[Udemy] The Ultimate Pandas Bootcamp Advanced Python Data Analysis (2021)

Creation Time	Aug. 1, 2024, 1:48 p.m.
Last Access Time	Nov. 6, 2024, 12:39 p.m.
File Size	9.6 GB
Keywords	Python Analysis Bootcamp Ultimate The Udemy Data Pandas Advanced 2021
Total Requests	26
Total Files	721
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

13. Data Formats And IO/3. Reading HTML.mp4 103.7 MB
11. Regex And Text Manipulation/19. Is This A Valid Email.mp4 80.1 MB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.mp4 76.3 MB
11. Regex And Text Manipulation/16. Introduction To Regular Expressions.mp4 75.0 MB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.mp4 74.0 MB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.mp4 73.2 MB
11. Regex And Text Manipulation/23. Solution.mp4 72.4 MB
15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.mp4 71.3 MB
3. Series Methods And Handling/28. Transforming With update(), apply() And map().mp4 69.9 MB
5. DataFrames In Depth/33. Element-wise Operations With applymap().mp4 68.5 MB
5. DataFrames In Depth/4. More Approaches To Boolean Masking.mp4 68.4 MB
5. DataFrames In Depth/31. Same-shape Transforms.mp4 67.0 MB
4. Working With DataFrames/22. Part I Collecting The Units.mp4 66.8 MB
11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().mp4 66.3 MB
5. DataFrames In Depth/14. Sorting vs. Reordering.mp4 65.2 MB
11. Regex And Text Manipulation/17. More Regex Concepts.mp4 65.2 MB
12. Visualizing Data/9. Other Visualization Options.mp4 63.6 MB
11. Regex And Text Manipulation/18. How To Approach Regex.mp4 63.5 MB
12. Visualizing Data/8. Scatter Plots.mp4 63.4 MB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4 63.0 MB
12. Visualizing Data/3. The Preliminaries Of matplotlib.mp4 62.9 MB
1. Introduction/7. NumPy.mp4 62.2 MB
5. DataFrames In Depth/19. Identifying Dupes.mp4 60.9 MB
6. Working With Multiple DataFrames/11. Solution.mp4 59.5 MB
5. DataFrames In Depth/32. More Flexibility With apply().mp4 59.4 MB
7. Going MultiDimensional/7. Indexing Ranges And Slices.mp4 59.1 MB
7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.mp4 58.7 MB
6. Working With Multiple DataFrames/5. Enforcing Unique Indices.mp4 58.4 MB
14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.mp4 57.8 MB
5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().mp4 57.4 MB
4. Working With DataFrames/26. Part II Merging Units With Column Names.mp4 57.3 MB
6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.mp4 57.0 MB
13. Data Formats And IO/4. Reading Excel.mp4 55.7 MB
6. Working With Multiple DataFrames/17. Many-to-Many Joins.mp4 55.6 MB
3. Series Methods And Handling/27. Filtering filter(), where(), And mask().mp4 55.1 MB
12. Visualizing Data/6. Pie Plots.mp4 54.9 MB
12. Visualizing Data/12. Solution.mp4 54.2 MB
12. Visualizing Data/4. Line Graphs.mp4 54.2 MB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.mp4 53.0 MB
10. Handling Date And Time/3. Parsing Dates From Text.mp4 52.8 MB
3. Series Methods And Handling/2. Reading In Data With read_csv().mp4 52.8 MB
6. Working With Multiple DataFrames/4. The Duplicated Index Issue.mp4 51.3 MB
5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.mp4 50.5 MB
4. Working With DataFrames/12. Changing The Index.mp4 50.4 MB
12. Visualizing Data/5. Bar Charts.mp4 50.1 MB
5. DataFrames In Depth/40. Adding Rows To DataFrames.mp4 49.9 MB
4. Working With DataFrames/29. DataFrame Sorting.mp4 49.4 MB
10. Handling Date And Time/19. Upsampling And Interpolation.mp4 49.4 MB
5. DataFrames In Depth/38. View vs Copy.mp4 49.3 MB
7. Going MultiDimensional/24. Solution.mp4 49.2 MB
5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.mp4 49.0 MB
3. Series Methods And Handling/32. Solution III - Z-scores.mp4 48.2 MB
1. Introduction/4. Jupyter Notebooks.mp4 48.0 MB
4. Working With DataFrames/14. DataFrame Extraction by Position.mp4 46.7 MB
11. Regex And Text Manipulation/8. String Splitting And Concatenation.mp4 46.3 MB
5. DataFrames In Depth/12. Fancy Indexing With lookup().mp4 46.2 MB
6. Working With Multiple DataFrames/21. Solution.mp4 46.1 MB
7. Going MultiDimensional/19. The Flipside unstack().mp4 45.9 MB
4. Working With DataFrames/2. What Is A DataFrame.mp4 45.9 MB
13. Data Formats And IO/10. Solution.mp4 45.8 MB
12. Visualizing Data/7. Histograms.mp4 45.8 MB
5. DataFrames In Depth/7. Combining Conditions.mp4 45.6 MB
4. Working With DataFrames/18. Solution.mp4 45.2 MB
5. DataFrames In Depth/13. Sorting By Index Or Column.mp4 45.0 MB
7. Going MultiDimensional/11. Solution.mp4 44.8 MB
4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.mp4 44.3 MB
8. GroupBy And Aggregates/15. Fine-tuned Aggregates.mp4 44.1 MB
5. DataFrames In Depth/36. Setting DataFrame Values.mp4 43.6 MB
10. Handling Date And Time/21. BONUS Rolling Windows.mp4 43.5 MB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.mp4 42.9 MB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.mp4 42.8 MB
5. DataFrames In Depth/29. Solution.mp4 42.5 MB
4. Working With DataFrames/28. Filtering in 2D.mp4 42.3 MB
4. Working With DataFrames/34. Solution.mp4 42.3 MB
5. DataFrames In Depth/25. Null Values In DataFrames.mp4 42.2 MB
6. Working With Multiple DataFrames/3. Concatenating DataFrames.mp4 42.1 MB
9. Reshaping With Pivots/3. Pivoting Data.mp4 41.9 MB
11. Regex And Text Manipulation/15. Text Replacement.mp4 41.8 MB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.mp4 41.7 MB
8. GroupBy And Aggregates/19. BONUS - There's Also apply().mp4 41.2 MB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.mp4 40.6 MB
4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.mp4 40.5 MB
10. Handling Date And Time/2. The Python datetime Module.mp4 40.3 MB
3. Series Methods And Handling/22. Series Arithmetics And fill_value().mp4 40.2 MB
11. Regex And Text Manipulation/9. More Split Parameters.mp4 40.1 MB
4. Working With DataFrames/24. DataFrame dropna().mp4 40.1 MB
5. DataFrames In Depth/10. Solution.mp4 40.0 MB
5. DataFrames In Depth/11. 2d Indexing.mp4 40.0 MB
5. DataFrames In Depth/37. The SettingWithCopy Warning.mp4 39.8 MB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.mp4 39.4 MB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.mp4 39.1 MB
8. GroupBy And Aggregates/18. GroupBy Transformations.mp4 38.8 MB
10. Handling Date And Time/18. Resampling Timeseries.mp4 38.5 MB
6. Working With Multiple DataFrames/9. Concat On Different Columns.mp4 38.2 MB
10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.mp4 38.1 MB
6. Working With Multiple DataFrames/18. Merging By Index.mp4 38.1 MB
5. DataFrames In Depth/5. Binary Operators With Booleans.mp4 37.9 MB
7. Going MultiDimensional/17. More MultiIndex Methods.mp4 37.9 MB
7. Going MultiDimensional/15. Removing MultiIndex Levels.mp4 37.7 MB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.mp4 37.1 MB
5. DataFrames In Depth/30. Calculating Aggregates With agg().mp4 37.1 MB
11. Regex And Text Manipulation/13. Masking With String Methods.mp4 36.9 MB
4. Working With DataFrames/36. Solution.mp4 36.9 MB
3. Series Methods And Handling/6. Accessing And Counting NAs.mp4 36.8 MB
9. Reshaping With Pivots/13. Solution.mp4 36.6 MB
10. Handling Date And Time/20. What About asfreq().mp4 36.6 MB
10. Handling Date And Time/15. Creating Date Ranges.mp4 36.5 MB
8. GroupBy And Aggregates/16. Named Aggregations.mp4 36.5 MB
5. DataFrames In Depth/39. Adding DataFrame Columns.mp4 36.5 MB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.mp4 36.3 MB
10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.mp4 36.2 MB
9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.mp4 36.2 MB
4. Working With DataFrames/13. Extracting From DataFrames By Label.mp4 36.0 MB
4. Working With DataFrames/27. Part III Removing Units From Values.mp4 35.6 MB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.mp4 35.6 MB
7. Going MultiDimensional/16. MultiIndex sort_index().mp4 35.6 MB
6. Working With Multiple DataFrames/12. The merge() Method.mp4 35.4 MB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().mp4 35.4 MB
10. Handling Date And Time/6. Performant Datetimes With Numpy.mp4 35.3 MB
4. Working With DataFrames/30. Using Series between() With DataFrames.mp4 35.0 MB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.mp4 34.8 MB
9. Reshaping With Pivots/5. What About Aggregates.mp4 34.3 MB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.mp4 34.2 MB
3. Series Methods And Handling/13. Descriptive Statistics.mp4 33.7 MB
9. Reshaping With Pivots/6. The pivot_table().mp4 33.7 MB
7. Going MultiDimensional/13. Adding Another Level.mp4 33.6 MB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.mp4 33.2 MB
2. Series At A Glance/7. Index And RangeIndex.mp4 33.2 MB
7. Going MultiDimensional/9. Cross Sections With xs().mp4 33.2 MB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.mp4 33.0 MB
1. Introduction/6. Hello, Python.mp4 32.8 MB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.mp4 32.3 MB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.mp4 32.2 MB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.mp4 32.1 MB
5. DataFrames In Depth/43. Solution.mp4 31.9 MB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.mp4 31.8 MB
3. Series Methods And Handling/15. mode() And value_counts().mp4 31.7 MB
11. Regex And Text Manipulation/7. Strips And Whitespace.mp4 31.7 MB
13. Data Formats And IO/6. BONUS Introduction To Pickling.mp4 31.7 MB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.mp4 31.0 MB
7. Going MultiDimensional/18. Reshaping With stack().mp4 30.6 MB
2. Series At A Glance/20. Selecting With .get().mp4 30.5 MB
14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.mp4 30.4 MB
5. DataFrames In Depth/20. Removing Duplicates.mp4 29.8 MB
14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.mp4 29.5 MB
2. Series At A Glance/17. Boolean Masks And The .loc Indexer.mp4 29.5 MB
10. Handling Date And Time/8. Our Dataset Brent Prices.mp4 29.4 MB
4. Working With DataFrames/25. BONUS - dropna() With Subset.mp4 29.3 MB
14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.mp4 29.2 MB
2. Series At A Glance/13. Extracting By Index Position.mp4 29.1 MB
8. GroupBy And Aggregates/3. Simple Aggregations Review.mp4 29.0 MB
11. Regex And Text Manipulation/3. String Methods In Python.mp4 28.8 MB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().mp4 28.5 MB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.mp4 28.4 MB
2. Series At A Glance/21. Selection Recap.mp4 28.2 MB
13. Data Formats And IO/8. The Many Other Formats.mp4 27.9 MB
9. Reshaping With Pivots/4. Undoing Pivots.mp4 27.9 MB
7. Going MultiDimensional/22. BONUS - What About Panels.mp4 27.9 MB
7. Going MultiDimensional/5. MultiIndex From read_csv().mp4 27.7 MB
8. GroupBy And Aggregates/11. Solution.mp4 27.6 MB
4. Working With DataFrames/23. The rename() Method.mp4 27.6 MB
14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.mp4 27.6 MB
14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.mp4 27.5 MB
4. Working With DataFrames/6. Reading In Nutrition Data.mp4 27.3 MB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.mp4 27.1 MB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.mp4 27.1 MB
2. Series At A Glance/14. Accessing Elements By Label.mp4 27.1 MB
7. Going MultiDimensional/3. Index And RangeIndex.mp4 26.9 MB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.mp4 26.8 MB
10. Handling Date And Time/11. Indexing Dates.mp4 26.6 MB
8. GroupBy And Aggregates/14. MultiIndex Grouping.mp4 26.5 MB
1. Introduction/5. Cloud vs Local.mp4 26.5 MB
5. DataFrames In Depth/35. Solution.mp4 26.5 MB
7. Going MultiDimensional/1. Section Intro.mp4 26.4 MB
4. Working With DataFrames/15. Single Value Access With .at And .iat.mp4 26.3 MB
8. GroupBy And Aggregates/17. The filter() Method.mp4 26.1 MB
5. DataFrames In Depth/18. Solution.mp4 25.8 MB
11. Regex And Text Manipulation/6. Finding Characters And Words.mp4 25.7 MB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.mp4 25.3 MB
4. Working With DataFrames/20. The astype() Method.mp4 25.2 MB
4. Working With DataFrames/16. BONUS - The get_loc() Method.mp4 25.1 MB
9. Reshaping With Pivots/9. Adding Margins.mp4 24.6 MB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.mp4 24.5 MB
8. GroupBy And Aggregates/21. Solution.mp4 24.5 MB
8. GroupBy And Aggregates/4. Conditional Aggregates.mp4 24.5 MB
7. Going MultiDimensional/14. Shuffling Levels.mp4 24.3 MB
11. Regex And Text Manipulation/12. Slicing Substrings.mp4 24.2 MB
10. Handling Date And Time/7. The Pandas Timestamp.mp4 24.0 MB
10. Handling Date And Time/4. Even Better dateutil.mp4 23.9 MB
9. Reshaping With Pivots/1. Section Intro.mp4 23.8 MB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.mp4 23.7 MB
8. GroupBy And Aggregates/13. Handpicking Subgroups.mp4 23.6 MB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.mp4 23.6 MB
2. Series At A Glance/23. Solution.mp4 23.4 MB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.mp4 23.3 MB
4. Working With DataFrames/11. DataFrame Axes.mp4 23.3 MB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().mp4 23.3 MB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.mp4 23.2 MB
2. Series At A Glance/12. The head() And tail() Methods.mp4 23.0 MB
13. Data Formats And IO/7. Pickles In Pandas.mp4 22.9 MB
10. Handling Date And Time/23. Solution.mp4 22.9 MB
2. Series At A Glance/10. Solution.mp4 22.9 MB
6. Working With Multiple DataFrames/19. The join() Method.mp4 22.9 MB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.mp4 22.7 MB
4. Working With DataFrames/8. The sample() Method.mp4 22.6 MB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.mp4 22.5 MB
4. Working With DataFrames/3. Creating A DataFrame.mp4 22.4 MB
10. Handling Date And Time/5. From Datetime To String.mp4 22.4 MB
10. Handling Date And Time/1. Section Intro.mp4 22.3 MB
7. Going MultiDimensional/2. Introducing New Data.mp4 22.1 MB
3. Series Methods And Handling/16. idxmax() And idxmin().mp4 22.0 MB
11. Regex And Text Manipulation/11. Solution.mp4 22.0 MB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.mp4 21.9 MB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.mp4 21.7 MB
8. GroupBy And Aggregates/6. The groupby() Method.mp4 21.6 MB
3. Series Methods And Handling/12. Dropping And Filling NAs.mp4 21.5 MB
3. Series Methods And Handling/7. BONUS Another Approach.mp4 21.3 MB
5. DataFrames In Depth/1. Section Intro.mp4 21.1 MB
8. GroupBy And Aggregates/12. Iterating Through Groups.mp4 21.0 MB
8. GroupBy And Aggregates/9. BONUS - Series groupby().mp4 20.8 MB
1. Introduction/3. Anaconda.mp4 20.7 MB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.mp4 20.6 MB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.mp4 20.5 MB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.mp4 20.5 MB
2. Series At A Glance/4. What’s In The Data.mp4 20.4 MB
6. Working With Multiple DataFrames/15. Left vs Right Joins.mp4 20.3 MB
7. Going MultiDimensional/4. Creating A MultiIndex.mp4 20.1 MB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.mp4 20.0 MB
5. DataFrames In Depth/8. Conditions As Variables.mp4 19.9 MB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.mp4 19.8 MB
5. DataFrames In Depth/21. Removing DataFrame Rows.mp4 19.8 MB
13. Data Formats And IO/2. Reading JSON.mp4 19.7 MB
3. Series Methods And Handling/17. Sorting With sort_values().mp4 19.6 MB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.mp4 19.3 MB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.mp4 19.1 MB
2. Series At A Glance/8. Series And Index Names.mp4 19.1 MB
5. DataFrames In Depth/23. BONUS - Another Way pop().mp4 19.1 MB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.mp4 19.0 MB
4. Working With DataFrames/5. The info() Method.mp4 19.0 MB
4. Working With DataFrames/19. More Cleanup Going Numeric.mp4 18.6 MB
7. Going MultiDimensional/21. An Easier Way transpose().mp4 18.6 MB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.mp4 18.4 MB
9. Reshaping With Pivots/11. Applying Multiple Functions.mp4 18.3 MB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().mp4 18.3 MB
5. DataFrames In Depth/2. Introducing A New Dataset.mp4 18.3 MB
3. Series Methods And Handling/24. Cumulative Operations.mp4 17.9 MB
1. Introduction/2. Pandas Is Not Single.mp4 17.8 MB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.mp4 17.8 MB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.mp4 17.6 MB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.mp4 17.4 MB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.mp4 17.2 MB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.mp4 17.1 MB
10. Handling Date And Time/13. Solution.mp4 17.1 MB
8. GroupBy And Aggregates/1. Section Intro.mp4 17.1 MB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.mp4 17.1 MB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.mp4 17.0 MB
11. Regex And Text Manipulation/1. Section Intro.mp4 16.7 MB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.mp4 16.5 MB
5. DataFrames In Depth/22. BONUS - Removing Columns.mp4 16.2 MB
3. Series Methods And Handling/26. Series Iteration.mp4 16.1 MB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.mp4 15.9 MB
3. Series Methods And Handling/19. Sorting With sort_index().mp4 15.3 MB
8. GroupBy And Aggregates/2. New Data Game Sales.mp4 14.9 MB
3. Series Methods And Handling/30. Solution I - Reading Data.mp4 14.6 MB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().mp4 14.5 MB
1. Introduction/1. Course Structure.mp4 14.1 MB
11. Regex And Text Manipulation/5. Case Operations.mp4 14.0 MB
3. Series Methods And Handling/11. Solution.mp4 13.4 MB
2. Series At A Glance/16. Using Dot Notation.mp4 13.2 MB
12. Visualizing Data/2. The Art Of Data Visualization.mp4 13.0 MB
5. DataFrames In Depth/15. BONUS - Another Way.mp4 12.9 MB
3. Series Methods And Handling/1. Section Intro.mp4 12.9 MB
3. Series Methods And Handling/25. Pairwise Differences With diff().mp4 12.8 MB
2. Series At A Glance/2. What Is A Series.mp4 12.5 MB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.mp4 12.5 MB
3. Series Methods And Handling/18. nlargest() And nsmallest().mp4 12.2 MB
13. Data Formats And IO/9. Skill Challenge.mp4 11.7 MB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.mp4 11.6 MB
2. Series At A Glance/18. Extracting By Position With .iloc.mp4 11.6 MB
2. Series At A Glance/11. Another Solution.mp4 11.2 MB
3. Series Methods And Handling/8. The Other Side notnull() And notna().mp4 11.0 MB
4. Working With DataFrames/1. Section Intro.mp4 10.8 MB
12. Visualizing Data/1. Section Intro.mp4 10.3 MB
3. Series Methods And Handling/29. Skill Challenge.mp4 10.2 MB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.mp4 10.2 MB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.mp4 10.1 MB
3. Series Methods And Handling/21. Solution.mp4 9.9 MB
3. Series Methods And Handling/14. The describe() Method.mp4 9.7 MB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.mp4 8.9 MB
5. DataFrames In Depth/34. Skill Challenge.mp4 8.8 MB
2. Series At A Glance/3. Parameters vs Arguments.mp4 8.1 MB
7. Going MultiDimensional/23. Skill Challenge.mp4 8.0 MB
6. Working With Multiple DataFrames/1. Section Intro.mp4 8.0 MB
2. Series At A Glance/9. Skill Challenge.mp4 7.7 MB
12. Visualizing Data/11. Skill Challenge.mp4 7.5 MB
2. Series At A Glance/1. Section Intro.mp4 6.9 MB
4. Working With DataFrames/35. Another Skill Challenge.mp4 6.8 MB
2. Series At A Glance/22. Skill Challenge.mp4 6.4 MB
2. Series At A Glance/5. The .dtype Attribute.mp4 6.4 MB
3. Series Methods And Handling/5. The count() Method.mp4 6.0 MB
6. Working With Multiple DataFrames/10. Skill Challenge.mp4 6.0 MB
9. Reshaping With Pivots/12. Skill Challenge.mp4 5.5 MB
11. Regex And Text Manipulation/22. Skill Challenge.mp4 5.4 MB
5. DataFrames In Depth/28. Skill Challenge.mp4 5.3 MB
13. Data Formats And IO/1. Section Intro.mp4 5.2 MB
5. DataFrames In Depth/42. Skill Challenge.mp4 5.0 MB
10. Handling Date And Time/22. Skill Challenge.mp4 4.7 MB
5. DataFrames In Depth/17. Skill Challenge.mp4 4.5 MB
Sources/nutrition.csv 4.4 MB
4. Working With DataFrames/33. Skill Challenge.mp4 4.3 MB
4. Working With DataFrames/17. Skill Challenge.mp4 4.1 MB
8. GroupBy And Aggregates/20. Skill Challenge.mp4 4.1 MB
3. Series Methods And Handling/10. Skill Challenge.mp4 4.0 MB
5. DataFrames In Depth/9. Skill Challenge.mp4 4.0 MB
6. Working With Multiple DataFrames/20. Skill Challenge.mp4 3.8 MB
10. Handling Date And Time/12. Skill Challenge.mp4 3.8 MB
7. Going MultiDimensional/10. Skill Challenge.mp4 3.8 MB
11. Regex And Text Manipulation/10. Skill Challenge.mp4 3.2 MB
8. GroupBy And Aggregates/10. Skill Challenge.mp4 3.2 MB
3. Series Methods And Handling/20. Skill Challenge.mp4 3.2 MB
Sources/Visualizing_Data.ipynb.zip 500.7 KB
Sources/tech_giants (1).csv 467.2 KB
Sources/tech_giants.csv 467.2 KB
Sources/MemoryLayout.pdf 246.3 KB
Sources/games_sales (1).csv 236.9 KB
Sources/games_sales (2).csv 236.9 KB
Sources/games_sales.csv 236.9 KB
Sources/Vectorization.pdf 115.3 KB
Sources/SplitApplyCombine.pdf 114.8 KB
Sources/SelectionRecap.pdf 111.4 KB
Sources/WhatIsDtype.pdf 110.9 KB
Sources/MultiIndexInternals.pdf 110.7 KB
Sources/Working_With_DataFrames.zip 105.5 KB
Sources/Handling_Time_And_Date.ipynb.zip 104.7 KB
Sources/BrentOilPrices (1).csv 78.8 KB
Sources/BrentOilPrices.csv 78.8 KB
Sources/WhatIsASeries.pdf 74.8 KB
Sources/scores (1).csv 74.7 KB
Sources/scores.csv 74.7 KB
Sources/SelectionTerminology.pdf 66.7 KB
Sources/3KeyConcepts.pdf 63.0 KB
Sources/ConcatVsMerge.pdf 62.7 KB
Sources/WhatIsCSV.pdf 62.6 KB
Sources/TwosComplement.pdf 60.5 KB
Sources/DataFrames_In_Depth.zip 59.4 KB
Sources/DropnaWithSubset.pdf 58.8 KB
Sources/2017BostonMarathonTop1000 (1).csv 57.5 KB
Sources/2017BostonMarathonTop1000.csv 57.5 KB
Sources/DroppingAndFillingNA.pdf 56.5 KB
Sources/ViewVsCopy.pdf 53.3 KB
Sources/Lookup.pdf 49.7 KB
Sources/AppendVsConcat.pdf 49.4 KB
Sources/Transforms.pdf 47.3 KB
Sources/SortValueOrIndex.pdf 44.2 KB
Sources/BooleanMasks.pdf 43.9 KB
Sources/InnerVsOuter.pdf 43.7 KB
Sources/SeriesAtGlance.pdf 43.0 KB
Sources/Diff.pdf 42.5 KB
Sources/SizeAndShape.pdf 42.3 KB
Sources/SeriesAccounting.pdf 42.0 KB
Sources/Going_MultiDimensional.zip 41.9 KB
Sources/SeqVsVectorizedOperations.pdf 41.5 KB
Sources/LeftVsRight.pdf 40.8 KB
Sources/IdxminIdxmax.pdf 40.1 KB
Sources/Variance.pdf 38.0 KB
Sources/RangeVSInt64Index.pdf 37.8 KB
Sources/BoolsAsInts.pdf 37.5 KB
Sources/ValueCounts.pdf 36.0 KB
Sources/JoinCardinalities.pdf 35.3 KB
Sources/soccer.csv 33.7 KB
Sources/OurProcess.pdf 32.6 KB
Sources/Median.pdf 32.5 KB
Sources/MethodsVAttribtues.pdf 32.5 KB
Sources/Series_Methods_And_Handling.zip 31.8 KB
Sources/AtAndIat.pdf 30.6 KB
Sources/Regex_And_Text_Manipulation.ipynb.zip 29.8 KB
Sources/IndexingWithCallables.pdf 29.1 KB
Sources/MoreWaysToBuildDataframes.pdf 29.1 KB
Sources/Comparators.pdf 28.7 KB
Sources/Working_With_Multiple_DataFrames.zip 27.4 KB
Sources/ViewVsCopyHowDoWeTell.pdf 27.1 KB
Sources/Appendix_A_Rapid_Fire_Python_Fundamentals.ipynb.zip 25.6 KB
Sources/BinaryOperators.pdf 24.4 KB
Sources/Duplicates.pdf 24.3 KB
Sources/Data_Formats_And_I_O.ipynb.zip 23.6 KB
Sources/mid_career_salaries.csv 22.7 KB
Sources/GroupBy_And_Aggregates.ipynb.zip 22.4 KB
Sources/WhatsInTheData.pdf 19.2 KB
11. Regex And Text Manipulation/19. Is This A Valid Email.srt 18.6 KB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.srt 18.5 KB
Sources/ArgsVParams.pdf 18.4 KB
5. DataFrames In Depth/31. Same-shape Transforms.srt 18.1 KB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.srt 17.5 KB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.srt 17.4 KB
Sources/Reshaping_With_Pivots.ipynb.zip 17.1 KB
13. Data Formats And IO/3. Reading HTML.srt 16.4 KB
5. DataFrames In Depth/32. More Flexibility With apply().srt 16.4 KB
11. Regex And Text Manipulation/16. Introduction To Regular Expressions.srt 16.3 KB
5. DataFrames In Depth/33. Element-wise Operations With applymap().srt 16.0 KB
4. Working With DataFrames/22. Part I Collecting The Units.srt 15.5 KB
7. Going MultiDimensional/7. Indexing Ranges And Slices.srt 14.9 KB
11. Regex And Text Manipulation/23. Solution.srt 14.8 KB
3. Series Methods And Handling/28. Transforming With update(), apply() And map().srt 14.6 KB
5. DataFrames In Depth/14. Sorting vs. Reordering.srt 14.5 KB
12. Visualizing Data/3. The Preliminaries Of matplotlib.srt 14.4 KB
1. Introduction/7. NumPy.srt 14.3 KB
5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.srt 14.3 KB
1. Introduction/4. Jupyter Notebooks.srt 14.0 KB
14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.srt 13.7 KB
Sources/Series_At_Glance.zip 13.6 KB
12. Visualizing Data/4. Line Graphs.srt 13.6 KB
3. Series Methods And Handling/27. Filtering filter(), where(), And mask().srt 13.3 KB
11. Regex And Text Manipulation/18. How To Approach Regex.srt 13.3 KB
10. Handling Date And Time/21. BONUS Rolling Windows.srt 13.2 KB
6. Working With Multiple DataFrames/11. Solution.srt 13.1 KB
4. Working With DataFrames/26. Part II Merging Units With Column Names.srt 12.9 KB
5. DataFrames In Depth/19. Identifying Dupes.srt 12.9 KB
4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.srt 12.9 KB
7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.srt 12.7 KB
11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().srt 12.6 KB
10. Handling Date And Time/2. The Python datetime Module.srt 12.5 KB
11. Regex And Text Manipulation/17. More Regex Concepts.srt 12.4 KB
12. Visualizing Data/8. Scatter Plots.srt 12.2 KB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.srt 12.2 KB
5. DataFrames In Depth/5. Binary Operators With Booleans.srt 12.2 KB
4. Working With DataFrames/2. What Is A DataFrame.srt 12.0 KB
12. Visualizing Data/6. Pie Plots.srt 12.0 KB
4. Working With DataFrames/24. DataFrame dropna().srt 11.9 KB
12. Visualizing Data/5. Bar Charts.srt 11.9 KB
Sources/state.csv 11.6 KB
10. Handling Date And Time/3. Parsing Dates From Text.srt 11.6 KB
5. DataFrames In Depth/4. More Approaches To Boolean Masking.srt 11.6 KB
12. Visualizing Data/7. Histograms.srt 11.4 KB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.srt 11.4 KB
5. DataFrames In Depth/11. 2d Indexing.srt 11.4 KB
5. DataFrames In Depth/30. Calculating Aggregates With agg().srt 11.4 KB
5. DataFrames In Depth/40. Adding Rows To DataFrames.srt 11.3 KB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.srt 11.1 KB
10. Handling Date And Time/19. Upsampling And Interpolation.srt 11.1 KB
Sources/regions.csv 11.0 KB
10. Handling Date And Time/20. What About asfreq().srt 10.9 KB
5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().srt 10.9 KB
11. Regex And Text Manipulation/8. String Splitting And Concatenation.srt 10.8 KB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.srt 10.8 KB
3. Series Methods And Handling/6. Accessing And Counting NAs.srt 10.8 KB
5. DataFrames In Depth/38. View vs Copy.srt 10.7 KB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.srt 10.7 KB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.srt 10.6 KB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.srt 10.5 KB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.srt 10.5 KB
4. Working With DataFrames/28. Filtering in 2D.srt 10.5 KB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.srt 10.4 KB
8. GroupBy And Aggregates/15. Fine-tuned Aggregates.srt 10.4 KB
6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.srt 10.4 KB
10. Handling Date And Time/6. Performant Datetimes With Numpy.srt 10.3 KB
3. Series Methods And Handling/2. Reading In Data With read_csv().srt 10.3 KB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.srt 10.2 KB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.srt 10.2 KB
2. Series At A Glance/17. Boolean Masks And The .loc Indexer.srt 10.2 KB
7. Going MultiDimensional/11. Solution.srt 10.2 KB
12. Visualizing Data/9. Other Visualization Options.srt 10.2 KB
7. Going MultiDimensional/17. More MultiIndex Methods.srt 10.1 KB
7. Going MultiDimensional/24. Solution.srt 10.1 KB
5. DataFrames In Depth/39. Adding DataFrame Columns.srt 9.9 KB
13. Data Formats And IO/4. Reading Excel.srt 9.8 KB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.srt 9.8 KB
11. Regex And Text Manipulation/9. More Split Parameters.srt 9.8 KB
12. Visualizing Data/12. Solution.srt 9.8 KB
5. DataFrames In Depth/12. Fancy Indexing With lookup().srt 9.7 KB
4. Working With DataFrames/18. Solution.srt 9.7 KB
4. Working With DataFrames/14. DataFrame Extraction by Position.srt 9.7 KB
3. Series Methods And Handling/32. Solution III - Z-scores.srt 9.6 KB
Sources/folks.xlsx 9.5 KB
10. Handling Date And Time/18. Resampling Timeseries.srt 9.4 KB
8. GroupBy And Aggregates/18. GroupBy Transformations.srt 9.3 KB
6. Working With Multiple DataFrames/17. Many-to-Many Joins.srt 9.3 KB
3. Series Methods And Handling/13. Descriptive Statistics.srt 9.2 KB
10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.srt 9.1 KB
3. Series Methods And Handling/22. Series Arithmetics And fill_value().srt 9.1 KB
11. Regex And Text Manipulation/15. Text Replacement.srt 9.1 KB
6. Working With Multiple DataFrames/5. Enforcing Unique Indices.srt 9.1 KB
4. Working With DataFrames/25. BONUS - dropna() With Subset.srt 9.0 KB
4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.srt 8.9 KB
14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.srt 8.9 KB
5. DataFrames In Depth/37. The SettingWithCopy Warning.srt 8.9 KB
4. Working With DataFrames/23. The rename() Method.srt 8.9 KB
6. Working With Multiple DataFrames/3. Concatenating DataFrames.srt 8.8 KB
13. Data Formats And IO/10. Solution.srt 8.7 KB
4. Working With DataFrames/29. DataFrame Sorting.srt 8.7 KB
6. Working With Multiple DataFrames/4. The Duplicated Index Issue.srt 8.7 KB
4. Working With DataFrames/12. Changing The Index.srt 8.7 KB
11. Regex And Text Manipulation/3. String Methods In Python.srt 8.7 KB
2. Series At A Glance/13. Extracting By Index Position.srt 8.6 KB
14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.srt 8.6 KB
9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.srt 8.5 KB
14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.srt 8.5 KB
5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.srt 8.5 KB
8. GroupBy And Aggregates/19. BONUS - There's Also apply().srt 8.5 KB
2. Series At A Glance/7. Index And RangeIndex.srt 8.5 KB
9. Reshaping With Pivots/3. Pivoting Data.srt 8.5 KB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.srt 8.4 KB
5. DataFrames In Depth/7. Combining Conditions.srt 8.4 KB
6. Working With Multiple DataFrames/21. Solution.srt 8.3 KB
10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.srt 8.3 KB
11. Regex And Text Manipulation/7. Strips And Whitespace.srt 8.3 KB
5. DataFrames In Depth/25. Null Values In DataFrames.srt 8.2 KB
11. Regex And Text Manipulation/13. Masking With String Methods.srt 8.2 KB
3. Series Methods And Handling/15. mode() And value_counts().srt 8.1 KB
4. Working With DataFrames/13. Extracting From DataFrames By Label.srt 8.1 KB
13. Data Formats And IO/6. BONUS Introduction To Pickling.srt 8.0 KB
5. DataFrames In Depth/29. Solution.srt 8.0 KB
2. Series At A Glance/14. Accessing Elements By Label.srt 7.9 KB
8. GroupBy And Aggregates/16. Named Aggregations.srt 7.9 KB
14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.srt 7.9 KB
14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.srt 7.8 KB
5. DataFrames In Depth/36. Setting DataFrame Values.srt 7.8 KB
7. Going MultiDimensional/19. The Flipside unstack().srt 7.7 KB
11. Regex And Text Manipulation/6. Finding Characters And Words.srt 7.6 KB
15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.srt 7.6 KB
5. DataFrames In Depth/13. Sorting By Index Or Column.srt 7.6 KB
7. Going MultiDimensional/15. Removing MultiIndex Levels.srt 7.6 KB
7. Going MultiDimensional/16. MultiIndex sort_index().srt 7.6 KB
5. DataFrames In Depth/10. Solution.srt 7.5 KB
4. Working With DataFrames/16. BONUS - The get_loc() Method.srt 7.4 KB
4. Working With DataFrames/36. Solution.srt 7.4 KB
4. Working With DataFrames/27. Part III Removing Units From Values.srt 7.3 KB
4. Working With DataFrames/20. The astype() Method.srt 7.3 KB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.srt 7.2 KB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.srt 7.1 KB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().srt 7.1 KB
5. DataFrames In Depth/43. Solution.srt 7.1 KB
7. Going MultiDimensional/18. Reshaping With stack().srt 7.1 KB
1. Introduction/5. Cloud vs Local.srt 7.0 KB
11. Regex And Text Manipulation/12. Slicing Substrings.srt 7.0 KB
9. Reshaping With Pivots/6. The pivot_table().srt 7.0 KB
4. Working With DataFrames/30. Using Series between() With DataFrames.srt 7.0 KB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.srt 6.9 KB
7. Going MultiDimensional/9. Cross Sections With xs().srt 6.9 KB
10. Handling Date And Time/15. Creating Date Ranges.srt 6.9 KB
7. Going MultiDimensional/13. Adding Another Level.srt 6.8 KB
2. Series At A Glance/4. What’s In The Data.srt 6.8 KB
6. Working With Multiple DataFrames/12. The merge() Method.srt 6.8 KB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.srt 6.8 KB
10. Handling Date And Time/23. Solution.srt 6.7 KB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.srt 6.7 KB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.srt 6.7 KB
9. Reshaping With Pivots/5. What About Aggregates.srt 6.7 KB
8. GroupBy And Aggregates/14. MultiIndex Grouping.srt 6.6 KB
5. DataFrames In Depth/20. Removing Duplicates.srt 6.6 KB
8. GroupBy And Aggregates/17. The filter() Method.srt 6.6 KB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.srt 6.6 KB
9. Reshaping With Pivots/4. Undoing Pivots.srt 6.6 KB
2. Series At A Glance/21. Selection Recap.srt 6.5 KB
4. Working With DataFrames/34. Solution.srt 6.5 KB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.srt 6.5 KB
2. Series At A Glance/23. Solution.srt 6.5 KB
3. Series Methods And Handling/16. idxmax() And idxmin().srt 6.5 KB
9. Reshaping With Pivots/13. Solution.srt 6.4 KB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.srt 6.4 KB
8. GroupBy And Aggregates/4. Conditional Aggregates.srt 6.4 KB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.srt 6.4 KB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.srt 6.3 KB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.srt 6.3 KB
8. GroupBy And Aggregates/11. Solution.srt 6.3 KB
8. GroupBy And Aggregates/3. Simple Aggregations Review.srt 6.2 KB
2. Series At A Glance/8. Series And Index Names.srt 6.2 KB
6. Working With Multiple DataFrames/18. Merging By Index.srt 6.2 KB
8. GroupBy And Aggregates/21. Solution.srt 6.2 KB
2. Series At A Glance/12. The head() And tail() Methods.srt 6.2 KB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.srt 6.2 KB
10. Handling Date And Time/7. The Pandas Timestamp.srt 6.1 KB
5. DataFrames In Depth/35. Solution.srt 6.1 KB
7. Going MultiDimensional/2. Introducing New Data.srt 6.0 KB
13. Data Formats And IO/7. Pickles In Pandas.srt 6.0 KB
7. Going MultiDimensional/14. Shuffling Levels.srt 5.9 KB
10. Handling Date And Time/5. From Datetime To String.srt 5.9 KB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.srt 5.9 KB
6. Working With Multiple DataFrames/9. Concat On Different Columns.srt 5.9 KB
4. Working With DataFrames/15. Single Value Access With .at And .iat.srt 5.8 KB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.srt 5.8 KB
3. Series Methods And Handling/24. Cumulative Operations.srt 5.7 KB
8. GroupBy And Aggregates/9. BONUS - Series groupby().srt 5.7 KB
3. Series Methods And Handling/7. BONUS Another Approach.srt 5.7 KB
2. Series At A Glance/20. Selecting With .get().srt 5.7 KB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.srt 5.7 KB
10. Handling Date And Time/8. Our Dataset Brent Prices.srt 5.7 KB
3. Series Methods And Handling/17. Sorting With sort_values().srt 5.7 KB
10. Handling Date And Time/11. Indexing Dates.srt 5.6 KB
13. Data Formats And IO/2. Reading JSON.srt 5.6 KB
9. Reshaping With Pivots/9. Adding Margins.srt 5.5 KB
8. GroupBy And Aggregates/6. The groupby() Method.srt 5.5 KB
4. Working With DataFrames/3. Creating A DataFrame.srt 5.5 KB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().srt 5.4 KB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.srt 5.4 KB
8. GroupBy And Aggregates/13. Handpicking Subgroups.srt 5.4 KB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().srt 5.3 KB
5. DataFrames In Depth/8. Conditions As Variables.srt 5.3 KB
4. Working With DataFrames/5. The info() Method.srt 5.3 KB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.srt 5.3 KB
5. DataFrames In Depth/23. BONUS - Another Way pop().srt 5.3 KB
1. Introduction/6. Hello, Python.srt 5.2 KB
10. Handling Date And Time/4. Even Better dateutil.srt 5.2 KB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.srt 5.2 KB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.srt 5.2 KB
3. Series Methods And Handling/12. Dropping And Filling NAs.srt 5.1 KB
7. Going MultiDimensional/3. Index And RangeIndex.srt 5.1 KB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.srt 5.1 KB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.srt 5.1 KB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.srt 5.0 KB
4. Working With DataFrames/11. DataFrame Axes.srt 5.0 KB
11. Regex And Text Manipulation/11. Solution.srt 4.9 KB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.srt 4.9 KB
7. Going MultiDimensional/5. MultiIndex From read_csv().srt 4.8 KB
4. Working With DataFrames/8. The sample() Method.srt 4.8 KB
13. Data Formats And IO/8. The Many Other Formats.srt 4.8 KB
2. Series At A Glance/2. What Is A Series.srt 4.8 KB
9. Reshaping With Pivots/11. Applying Multiple Functions.srt 4.8 KB
2. Series At A Glance/10. Solution.srt 4.7 KB
3. Series Methods And Handling/26. Series Iteration.srt 4.7 KB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.srt 4.7 KB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.srt 4.6 KB
7. Going MultiDimensional/4. Creating A MultiIndex.srt 4.6 KB
4. Working With DataFrames/6. Reading In Nutrition Data.srt 4.6 KB
5. DataFrames In Depth/2. Introducing A New Dataset.srt 4.5 KB
2. Series At A Glance/16. Using Dot Notation.srt 4.5 KB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.srt 4.5 KB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.srt 4.4 KB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.srt 4.4 KB
6. Working With Multiple DataFrames/15. Left vs Right Joins.srt 4.4 KB
5. DataFrames In Depth/18. Solution.srt 4.4 KB
2. Series At A Glance/18. Extracting By Position With .iloc.srt 4.4 KB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.srt 4.3 KB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.srt 4.3 KB
3. Series Methods And Handling/25. Pairwise Differences With diff().srt 4.3 KB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.srt 4.3 KB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.srt 4.3 KB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().srt 4.2 KB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.srt 4.1 KB
8. GroupBy And Aggregates/12. Iterating Through Groups.srt 4.1 KB
Sources/drinks (1).csv 4.1 KB
Sources/drinks (2).csv 4.1 KB
Sources/drinks.csv 4.1 KB
3. Series Methods And Handling/19. Sorting With sort_index().srt 4.0 KB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.srt 4.0 KB
7. Going MultiDimensional/22. BONUS - What About Panels.srt 4.0 KB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.srt 4.0 KB
10. Handling Date And Time/13. Solution.srt 3.9 KB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.srt 3.9 KB
4. Working With DataFrames/19. More Cleanup Going Numeric.srt 3.9 KB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.srt 3.8 KB
8. GroupBy And Aggregates/2. New Data Game Sales.srt 3.8 KB
1. Introduction/3. Anaconda.srt 3.8 KB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.srt 3.7 KB
3. Series Methods And Handling/11. Solution.srt 3.7 KB
11. Regex And Text Manipulation/5. Case Operations.srt 3.6 KB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.srt 3.6 KB
2. Series At A Glance/11. Another Solution.srt 3.6 KB
12. Visualizing Data/2. The Art Of Data Visualization.srt 3.6 KB
5. DataFrames In Depth/22. BONUS - Removing Columns.srt 3.5 KB
13. Data Formats And IO/9. Skill Challenge.srt 3.5 KB
5. DataFrames In Depth/21. Removing DataFrame Rows.srt 3.4 KB
2. Series At A Glance/3. Parameters vs Arguments.srt 3.3 KB
3. Series Methods And Handling/18. nlargest() And nsmallest().srt 3.3 KB
3. Series Methods And Handling/8. The Other Side notnull() And notna().srt 3.2 KB
7. Going MultiDimensional/21. An Easier Way transpose().srt 3.2 KB
3. Series Methods And Handling/29. Skill Challenge.srt 3.2 KB
6. Working With Multiple DataFrames/19. The join() Method.srt 3.2 KB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().srt 3.1 KB
5. DataFrames In Depth/1. Section Intro.srt 3.1 KB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.srt 3.0 KB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.srt 2.9 KB
Sources/liberal_arts.csv 2.9 KB
3. Series Methods And Handling/5. The count() Method.srt 2.8 KB
2. Series At A Glance/9. Skill Challenge.srt 2.8 KB
5. DataFrames In Depth/15. BONUS - Another Way.srt 2.6 KB
5. DataFrames In Depth/34. Skill Challenge.srt 2.6 KB
3. Series Methods And Handling/30. Solution I - Reading Data.srt 2.6 KB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.srt 2.6 KB
2. Series At A Glance/5. The .dtype Attribute.srt 2.5 KB
3. Series Methods And Handling/14. The describe() Method.srt 2.5 KB
3. Series Methods And Handling/21. Solution.srt 2.5 KB
1. Introduction/2. Pandas Is Not Single.srt 2.5 KB
3. Series Methods And Handling/1. Section Intro.srt 2.4 KB
4. Working With DataFrames/35. Another Skill Challenge.srt 2.3 KB
2. Series At A Glance/22. Skill Challenge.srt 2.3 KB
7. Going MultiDimensional/1. Section Intro.srt 2.3 KB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.srt 2.3 KB
4. Working With DataFrames/1. Section Intro.srt 2.3 KB
11. Regex And Text Manipulation/1. Section Intro.srt 2.3 KB
6. Working With Multiple DataFrames/10. Skill Challenge.srt 2.1 KB
12. Visualizing Data/11. Skill Challenge.srt 2.0 KB
5. DataFrames In Depth/42. Skill Challenge.srt 2.0 KB
7. Going MultiDimensional/23. Skill Challenge.srt 1.9 KB
11. Regex And Text Manipulation/22. Skill Challenge.srt 1.9 KB
5. DataFrames In Depth/28. Skill Challenge.srt 1.8 KB
1. Introduction/1. Course Structure.srt 1.8 KB
10. Handling Date And Time/22. Skill Challenge.srt 1.7 KB
4. Working With DataFrames/17. Skill Challenge.srt 1.7 KB
4. Working With DataFrames/33. Skill Challenge.srt 1.7 KB
12. Visualizing Data/1. Section Intro.srt 1.7 KB
7. Going MultiDimensional/10. Skill Challenge.srt 1.7 KB
9. Reshaping With Pivots/12. Skill Challenge.srt 1.6 KB
10. Handling Date And Time/1. Section Intro.srt 1.6 KB
9. Reshaping With Pivots/1. Section Intro.srt 1.5 KB
Sources/eng.csv 1.5 KB
8. GroupBy And Aggregates/20. Skill Challenge.srt 1.5 KB
6. Working With Multiple DataFrames/1. Section Intro.srt 1.5 KB
5. DataFrames In Depth/9. Skill Challenge.srt 1.5 KB
3. Series Methods And Handling/10. Skill Challenge.srt 1.5 KB
8. GroupBy And Aggregates/1. Section Intro.srt 1.5 KB
5. DataFrames In Depth/17. Skill Challenge.srt 1.5 KB
Sources/portfolio.zip 1.4 KB
6. Working With Multiple DataFrames/20. Skill Challenge.srt 1.4 KB
11. Regex And Text Manipulation/10. Skill Challenge.srt 1.3 KB
2. Series At A Glance/1. Section Intro.srt 1.3 KB
10. Handling Date And Time/12. Skill Challenge.srt 1.3 KB
3. Series Methods And Handling/20. Skill Challenge.srt 1.2 KB
8. GroupBy And Aggregates/10. Skill Challenge.srt 1.2 KB
13. Data Formats And IO/1. Section Intro.srt 1.1 KB
Sources/ivies.csv 548 bytes
Sources/folks.json 244 bytes

[Udemy] The Ultimate Pandas Bootcamp Advanced Python Data Analysis (2021)

File List

Download Torrent

Related Resources

Copyright Infringement