.8 MB)
  • 3. Titanic Project - Part 1.vtt (21.6 KB)
  • 3.1 First Data Project.txt (0.3 KB)
  • 4. Titanic Project - Part 2.mp4 (17.5 MB)
  • 4. Titanic Project - Part 2.vtt (18.6 KB)
  • 5. Titanic Project - Part 3.mp4 (16.2 MB)
  • 5. Titanic Project - Part 3.vtt (17.2 KB)
  • 6. Titanic Project - Part 4.mp4 (2.5 MB)
  • 6. Titanic Project - Part 4.vtt (3.3 KB)
  • 7. Intro to Data Project - Stock Market Analysis.mp4 (10.4 MB)
  • 7. Intro to Data Project - Stock Market Analysis.vtt (4.8 KB)
  • 8. Data Project - Stock Market Analysis Part 1.mp4 (13.6 MB)
  • 8. Data Project - Stock Market Analysis Part 1.vtt (15.6 KB)
  • 9. Data Project - Stock Market Analysis Part 2.mp4 (23.4 MB)
  • 9. Data Project - Stock Market Analysis Part 2.vtt (23.2 KB)
  • [FreeCourseLab.com].url (0.1 KB)

  • Info

    Learn python and how to use it to analyze,visualize and present data. Create data visualizations using matplotlib and the seaborn modules with python. Have a portfolio of various data analysis projects.

    Learn python and how to use it to analyze,visualize and present data. Expand all110 lectures 21:05:06. Includes tons of sample code and hours of video! What you’ll learn.

    Want to be notified of new releases in -Visualisation?

    In this tutorial, we are going to learn about data analysis and visualization using modules like pandas and matplotlib in. .We are going to see some useful methods from the pandas for data analysis. We need multiple rows to create a DataFrame.

    In this tutorial, we are going to learn about data analysis and visualization using modules like pandas and matplotlib in Python. Python is an excellent fit for.

    Learn python and how to use it to analyze, visualize and present data Have a portfolio of various data analysis projects. Curriculum For This Course Expand All Collapse All 110 Lectures 21:05:16 + – Intro to Course and Python 2 Lectures 07:18.

    Learn python and how to use it to analyze, visualize and present data. Get a basic overview of what you will learn in this course. IDEs and Course Resources 10:56 iPython/Jupyter Notebook Overview 14:57 + – Learning Numpy 8 Lectures 01:06:52.

    Master Python to Analyze and Visualize Data. If you're already familiar with Python, this course is right for you. It will take your skills to the next level by showing you how to analyze and visualize data with greater ease and efficiency. Whether you're already working in the field of data science or you want to dive in, this course will provide you with a complete understanding of how to program with Python.

    Learning Path: Python: Effective Data Analysis Using Python. Use Pythons tools & libraries effectively for extracting data from web & creating attractive & informative visualization. Udemy is an online learning and teaching marketplace with over courses and 24 million students. Learn programming, marketing, data science and more.

    Pandas is one of those packages, and makes importing and analyzing data much easier. In this article, I have used Pandas to analyze data on Country Data. csv file from UN public Data Sets of a popular ‘statweb. As I have analyzed the Indian Country Data, I have introduced Pandas key concepts as below.

    I want to learn Python for data analysis and machine learning. Matlplotlib is a Python module for visualization. Matplotlib allows you to easily make line graphs, pie chart, histogram and other professional grade figures. Using Matplotlib you can customize every aspect of a figure.

    Udemy - Learning Python for Data Analysis and Visualization
    Learn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video!
    For more Udemy Courses: https://freecourselab.com

Udemy - Learning Python for Data Analysis and Visualization