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[FreeCourseSite.com] Udemy - The Ultimate Pandas Bootcamp Advanced Python Data Analysis
magnet:?xt=urn:btih:a0c4d102befdc70c9df1368c0ee9f671ad3da227&dn=[FreeCourseSite.com] Udemy - The Ultimate Pandas Bootcamp Advanced Python Data Analysis
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Hash值:
a0c4d102befdc70c9df1368c0ee9f671ad3da227
点击数:
147
文件大小:
9.62 GB
文件数量:
319
创建日期:
2022-4-25 12:36
最后访问:
2024-7-2 02:39
访问标签:
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com
Udemy
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The
Ultimate
Pandas
Bootcamp
Advanced
Python
Data
Analysis
文件列表详情
1. Introduction/1. Course Structure.mp4 14.06 MB
1. Introduction/2. Pandas Is Not Single.mp4 17.81 MB
1. Introduction/3. Anaconda.mp4 20.71 MB
1. Introduction/4. Jupyter Notebooks.mp4 48.02 MB
1. Introduction/5. Cloud vs Local.mp4 26.53 MB
1. Introduction/6. Hello, Python.mp4 32.79 MB
1. Introduction/7. NumPy.mp4 62.19 MB
10. Handling Date And Time/1. Section Intro.mp4 22.33 MB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.mp4 17.61 MB
10. Handling Date And Time/11. Indexing Dates.mp4 26.63 MB
10. Handling Date And Time/12. Skill Challenge.mp4 3.79 MB
10. Handling Date And Time/13. Solution.mp4 17.1 MB
10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.mp4 38.15 MB
10. Handling Date And Time/15. Creating Date Ranges.mp4 36.53 MB
10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.mp4 36.22 MB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.mp4 28.36 MB
10. Handling Date And Time/18. Resampling Timeseries.mp4 38.53 MB
10. Handling Date And Time/19. Upsampling And Interpolation.mp4 49.4 MB
10. Handling Date And Time/2. The Python datetime Module.mp4 40.29 MB
10. Handling Date And Time/20. What About asfreq().mp4 36.61 MB
10. Handling Date And Time/21. BONUS Rolling Windows.mp4 43.49 MB
10. Handling Date And Time/22. Skill Challenge.mp4 4.65 MB
10. Handling Date And Time/23. Solution.mp4 22.9 MB
10. Handling Date And Time/3. Parsing Dates From Text.mp4 52.82 MB
10. Handling Date And Time/4. Even Better dateutil.mp4 23.85 MB
10. Handling Date And Time/5. From Datetime To String.mp4 22.37 MB
10. Handling Date And Time/6. Performant Datetimes With Numpy.mp4 35.33 MB
10. Handling Date And Time/7. The Pandas Timestamp.mp4 24.04 MB
10. Handling Date And Time/8. Our Dataset Brent Prices.mp4 29.43 MB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.mp4 24.53 MB
11. Regex And Text Manipulation/1. Section Intro.mp4 16.68 MB
11. Regex And Text Manipulation/10. Skill Challenge.mp4 3.23 MB
11. Regex And Text Manipulation/11. Solution.mp4 21.97 MB
11. Regex And Text Manipulation/12. Slicing Substrings.mp4 24.19 MB
11. Regex And Text Manipulation/13. Masking With String Methods.mp4 36.91 MB
11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().mp4 66.3 MB
11. Regex And Text Manipulation/15. Text Replacement.mp4 41.78 MB
11. Regex And Text Manipulation/16. Introduction To Regular Expressions.mp4 75.02 MB
11. Regex And Text Manipulation/17. More Regex Concepts.mp4 65.17 MB
11. Regex And Text Manipulation/18. How To Approach Regex.mp4 63.52 MB
11. Regex And Text Manipulation/19. Is This A Valid Email.mp4 80.08 MB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.mp4 23.57 MB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().mp4 18.31 MB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.mp4 76.29 MB
11. Regex And Text Manipulation/22. Skill Challenge.mp4 5.42 MB
11. Regex And Text Manipulation/23. Solution.mp4 72.37 MB
11. Regex And Text Manipulation/3. String Methods In Python.mp4 28.77 MB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.mp4 18.43 MB
11. Regex And Text Manipulation/5. Case Operations.mp4 14.03 MB
11. Regex And Text Manipulation/6. Finding Characters And Words.mp4 25.73 MB
11. Regex And Text Manipulation/7. Strips And Whitespace.mp4 31.73 MB
11. Regex And Text Manipulation/8. String Splitting And Concatenation.mp4 46.35 MB
11. Regex And Text Manipulation/9. More Split Parameters.mp4 40.08 MB
12. Visualizing Data/1. Section Intro.mp4 10.33 MB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.mp4 32.34 MB
12. Visualizing Data/11. Skill Challenge.mp4 7.52 MB
12. Visualizing Data/12. Solution.mp4 54.25 MB
12. Visualizing Data/2. The Art Of Data Visualization.mp4 13.01 MB
12. Visualizing Data/3. The Preliminaries Of matplotlib.mp4 62.88 MB
12. Visualizing Data/4. Line Graphs.mp4 54.18 MB
12. Visualizing Data/5. Bar Charts.mp4 50.14 MB
12. Visualizing Data/6. Pie Plots.mp4 54.89 MB
12. Visualizing Data/7. Histograms.mp4 45.78 MB
12. Visualizing Data/8. Scatter Plots.mp4 63.39 MB
12. Visualizing Data/9. Other Visualization Options.mp4 63.65 MB
13. Data Formats And IO/1. Section Intro.mp4 5.21 MB
13. Data Formats And IO/10. Solution.mp4 45.82 MB
13. Data Formats And IO/2. Reading JSON.mp4 19.74 MB
13. Data Formats And IO/3. Reading HTML.mp4 103.72 MB
13. Data Formats And IO/4. Reading Excel.mp4 55.72 MB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.mp4 74.01 MB
13. Data Formats And IO/6. BONUS Introduction To Pickling.mp4 31.71 MB
13. Data Formats And IO/7. Pickles In Pandas.mp4 22.93 MB
13. Data Formats And IO/8. The Many Other Formats.mp4 27.91 MB
13. Data Formats And IO/9. Skill Challenge.mp4 11.71 MB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.mp4 8.88 MB
14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.mp4 27.56 MB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.mp4 32.99 MB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.mp4 20.03 MB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.mp4 52.97 MB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.mp4 22.74 MB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.mp4 36.32 MB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.mp4 19.28 MB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.mp4 41.66 MB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.mp4 15.92 MB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.mp4 20.57 MB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.mp4 10.16 MB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.mp4 23.72 MB
14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.mp4 29.23 MB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.mp4 19.14 MB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.mp4 17.19 MB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.mp4 31.78 MB
14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.mp4 57.77 MB
14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.mp4 30.44 MB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.mp4 23.21 MB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.mp4 34.15 MB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.mp4 39.13 MB
14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.mp4 27.46 MB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.mp4 42.8 MB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.mp4 21.88 MB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.mp4 32.13 MB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.mp4 25.33 MB
14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.mp4 29.49 MB
15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.mp4 71.34 MB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.mp4 17.14 MB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.mp4 30.95 MB
2. Series At A Glance/1. Section Intro.mp4 6.93 MB
2. Series At A Glance/10. Solution.mp4 22.9 MB
2. Series At A Glance/11. Another Solution.mp4 11.24 MB
2. Series At A Glance/12. The head() And tail() Methods.mp4 22.98 MB
2. Series At A Glance/13. Extracting By Index Position.mp4 29.06 MB
2. Series At A Glance/14. Accessing Elements By Label.mp4 27.06 MB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.mp4 16.49 MB
2. Series At A Glance/16. Using Dot Notation.mp4 13.25 MB
2. Series At A Glance/17. Boolean Masks And The .loc Indexer.mp4 29.47 MB
2. Series At A Glance/18. Extracting By Position With .iloc.mp4 11.61 MB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.mp4 37.14 MB
2. Series At A Glance/2. What Is A Series.mp4 12.54 MB
2. Series At A Glance/20. Selecting With .get().mp4 30.55 MB
2. Series At A Glance/21. Selection Recap.mp4 28.19 MB
2. Series At A Glance/22. Skill Challenge.mp4 6.38 MB
2. Series At A Glance/23. Solution.mp4 23.39 MB
2. Series At A Glance/3. Parameters vs Arguments.mp4 8.07 MB
2. Series At A Glance/4. What’s In The Data.mp4 20.41 MB
2. Series At A Glance/5. The .dtype Attribute.mp4 6.37 MB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.mp4 10.1 MB
2. Series At A Glance/7. Index And RangeIndex.mp4 33.16 MB
2. Series At A Glance/8. Series And Index Names.mp4 19.12 MB
2. Series At A Glance/9. Skill Challenge.mp4 7.71 MB
3. Series Methods And Handling/1. Section Intro.mp4 12.93 MB
3. Series Methods And Handling/10. Skill Challenge.mp4 4.05 MB
3. Series Methods And Handling/11. Solution.mp4 13.45 MB
3. Series Methods And Handling/12. Dropping And Filling NAs.mp4 21.52 MB
3. Series Methods And Handling/13. Descriptive Statistics.mp4 33.67 MB
3. Series Methods And Handling/14. The describe() Method.mp4 9.7 MB
3. Series Methods And Handling/15. mode() And value_counts().mp4 31.73 MB
3. Series Methods And Handling/16. idxmax() And idxmin().mp4 22 MB
3. Series Methods And Handling/17. Sorting With sort_values().mp4 19.63 MB
3. Series Methods And Handling/18. nlargest() And nsmallest().mp4 12.17 MB
3. Series Methods And Handling/19. Sorting With sort_index().mp4 15.3 MB
3. Series Methods And Handling/2. Reading In Data With read_csv().mp4 52.81 MB
3. Series Methods And Handling/20. Skill Challenge.mp4 3.18 MB
3. Series Methods And Handling/21. Solution.mp4 9.91 MB
3. Series Methods And Handling/22. Series Arithmetics And fill_value().mp4 40.2 MB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.mp4 17.36 MB
3. Series Methods And Handling/24. Cumulative Operations.mp4 17.94 MB
3. Series Methods And Handling/25. Pairwise Differences With diff().mp4 12.79 MB
3. Series Methods And Handling/26. Series Iteration.mp4 16.07 MB
3. Series Methods And Handling/27. Filtering filter(), where(), And mask().mp4 55.05 MB
3. Series Methods And Handling/28. Transforming With update(), apply() And map().mp4 69.92 MB
3. Series Methods And Handling/29. Skill Challenge.mp4 10.2 MB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().mp4 23.26 MB
3. Series Methods And Handling/30. Solution I - Reading Data.mp4 14.55 MB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.mp4 20.47 MB
3. Series Methods And Handling/32. Solution III - Z-scores.mp4 48.2 MB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.mp4 17.8 MB
3. Series Methods And Handling/5. The count() Method.mp4 6.03 MB
3. Series Methods And Handling/6. Accessing And Counting NAs.mp4 36.79 MB
3. Series Methods And Handling/7. BONUS Another Approach.mp4 21.33 MB
3. Series Methods And Handling/8. The Other Side notnull() And notna().mp4 11.04 MB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.mp4 11.62 MB
4. Working With DataFrames/1. Section Intro.mp4 10.81 MB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.mp4 42.94 MB
4. Working With DataFrames/11. DataFrame Axes.mp4 23.31 MB
4. Working With DataFrames/12. Changing The Index.mp4 50.38 MB
4. Working With DataFrames/13. Extracting From DataFrames By Label.mp4 36.01 MB
4. Working With DataFrames/14. DataFrame Extraction by Position.mp4 46.71 MB
4. Working With DataFrames/15. Single Value Access With .at And .iat.mp4 26.34 MB
4. Working With DataFrames/16. BONUS - The get_loc() Method.mp4 25.07 MB
4. Working With DataFrames/17. Skill Challenge.mp4 4.1 MB
4. Working With DataFrames/18. Solution.mp4 45.19 MB
4. Working With DataFrames/19. More Cleanup Going Numeric.mp4 18.63 MB
4. Working With DataFrames/2. What Is A DataFrame.mp4 45.86 MB
4. Working With DataFrames/20. The astype() Method.mp4 25.17 MB
4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.mp4 44.28 MB
4. Working With DataFrames/22. Part I Collecting The Units.mp4 66.82 MB
4. Working With DataFrames/23. The rename() Method.mp4 27.59 MB
4. Working With DataFrames/24. DataFrame dropna().mp4 40.08 MB
4. Working With DataFrames/25. BONUS - dropna() With Subset.mp4 29.26 MB
4. Working With DataFrames/26. Part II Merging Units With Column Names.mp4 57.28 MB
4. Working With DataFrames/27. Part III Removing Units From Values.mp4 35.62 MB
4. Working With DataFrames/28. Filtering in 2D.mp4 42.35 MB
4. Working With DataFrames/29. DataFrame Sorting.mp4 49.42 MB
4. Working With DataFrames/3. Creating A DataFrame.mp4 22.42 MB
4. Working With DataFrames/30. Using Series between() With DataFrames.mp4 34.97 MB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4 62.98 MB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().mp4 35.36 MB
4. Working With DataFrames/33. Skill Challenge.mp4 4.31 MB
4. Working With DataFrames/34. Solution.mp4 42.25 MB
4. Working With DataFrames/35. Another Skill Challenge.mp4 6.79 MB
4. Working With DataFrames/36. Solution.mp4 36.86 MB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.mp4 73.23 MB
4. Working With DataFrames/5. The info() Method.mp4 19.04 MB
4. Working With DataFrames/6. Reading In Nutrition Data.mp4 27.29 MB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.mp4 35.62 MB
4. Working With DataFrames/8. The sample() Method.mp4 22.61 MB
4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.mp4 40.48 MB
5. DataFrames In Depth/1. Section Intro.mp4 21.13 MB
5. DataFrames In Depth/10. Solution.mp4 40.04 MB
5. DataFrames In Depth/11. 2d Indexing.mp4 40.02 MB
5. DataFrames In Depth/12. Fancy Indexing With lookup().mp4 46.21 MB
5. DataFrames In Depth/13. Sorting By Index Or Column.mp4 45.02 MB
5. DataFrames In Depth/14. Sorting vs. Reordering.mp4 65.24 MB
5. DataFrames In Depth/15. BONUS - Another Way.mp4 12.95 MB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.mp4 17.07 MB
5. DataFrames In Depth/17. Skill Challenge.mp4 4.48 MB
5. DataFrames In Depth/18. Solution.mp4 25.76 MB
5. DataFrames In Depth/19. Identifying Dupes.mp4 60.88 MB
5. DataFrames In Depth/2. Introducing A New Dataset.mp4 18.3 MB
5. DataFrames In Depth/20. Removing Duplicates.mp4 29.82 MB
5. DataFrames In Depth/21. Removing DataFrame Rows.mp4 19.78 MB
5. DataFrames In Depth/22. BONUS - Removing Columns.mp4 16.19 MB
5. DataFrames In Depth/23. BONUS - Another Way pop().mp4 19.07 MB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.mp4 33.17 MB
5. DataFrames In Depth/25. Null Values In DataFrames.mp4 42.16 MB
5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.mp4 49 MB
5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().mp4 57.38 MB
5. DataFrames In Depth/28. Skill Challenge.mp4 5.3 MB
5. DataFrames In Depth/29. Solution.mp4 42.49 MB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.mp4 23.33 MB
5. DataFrames In Depth/30. Calculating Aggregates With agg().mp4 37.08 MB
5. DataFrames In Depth/31. Same-shape Transforms.mp4 66.98 MB
5. DataFrames In Depth/32. More Flexibility With apply().mp4 59.38 MB
5. DataFrames In Depth/33. Element-wise Operations With applymap().mp4 68.51 MB
5. DataFrames In Depth/34. Skill Challenge.mp4 8.76 MB
5. DataFrames In Depth/35. Solution.mp4 26.47 MB
5. DataFrames In Depth/36. Setting DataFrame Values.mp4 43.55 MB
5. DataFrames In Depth/37. The SettingWithCopy Warning.mp4 39.81 MB
5. DataFrames In Depth/38. View vs Copy.mp4 49.3 MB
5. DataFrames In Depth/39. Adding DataFrame Columns.mp4 36.47 MB
5. DataFrames In Depth/4. More Approaches To Boolean Masking.mp4 68.42 MB
5. DataFrames In Depth/40. Adding Rows To DataFrames.mp4 49.9 MB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.mp4 21.73 MB
5. DataFrames In Depth/42. Skill Challenge.mp4 5.04 MB
5. DataFrames In Depth/43. Solution.mp4 31.94 MB
5. DataFrames In Depth/5. Binary Operators With Booleans.mp4 37.94 MB
5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.mp4 50.47 MB
5. DataFrames In Depth/7. Combining Conditions.mp4 45.57 MB
5. DataFrames In Depth/8. Conditions As Variables.mp4 19.9 MB
5. DataFrames In Depth/9. Skill Challenge.mp4 3.96 MB
6. Working With Multiple DataFrames/1. Section Intro.mp4 7.95 MB
6. Working With Multiple DataFrames/10. Skill Challenge.mp4 5.99 MB
6. Working With Multiple DataFrames/11. Solution.mp4 59.47 MB
6. Working With Multiple DataFrames/12. The merge() Method.mp4 35.38 MB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.mp4 32.2 MB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.mp4 27.11 MB
6. Working With Multiple DataFrames/15. Left vs Right Joins.mp4 20.27 MB
6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.mp4 57.01 MB
6. Working With Multiple DataFrames/17. Many-to-Many Joins.mp4 55.62 MB
6. Working With Multiple DataFrames/18. Merging By Index.mp4 38.15 MB
6. Working With Multiple DataFrames/19. The join() Method.mp4 22.87 MB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.mp4 40.6 MB
6. Working With Multiple DataFrames/20. Skill Challenge.mp4 3.81 MB
6. Working With Multiple DataFrames/21. Solution.mp4 46.08 MB
6. Working With Multiple DataFrames/3. Concatenating DataFrames.mp4 42.12 MB
6. Working With Multiple DataFrames/4. The Duplicated Index Issue.mp4 51.32 MB
6. Working With Multiple DataFrames/5. Enforcing Unique Indices.mp4 58.39 MB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().mp4 28.45 MB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.mp4 27.09 MB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().mp4 14.48 MB
6. Working With Multiple DataFrames/9. Concat On Different Columns.mp4 38.21 MB
7. Going MultiDimensional/1. Section Intro.mp4 26.42 MB
7. Going MultiDimensional/10. Skill Challenge.mp4 3.78 MB
7. Going MultiDimensional/11. Solution.mp4 44.8 MB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.mp4 34.85 MB
7. Going MultiDimensional/13. Adding Another Level.mp4 33.59 MB
7. Going MultiDimensional/14. Shuffling Levels.mp4 24.32 MB
7. Going MultiDimensional/15. Removing MultiIndex Levels.mp4 37.7 MB
7. Going MultiDimensional/16. MultiIndex sort_index().mp4 35.62 MB
7. Going MultiDimensional/17. More MultiIndex Methods.mp4 37.92 MB
7. Going MultiDimensional/18. Reshaping With stack().mp4 30.57 MB
7. Going MultiDimensional/19. The Flipside unstack().mp4 45.95 MB
7. Going MultiDimensional/2. Introducing New Data.mp4 22.11 MB
7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.mp4 58.73 MB
7. Going MultiDimensional/21. An Easier Way transpose().mp4 18.6 MB
7. Going MultiDimensional/22. BONUS - What About Panels.mp4 27.89 MB
7. Going MultiDimensional/23. Skill Challenge.mp4 8.01 MB
7. Going MultiDimensional/24. Solution.mp4 49.18 MB
7. Going MultiDimensional/3. Index And RangeIndex.mp4 26.87 MB
7. Going MultiDimensional/4. Creating A MultiIndex.mp4 20.15 MB
7. Going MultiDimensional/5. MultiIndex From read_csv().mp4 27.7 MB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.mp4 39.39 MB
7. Going MultiDimensional/7. Indexing Ranges And Slices.mp4 59.11 MB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.mp4 16.97 MB
7. Going MultiDimensional/9. Cross Sections With xs().mp4 33.15 MB
8. GroupBy And Aggregates/1. Section Intro.mp4 17.09 MB
8. GroupBy And Aggregates/10. Skill Challenge.mp4 3.22 MB
8. GroupBy And Aggregates/11. Solution.mp4 27.59 MB
8. GroupBy And Aggregates/12. Iterating Through Groups.mp4 21.03 MB
8. GroupBy And Aggregates/13. Handpicking Subgroups.mp4 23.65 MB
8. GroupBy And Aggregates/14. MultiIndex Grouping.mp4 26.54 MB
8. GroupBy And Aggregates/15. Fine-tuned Aggregates.mp4 44.14 MB
8. GroupBy And Aggregates/16. Named Aggregations.mp4 36.49 MB
8. GroupBy And Aggregates/17. The filter() Method.mp4 26.12 MB
8. GroupBy And Aggregates/18. GroupBy Transformations.mp4 38.79 MB
8. GroupBy And Aggregates/19. BONUS - There's Also apply().mp4 41.18 MB
8. GroupBy And Aggregates/2. New Data Game Sales.mp4 14.89 MB
8. GroupBy And Aggregates/20. Skill Challenge.mp4 4.05 MB
8. GroupBy And Aggregates/21. Solution.mp4 24.51 MB
8. GroupBy And Aggregates/3. Simple Aggregations Review.mp4 29.02 MB
8. GroupBy And Aggregates/4. Conditional Aggregates.mp4 24.51 MB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.mp4 22.51 MB
8. GroupBy And Aggregates/6. The groupby() Method.mp4 21.56 MB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.mp4 19.81 MB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.mp4 20.48 MB
8. GroupBy And Aggregates/9. BONUS - Series groupby().mp4 20.8 MB
9. Reshaping With Pivots/1. Section Intro.mp4 23.83 MB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.mp4 19.05 MB
9. Reshaping With Pivots/11. Applying Multiple Functions.mp4 18.33 MB
9. Reshaping With Pivots/12. Skill Challenge.mp4 5.48 MB
9. Reshaping With Pivots/13. Solution.mp4 36.64 MB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.mp4 26.77 MB
9. Reshaping With Pivots/3. Pivoting Data.mp4 41.9 MB
9. Reshaping With Pivots/4. Undoing Pivots.mp4 27.89 MB
9. Reshaping With Pivots/5. What About Aggregates.mp4 34.25 MB
9. Reshaping With Pivots/6. The pivot_table().mp4 33.66 MB
9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.mp4 36.16 MB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.mp4 12.5 MB
9. Reshaping With Pivots/9. Adding Margins.mp4 24.59 MB
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