Data Analysis with Python: NumPy & Pandas Masterclass

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Maven Analytics,Chris Bruehl

13:17:03

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1. Getting Started

1. Course Structure & Outline.mp4

01:49

2. READ ME Important Notes for New Students.html

3.1 Data Analysis With Python & Pandas.pdf

3.2 Pandas Course Resources.zip

3. DOWNLOAD Course Resources.html

4. Introducing the Course Project.mp4

00:52

5. Setting Expectations.mp4

01:18

6. Jupyter Installation & Launch.mp4

02:55

2. NumPy Primer

1. Pandas & NumPy Intro.mp4

02:53

2. Numpy Arrays & Array Properties.mp4

07:40

3. ASSIGNMENT Array Basics.mp4

01:49

4. SOLUTION Array Basics.mp4

02:07

5. Array Creation.mp4

08:18

6. Random Number Generation.mp4

06:02

7. ASSIGNMENT Array Creation.mp4

01:31

8. SOLUTION Array Creation.mp4

04:32

9. Indexing & Slicing Arrays.mp4

09:13

10. ASSIGNMENT Indexing & Slicing Arrays.mp4

01:11

11. SOLUTION Indexing & Slicing Arrays.mp4

02:23

12. Array Operations.mp4

07:49

13. ASSIGNMENT Array Operations.mp4

02:09

14. SOLUTION Array Operations.mp4

04:21

15. Filtering Arrays & Modifying Array Values.mp4

10:56

16. The Where Function.mp4

04:00

17. ASSIGNMENT Filtering & Modifying Arrays.mp4

02:04

18. SOLUTION Filtering & Modifying Arrays.mp4

03:11

19. Array Aggregation.mp4

06:57

20. Array Functions.mp4

07:41

21. Sorting Arrays.mp4

03:52

22. ASSIGNMENT Aggregation & Sorting.mp4

01:11

23. SOLUTION Aggregation & Sorting.mp4

01:35

24. Vectorization.mp4

04:23

25. Broadcasting.mp4

07:10

26. ASSIGNMENT Bringing it all together.mp4

02:45

27. SOLUTION Bringing it all together.mp4

06:18

28. Key Takeaways.mp4

01:56

29. QUIZ NumPy Primer.html

3. Pandas Series

1. Series Basics.mp4

08:06

2. Pandas Data Types & Type Conversion.mp4

06:55

3. ASSIGNMENT Data Types & Type Conversion.mp4

01:49

4. SOLUTION Data Types & Type Conversion.mp4

02:28

5. The Series Index & Custom Indices.mp4

07:06

6. The .iloc Accessor.mp4

04:33

7. The .loc Accessor.mp4

07:07

8. Duplicate Index Values & Resetting The Index.mp4

06:35

9. ASSIGNMENT Accessing Data & Resetting The Index.mp4

02:05

10. SOLUTION Accessing Data & Resetting The Index.mp4

02:39

11. Filtering Series & Logical Tests.mp4

08:22

12. Sorting Series.mp4

03:45

13. ASSIGNMENT Sorting & Filtering Series.mp4

00:57

14. SOLUTION Sorting & Filtering Series.mp4

03:24

15. Numeric Series Operations.mp4

06:31

16. Text Series Operations.mp4

07:04

17. ASSIGNMENT Series Operations.mp4

01:36

18. SOLUTION Series Operations.mp4

03:55

19. Numerical Series Aggregation.mp4

05:43

20. Categorical Series Aggregation.mp4

03:32

21. ASSIGNMENT Series Aggregation.mp4

00:50

22. SOLUTION Series Aggregation.mp4

04:20

23. Missing Data Representation in Pandas.mp4

04:30

24. Identifying Missing Data.mp4

02:15

25. Fixing Missing Data.mp4

09:25

26. ASSIGNMENT Missing Data.mp4

00:45

27. SOLUTION Missing Data.mp4

01:35

28. Applying Custom Functions to Series.mp4

04:08

29. Pandas Where (vs. NumPy Where).mp4

06:03

30. ASSIGNMENT Apply & Where.mp4

01:09

31. SOLUTION Apply & Where.mp4

04:37

32. Key Takeaways.mp4

01:24

33. QUIZ Pandas Series.html

4. Intro to DataFrames

1. DataFrame Basics.mp4

04:20

2. Creating a DataFrame.mp4

04:59

3. ASSIGNMENT DataFrame Basics.mp4

00:53

4. SOLUTION DataFrame Basics.mp4

02:02

5. Exploring DataFrames Heads, Tails & Sample.mp4

03:35

6. Exploring DataFrames Info & Describe.mp4

08:29

7. ASSIGNMENT Exploring a DataFrame.mp4

00:59

8. SOLUTION Exploring a DataFrame.mp4

04:03

9. Accessing DataFrame Columns.mp4

04:53

10. Accessing DataFrame Data with .iloc & .loc.mp4

06:09

11. ASSIGNMENT Accessing DataFrame Data.mp4

01:18

12. SOLUTION Accessing DataFrame Data.mp4

03:23

13. Dropping Columns & Rows.mp4

05:58

14. Identifying & Dropping Duplicates.mp4

07:01

15. ASSIGNMENT Dropping Data.mp4

01:01

16. SOLUTION Dropping Data.mp4

02:40

17. Missing Data.mp4

03:17

18. ASSIGNMENT Missing Data.mp4

00:51

19. SOLUTION Missing Data.mp4

02:14

20. Filtering DataFrames.mp4

04:31

21. PRO TIP The Query Method.mp4

04:17

22. ASSIGNMENT Filtering DataFrames.mp4

01:51

23. SOLUTION Filtering DataFrames.mp4

06:20

24. Sorting DataFrames.mp4

06:56

25. ASSIGNMENT Sorting DataFrames.mp4

00:45

26. SOLUTION Sorting DataFrames.mp4

02:50

27. Renaming & Reordering Columns.mp4

03:10

28. ASSIGNMENT Renaming & Reordering Columns.mp4

00:55

29. SOLUTION Renaming & Reordering Columns.mp4

03:18

30. Arithmetic & Boolean Column Creation.mp4

06:25

31. ASSIGNMENT Arithmetic & Boolean Columns.mp4

01:40

32. SOLUTION Arithmetic & Boolean Columns.mp4

04:02

33. PRO TIP Advanced Conditional Columns with Select.mp4

06:01

34. ASSIGNMENT The Select Function.mp4

01:47

35. SOLUTION The Select Function.mp4

03:34

36. The Map Method.mp4

04:24

37. PRO TIP Multiple Column Creation with Assign.mp4

08:20

38. ASSIGNMENT Map & Assign.mp4

01:24

39. SOLUTION Map & Assign.mp4

02:40

40. The Categorical Data Type.mp4

05:33

41. Type Conversion.mp4

01:37

42. PRO TIP Memory Usage & DataTypes.mp4

06:02

43. PRO TIP Downcasting Numeric Data Types.mp4

04:58

44. ASSIGNMENT DataFrame DataTypes.mp4

01:24

45. SOLUTION DataFrame DataTypes.mp4

03:19

46. Key Takeways.mp4

01:33

47. QUIZ Intro to DataFrames.html

5. Aggregating & Reshaping DataFrames

1. Basic Aggregations.mp4

04:16

2. The Groupby Method.mp4

04:32

3. ASSIGNMENT Groupby.mp4

01:18

4. SOLUTION Groupby.mp4

02:11

5. Grouping By Multiple Columns.mp4

04:43

6. ASSIGNMENT Grouping By Multiple Columns.mp4

01:09

7. SOLUTION Grouping By Multiple Columns.mp4

03:00

8. Multi-Index DataFrames.mp4

07:41

9. Modifying Multi-Indices.mp4

04:27

10. ASSIGNMENT Multi-Index DataFrames.mp4

01:18

11. SOLUTION Multi-Index DataFrames.mp4

04:02

12. The Agg Method & Named Aggregations.mp4

07:22

13. ASSIGNMENT The Agg Method.mp4

01:22

14. SOLUTION The Agg Method.mp4

03:01

15. PRO TIP Transforming DataFrames.mp4

06:53

16. ASSIGNMENT Transforming a DataFrame.mp4

01:18

17. SOLUTION Transforming a DataFrame.mp4

04:29

18. Pivot Tables in Pandas.mp4

06:40

19. Multiple Aggregation Pivot Tables.mp4

02:59

20. PRO TIP Pivot Table Heatmaps.mp4

04:34

21. Melting DataFrames.mp4

06:28

22. ASSIGNMENT Pivot & Melt.mp4

01:04

23. SOLUTION Pivot & Melt.mp4

05:41

24. Key Takeaways.mp4

01:53

25. QUIZ Aggregating & Reshaping DataFrames.html

6. Basic Data Visualization in Python

1. The matplotlib API & The .plot() Method.mp4

09:34

2. ASSIGNMENT Basic Line Chart.mp4

00:50

3. SOLUTION Basic Line Chart.mp4

03:09

4. Chart Titles.mp4

03:31

5. Chart Colors.mp4

05:13

6. Line Styles.mp4

02:01

7. Chart Legends & Gridlines.mp4

03:53

8. Chart Styles.mp4

04:08

9. ASSIGNMENT Stylized Line Chart.mp4

01:11

10. SOLUTION Stylized Line Chart.mp4

01:21

11. Subplots & Figure Size.mp4

05:29

12. ASSIGNMENT Subplots.mp4

01:33

13. SOLUTION Subplots.mp4

02:59

14. Bar Charts.mp4

06:17

15. Grouped & Stacked Bar Charts.mp4

05:12

16. ASSIGNMENT Bar Charts.mp4

01:11

17. SOLUTION Bar Charts.mp4

02:19

18. Pie Charts & Scatterplots.mp4

06:54

19. ASSIGNMENT Scatterplots.mp4

01:00

20. SOLUTION Scatterplots.mp4

02:09

21. Histograms.mp4

03:47

22. ASSIGNMENT Histograms.mp4

00:33

23. SOLUTION Histograms.mp4

01:18

24. Saving Plots & Further Exploration.mp4

03:43

25. Key Takeaways.mp4

02:12

26. QUIZ Basic Data Visualization in Python.html

7. MID-COURSE PROJECT

1. Mid-Course Project Intro.mp4

04:45

2. SOLUTION Mid-Course Project.mp4

15:07

8. Analyzing Dates & Times

1. Times in Python and Pandas.mp4

03:17

2. Converting To Datetimes.mp4

06:16

3. Formatting Dates.mp4

05:19

4. Date & Time Parts.mp4

03:04

5. ASSIGNMENT Pandas Datetime Basics.mp4

01:23

6. SOLUTION Pandas Datetime Basics.mp4

02:10

7. Time Deltas & Arithmetic.mp4

06:40

8. ASSIGNMENT Time Deltas.mp4

01:10

9. SOLUTION Time Deltas.mp4

01:35

10. Time Series Indices.mp4

04:01

11. Missing Time Series Data.mp4

04:50

12. ASSIGNMENT Missing Time Series Data.mp4

01:44

13. SOLUTION Missing Time Series Data.mp4

02:13

14. Shifting Time Series.mp4

03:16

15. PRO TIP DIFF().mp4

02:55

16. ASSIGNMENT Shift & Diff.mp4

01:39

17. SOLUTION Shift & Diff.mp4

02:47

18. Aggregation & Resampling.mp4

04:07

19. ASSIGNMENT Resampling.mp4

00:41

20. SOLUTION Resampling.mp4

01:53

21. Rolling Aggregations.mp4

04:35

22. ASSIGNMENT Rolling Aggregations.mp4

00:45

23. SOLUTION Rolling Aggregations.mp4

00:55

24. Key Takeaways.mp4

01:37

25. QUIZ Analyzing Dates & Times.html

9. Importing & Exporting Data

1. Preprocessing with read csv.mp4

05:31

2. Column Selection.mp4

03:49

3. Row Selection & Missing Values.mp4

04:29

4. Parsing Dates & Data Types.mp4

03:35

5. PRO TIP Converters.mp4

02:48

6. ASSIGNMENT Importing Data.mp4

01:44

7. SOLUTION Importing Data.mp4

04:19

8. Importing from Text & Excel Files.mp4

05:21

9. Exporting to Flat Files.mp4

02:09

10. ASSIGNMENT Importing & Exporting Excel Data.mp4

01:19

11. SOLUTION Importing & Exporting Excel Data.mp4

01:54

12. Working With SQL Databases.mp4

06:22

13. Other Supported File Formats.mp4

02:34

14. Key Takeaways.mp4

01:11

15. QUIZ Importing & Exporting Data.html

10. Joining DataFrames

1. Why Multiple Tables.mp4

01:58

2. Appending DataFrames.mp4

04:41

3. ASSIGNMENT Appending DataFrames.mp4

01:25

4. SOLUTION Appending DataFrames.mp4

01:38

5. Joining DataFrames.mp4

02:23

6. Join Types.mp4

03:45

7. Inner Joins.mp4

03:22

8. Left Joins.mp4

04:22

9. ASSIGNMENT Joining DataFrames.mp4

02:00

10. SOLUTION Joining DataFrames.mp4

05:41

11. The Join Method.mp4

01:56

12. Key Takeaways.mp4

01:17

13. QUIZ Joining DataFrames.html

11. FINAL COURSE PROJECT

1. Final Project Intro.mp4

04:09

2. SOLUTION Final Project.mp4

13:04

12. BONUS LESSON

1. BONUS LESSON.html

Description

Learn NumPy & Pandas for data science, data analysis & business intelligence, with practical, hands-on Python projects!

What You'll Learn?

Master the essentials of NumPy and Pandas, two of Python's most powerful data analysis packages
Learn how to explore, transform, aggregate and join NumPy arrays and Pandas DataFrames
Analyze and manipulate dates and times for time intelligence and time-series analysis
Visualize raw data using plot methods and common chart options like line charts, bar charts, scatter plots and histograms
Import and export flat files, Excel workbooks and SQL database tables using Pandas
Build powerful, practical skills for modern analytics and business intelligence

Who is this for?

Analysts or BI professionals looking to learn data analysis with NumPy and Pandas

Aspiring data scientists who want to build or strengthen their Python skills

Anyone interested in learning one of the most popular open source programming languages in the world

Students looking to learn powerful, practical skills with unique, hands-on projects and course demos

What You Need to Know?

We'll use Anaconda & Jupyter Notebooks (a free, user-friendly coding environment)

Familiarity with base Python is strongly recommended, but not a strict prerequisite

More details

Description
This is a hands-on, project-based course designed to help you master two of the most popular Python packages for data analysis: NumPy and Pandas.

We'll start with a NumPy primer to introduce arrays and array properties, practice common operations like indexing, slicing, filtering and sorting, and explore important concepts like vectorization and broadcasting.

From there we'll dive into Pandas, and focus on the essential tools and methods to explore, analyze, aggregate and transform series and dataframes. You'll practice plotting dataframes with charts and graphs, manipulating time-series data, importing and exporting various file types, and combining dataframes using common join methods.

Throughout the course you'll play the role of Data Analyst for Maven Mega Mart, a large, multinational corporation that operates a chain of retail and grocery stores. Using the Python skills you learn throughout the course, you'll work with members of the Maven Mega Mart team to analyze products, pricing, transactions, and more.

COURSEÂ OUTLINE:

Intro to NumPy &Â Pandas
Introduce NumPy and Pandas, two critical Python libraries that help structure data in arrays & DataFrames and contain built-in functions for data analysis

Pandas Series
Introduce Pandas Series, the Python equivalent of a column of data, and cover their basic properties, creation, manipulation, and useful functions for analysis

Intro to DataFrames
Work with Pandas DataFrames, the Python equivalent of an Excel or SQL table, and use them to store, manipulate, and analyze data efficiently

Manipulating DataFrames
Aggregate & reshape data in DataFrames by grouping columns, performing aggregation calculations, and pivoting & unpivoting data

Basic Data Visualization
Learn the basics of data visualization in Pandas, and use the plot method to create & customize line charts, bar charts, scatterplots, and histograms

MID-COURSEÂ PROJECT
Put your skills to the test with a brand new dataset, and use your Python skills to analyze and evaluate a new retailer as a potential acquisition target for Maven MegaMart

Analyzing Dates &Â Times
Learn how to work with the datetime data type in Pandas to extract date components, group by dates, and perform time intelligence calculations like moving averages

Importing & Exporting Data
Read in data from flat files and apply processing steps during import, create DataFrames by querying SQL tables, and write data back out to its source

Joining DataFrames
Combine multiple DataFrames by joining data from related fields to add new columns, and appending data with the same fields to add new rows

FINALÂ COURSEÂ PROJECT
Put the finishing touches on your project by joining a new table, performing time series analysis, optimizing your workflow, and writing out your results

Join todayÂ and get immediate, lifetime accessÂ to the following:

13+ hours of high-quality video
Python &Â Pandas PDF ebook (350+Â pages)
Downloadable project files &Â solutions
Expert support and Q&AÂ forum
30-day Udemy satisfaction guarantee

If you're a data scientist, BI analyst or data engineer looking to add Pandas to your Python skill set, this course is for you.

Happy learning!
-Chris Bruehl (Python Expert &Â Lead Python Instructor, Maven Analytics)
__________
Looking for our full business intelligence stack? Search for "Maven Analytics"Â to browse our full course library, including Excel, Power BI, MySQL,Â TableauÂ and Machine Learning courses!

See why our courses are among the TOP-RATEDÂ on Udemy:

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Who this course is for:
Analysts or BI professionals looking to learn data analysis with NumPy and Pandas
Aspiring data scientists who want to build or strengthen their Python skills
Anyone interested in learning one of the most popular open source programming languages in the world
Students looking to learn powerful, practical skills with unique, hands-on projects and course demos

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Maven Analytics helps individuals and teams build expert-level analytics & business intelligence skills. We've helped more than 1,000,000 students around the world build job-ready skills, master sought-after tools like Excel, SQL, Power BI, Tableau & Python, and build the foundation for a successful career in data. At Maven Analytics, we empower everyday people to change the world with data.

Chris Bruehl

Instructor's Courses

Chris is a seasoned data scientist, having held Data Science roles in the financial services industry. He was first trained on SAS before falling in love with Python and making it his tool of choice. Chris transitioned from applying data science in the field, to teaching at a top tier data science bootcamp. He is passionate about teaching and is able to break down complex concepts into bite size lessons. He holds a Masters Degree in Analytics from NCSU.

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