[GigaCourse.Com] Udemy - The Ultimate Pandas Bootcamp Advanced Python Data Analysis

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[GigaCourse.Com] Udemy - The Ultimate Pandas Bootcamp Advanced Python Data Analysis

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收录时间：2022-02-25
最近下载：2024-11-07

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文件列表

  • 13. Data Formats And IO/3. Reading HTML.mp4 108.8 MB
  • 11. Regex And Text Manipulation/19. Is This A Valid Email.mp4 84.0 MB
  • 11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.mp4 80.0 MB
  • 11. Regex And Text Manipulation/16. Introduction To Regular Expressions.mp4 78.7 MB
  • 13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.mp4 77.6 MB
  • 4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.mp4 76.8 MB
  • 11. Regex And Text Manipulation/23. Solution.mp4 75.9 MB
  • 15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.mp4 74.8 MB
  • 3. Series Methods And Handling/28. Transforming With update(), apply() And map().mp4 73.3 MB
  • 5. DataFrames In Depth/33. Element-wise Operations With applymap().mp4 71.8 MB
  • 5. DataFrames In Depth/4. More Approaches To Boolean Masking.mp4 71.7 MB
  • 5. DataFrames In Depth/31. Same-shape Transforms.mp4 70.2 MB
  • 4. Working With DataFrames/22. Part I Collecting The Units.mp4 70.1 MB
  • 11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().mp4 69.5 MB
  • 5. DataFrames In Depth/14. Sorting vs. Reordering.mp4 68.4 MB
  • 11. Regex And Text Manipulation/17. More Regex Concepts.mp4 68.3 MB
  • 12. Visualizing Data/9. Other Visualization Options.mp4 66.7 MB
  • 11. Regex And Text Manipulation/18. How To Approach Regex.mp4 66.6 MB
  • 12. Visualizing Data/8. Scatter Plots.mp4 66.5 MB
  • 4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4 66.0 MB
  • 12. Visualizing Data/3. The Preliminaries Of matplotlib.mp4 65.9 MB
  • 1. Introduction/7. NumPy.mp4 65.2 MB
  • 5. DataFrames In Depth/19. Identifying Dupes.mp4 63.8 MB
  • 6. Working With Multiple DataFrames/11. Solution.mp4 62.4 MB
  • 5. DataFrames In Depth/32. More Flexibility With apply().mp4 62.3 MB
  • 7. Going MultiDimensional/7. Indexing Ranges And Slices.mp4 62.0 MB
  • 7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.mp4 61.6 MB
  • 6. Working With Multiple DataFrames/5. Enforcing Unique Indices.mp4 61.2 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.mp4 60.6 MB
  • 5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().mp4 60.2 MB
  • 4. Working With DataFrames/26. Part II Merging Units With Column Names.mp4 60.1 MB
  • 6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.mp4 59.8 MB
  • 13. Data Formats And IO/4. Reading Excel.mp4 58.4 MB
  • 6. Working With Multiple DataFrames/17. Many-to-Many Joins.mp4 58.3 MB
  • 3. Series Methods And Handling/27. Filtering filter(), where(), And mask().mp4 57.7 MB
  • 12. Visualizing Data/6. Pie Plots.mp4 57.6 MB
  • 12. Visualizing Data/12. Solution.mp4 56.9 MB
  • 12. Visualizing Data/4. Line Graphs.mp4 56.8 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.mp4 55.5 MB
  • 10. Handling Date And Time/3. Parsing Dates From Text.mp4 55.4 MB
  • 3. Series Methods And Handling/2. Reading In Data With read_csv().mp4 55.4 MB
  • 6. Working With Multiple DataFrames/4. The Duplicated Index Issue.mp4 53.8 MB
  • 5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.mp4 52.9 MB
  • 4. Working With DataFrames/12. Changing The Index.mp4 52.8 MB
  • 12. Visualizing Data/5. Bar Charts.mp4 52.6 MB
  • 5. DataFrames In Depth/40. Adding Rows To DataFrames.mp4 52.3 MB
  • 4. Working With DataFrames/29. DataFrame Sorting.mp4 51.8 MB
  • 10. Handling Date And Time/19. Upsampling And Interpolation.mp4 51.8 MB
  • 5. DataFrames In Depth/38. View vs Copy.mp4 51.7 MB
  • 7. Going MultiDimensional/24. Solution.mp4 51.6 MB
  • 5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.mp4 51.4 MB
  • 3. Series Methods And Handling/32. Solution III - Z-scores.mp4 50.5 MB
  • 1. Introduction/4. Jupyter Notebooks.mp4 50.3 MB
  • 4. Working With DataFrames/14. DataFrame Extraction by Position.mp4 49.0 MB
  • 11. Regex And Text Manipulation/8. String Splitting And Concatenation.mp4 48.6 MB
  • 5. DataFrames In Depth/12. Fancy Indexing With lookup().mp4 48.5 MB
  • 6. Working With Multiple DataFrames/21. Solution.mp4 48.3 MB
  • 7. Going MultiDimensional/19. The Flipside unstack().mp4 48.2 MB
  • 4. Working With DataFrames/2. What Is A DataFrame.mp4 48.1 MB
  • 13. Data Formats And IO/10. Solution.mp4 48.0 MB
  • 12. Visualizing Data/7. Histograms.mp4 48.0 MB
  • 5. DataFrames In Depth/7. Combining Conditions.mp4 47.8 MB
  • 4. Working With DataFrames/18. Solution.mp4 47.4 MB
  • 5. DataFrames In Depth/13. Sorting By Index Or Column.mp4 47.2 MB
  • 7. Going MultiDimensional/11. Solution.mp4 47.0 MB
  • 4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.mp4 46.4 MB
  • 8. GroupBy And Aggregates/15. Fine-tuned Aggregates.mp4 46.3 MB
  • 5. DataFrames In Depth/36. Setting DataFrame Values.mp4 45.7 MB
  • 10. Handling Date And Time/21. BONUS Rolling Windows.mp4 45.6 MB
  • 4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.mp4 45.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.mp4 44.9 MB
  • 5. DataFrames In Depth/29. Solution.mp4 44.6 MB
  • 4. Working With DataFrames/28. Filtering in 2D.mp4 44.4 MB
  • 4. Working With DataFrames/34. Solution.mp4 44.3 MB
  • 5. DataFrames In Depth/25. Null Values In DataFrames.mp4 44.2 MB
  • 6. Working With Multiple DataFrames/3. Concatenating DataFrames.mp4 44.2 MB
  • 9. Reshaping With Pivots/3. Pivoting Data.mp4 43.9 MB
  • 11. Regex And Text Manipulation/15. Text Replacement.mp4 43.8 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.mp4 43.7 MB
  • 8. GroupBy And Aggregates/19. BONUS - There's Also apply().mp4 43.2 MB
  • 6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.mp4 42.6 MB
  • 4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.mp4 42.4 MB
  • 10. Handling Date And Time/2. The Python datetime Module.mp4 42.2 MB
  • 3. Series Methods And Handling/22. Series Arithmetics And fill_value().mp4 42.2 MB
  • 11. Regex And Text Manipulation/9. More Split Parameters.mp4 42.0 MB
  • 4. Working With DataFrames/24. DataFrame dropna().mp4 42.0 MB
  • 5. DataFrames In Depth/10. Solution.mp4 42.0 MB
  • 5. DataFrames In Depth/11. 2d Indexing.mp4 42.0 MB
  • 5. DataFrames In Depth/37. The SettingWithCopy Warning.mp4 41.7 MB
  • 7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.mp4 41.3 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.mp4 41.0 MB
  • 8. GroupBy And Aggregates/18. GroupBy Transformations.mp4 40.7 MB
  • 10. Handling Date And Time/18. Resampling Timeseries.mp4 40.4 MB
  • 6. Working With Multiple DataFrames/9. Concat On Different Columns.mp4 40.1 MB
  • 10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.mp4 40.0 MB
  • 6. Working With Multiple DataFrames/18. Merging By Index.mp4 40.0 MB
  • 5. DataFrames In Depth/5. Binary Operators With Booleans.mp4 39.8 MB
  • 7. Going MultiDimensional/17. More MultiIndex Methods.mp4 39.8 MB
  • 7. Going MultiDimensional/15. Removing MultiIndex Levels.mp4 39.5 MB
  • 2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.mp4 38.9 MB
  • 5. DataFrames In Depth/30. Calculating Aggregates With agg().mp4 38.9 MB
  • 11. Regex And Text Manipulation/13. Masking With String Methods.mp4 38.7 MB
  • 4. Working With DataFrames/36. Solution.mp4 38.6 MB
  • 3. Series Methods And Handling/6. Accessing And Counting NAs.mp4 38.6 MB
  • 9. Reshaping With Pivots/13. Solution.mp4 38.4 MB
  • 10. Handling Date And Time/20. What About asfreq().mp4 38.4 MB
  • 10. Handling Date And Time/15. Creating Date Ranges.mp4 38.3 MB
  • 8. GroupBy And Aggregates/16. Named Aggregations.mp4 38.3 MB
  • 5. DataFrames In Depth/39. Adding DataFrame Columns.mp4 38.2 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.mp4 38.1 MB
  • 10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.mp4 38.0 MB
  • 9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.mp4 37.9 MB
  • 4. Working With DataFrames/13. Extracting From DataFrames By Label.mp4 37.8 MB
  • 4. Working With DataFrames/27. Part III Removing Units From Values.mp4 37.4 MB
  • 4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.mp4 37.4 MB
  • 7. Going MultiDimensional/16. MultiIndex sort_index().mp4 37.3 MB
  • 6. Working With Multiple DataFrames/12. The merge() Method.mp4 37.1 MB
  • 4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().mp4 37.1 MB
  • 10. Handling Date And Time/6. Performant Datetimes With Numpy.mp4 37.0 MB
  • 4. Working With DataFrames/30. Using Series between() With DataFrames.mp4 36.7 MB
  • 7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.mp4 36.5 MB
  • 9. Reshaping With Pivots/5. What About Aggregates.mp4 35.9 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.mp4 35.8 MB
  • 3. Series Methods And Handling/13. Descriptive Statistics.mp4 35.3 MB
  • 9. Reshaping With Pivots/6. The pivot_table().mp4 35.3 MB
  • 7. Going MultiDimensional/13. Adding Another Level.mp4 35.2 MB
  • 5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.mp4 34.8 MB
  • 2. Series At A Glance/7. Index And RangeIndex.mp4 34.8 MB
  • 7. Going MultiDimensional/9. Cross Sections With xs().mp4 34.8 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.mp4 34.6 MB
  • 1. Introduction/6. Hello, Python.mp4 34.4 MB
  • 12. Visualizing Data/10. BONUS Data Ink And Chartjunk.mp4 33.9 MB
  • 6. Working With Multiple DataFrames/13. The left_on And right_on Params.mp4 33.8 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.mp4 33.7 MB
  • 5. DataFrames In Depth/43. Solution.mp4 33.5 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.mp4 33.3 MB
  • 3. Series Methods And Handling/15. mode() And value_counts().mp4 33.3 MB
  • 11. Regex And Text Manipulation/7. Strips And Whitespace.mp4 33.3 MB
  • 13. Data Formats And IO/6. BONUS Introduction To Pickling.mp4 33.3 MB
  • 15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.mp4 32.5 MB
  • 7. Going MultiDimensional/18. Reshaping With stack().mp4 32.1 MB
  • 2. Series At A Glance/20. Selecting With .get().mp4 32.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.mp4 31.9 MB
  • 5. DataFrames In Depth/20. Removing Duplicates.mp4 31.3 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.mp4 30.9 MB
  • 2. Series At A Glance/17. Boolean Masks And The .loc Indexer.mp4 30.9 MB
  • 10. Handling Date And Time/8. Our Dataset Brent Prices.mp4 30.9 MB
  • 4. Working With DataFrames/25. BONUS - dropna() With Subset.mp4 30.7 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.mp4 30.7 MB
  • 2. Series At A Glance/13. Extracting By Index Position.mp4 30.5 MB
  • 8. GroupBy And Aggregates/3. Simple Aggregations Review.mp4 30.4 MB
  • 11. Regex And Text Manipulation/3. String Methods In Python.mp4 30.2 MB
  • 6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().mp4 29.8 MB
  • 10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.mp4 29.7 MB
  • 2. Series At A Glance/21. Selection Recap.mp4 29.6 MB
  • 13. Data Formats And IO/8. The Many Other Formats.mp4 29.3 MB
  • 9. Reshaping With Pivots/4. Undoing Pivots.mp4 29.2 MB
  • 7. Going MultiDimensional/22. BONUS - What About Panels.mp4 29.2 MB
  • 7. Going MultiDimensional/5. MultiIndex From read_csv().mp4 29.0 MB
  • 8. GroupBy And Aggregates/11. Solution.mp4 28.9 MB
  • 4. Working With DataFrames/23. The rename() Method.mp4 28.9 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.mp4 28.9 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.mp4 28.8 MB
  • 4. Working With DataFrames/6. Reading In Nutrition Data.mp4 28.6 MB
  • 6. Working With Multiple DataFrames/14. Inner vs Outer Joins.mp4 28.4 MB
  • 6. Working With Multiple DataFrames/7. Column Axis Concatenation.mp4 28.4 MB
  • 2. Series At A Glance/14. Accessing Elements By Label.mp4 28.4 MB
  • 7. Going MultiDimensional/3. Index And RangeIndex.mp4 28.2 MB
  • 9. Reshaping With Pivots/2. New Data New York City SAT Scores.mp4 28.1 MB
  • 10. Handling Date And Time/11. Indexing Dates.mp4 27.9 MB
  • 8. GroupBy And Aggregates/14. MultiIndex Grouping.mp4 27.8 MB
  • 1. Introduction/5. Cloud vs Local.mp4 27.8 MB
  • 5. DataFrames In Depth/35. Solution.mp4 27.8 MB
  • 7. Going MultiDimensional/1. Section Intro.mp4 27.7 MB
  • 4. Working With DataFrames/15. Single Value Access With .at And .iat.mp4 27.6 MB
  • 8. GroupBy And Aggregates/17. The filter() Method.mp4 27.4 MB
  • 5. DataFrames In Depth/18. Solution.mp4 27.0 MB
  • 11. Regex And Text Manipulation/6. Finding Characters And Words.mp4 27.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.mp4 26.6 MB
  • 4. Working With DataFrames/20. The astype() Method.mp4 26.4 MB
  • 4. Working With DataFrames/16. BONUS - The get_loc() Method.mp4 26.3 MB
  • 9. Reshaping With Pivots/9. Adding Margins.mp4 25.8 MB
  • 10. Handling Date And Time/9. Date Parsing And DatetimeIndex.mp4 25.7 MB
  • 8. GroupBy And Aggregates/21. Solution.mp4 25.7 MB
  • 8. GroupBy And Aggregates/4. Conditional Aggregates.mp4 25.7 MB
  • 7. Going MultiDimensional/14. Shuffling Levels.mp4 25.5 MB
  • 11. Regex And Text Manipulation/12. Slicing Substrings.mp4 25.4 MB
  • 10. Handling Date And Time/7. The Pandas Timestamp.mp4 25.2 MB
  • 10. Handling Date And Time/4. Even Better dateutil.mp4 25.0 MB
  • 9. Reshaping With Pivots/1. Section Intro.mp4 25.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.mp4 24.9 MB
  • 8. GroupBy And Aggregates/13. Handpicking Subgroups.mp4 24.8 MB
  • 11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.mp4 24.7 MB
  • 2. Series At A Glance/23. Solution.mp4 24.5 MB
  • 5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.mp4 24.5 MB
  • 4. Working With DataFrames/11. DataFrame Axes.mp4 24.4 MB
  • 3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().mp4 24.4 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.mp4 24.3 MB
  • 2. Series At A Glance/12. The head() And tail() Methods.mp4 24.1 MB
  • 13. Data Formats And IO/7. Pickles In Pandas.mp4 24.0 MB
  • 10. Handling Date And Time/23. Solution.mp4 24.0 MB
  • 2. Series At A Glance/10. Solution.mp4 24.0 MB
  • 6. Working With Multiple DataFrames/19. The join() Method.mp4 24.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.mp4 23.8 MB
  • 4. Working With DataFrames/8. The sample() Method.mp4 23.7 MB
  • 8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.mp4 23.6 MB
  • 4. Working With DataFrames/3. Creating A DataFrame.mp4 23.5 MB
  • 10. Handling Date And Time/5. From Datetime To String.mp4 23.5 MB
  • 10. Handling Date And Time/1. Section Intro.mp4 23.4 MB
  • 7. Going MultiDimensional/2. Introducing New Data.mp4 23.2 MB
  • 3. Series Methods And Handling/16. idxmax() And idxmin().mp4 23.1 MB
  • 11. Regex And Text Manipulation/11. Solution.mp4 23.0 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.mp4 22.9 MB
  • 5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.mp4 22.8 MB
  • 8. GroupBy And Aggregates/6. The groupby() Method.mp4 22.6 MB
  • 3. Series Methods And Handling/12. Dropping And Filling NAs.mp4 22.6 MB
  • 3. Series Methods And Handling/7. BONUS Another Approach.mp4 22.4 MB
  • 5. DataFrames In Depth/1. Section Intro.mp4 22.2 MB
  • 8. GroupBy And Aggregates/12. Iterating Through Groups.mp4 22.1 MB
  • 8. GroupBy And Aggregates/9. BONUS - Series groupby().mp4 21.8 MB
  • 1. Introduction/3. Anaconda.mp4 21.7 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.mp4 21.6 MB
  • 8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.mp4 21.5 MB
  • 3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.mp4 21.5 MB
  • 2. Series At A Glance/4. What’s In The Data.mp4 21.4 MB
  • 6. Working With Multiple DataFrames/15. Left vs Right Joins.mp4 21.3 MB
  • 7. Going MultiDimensional/4. Creating A MultiIndex.mp4 21.1 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.mp4 21.0 MB
  • 5. DataFrames In Depth/8. Conditions As Variables.mp4 20.9 MB
  • 8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.mp4 20.8 MB
  • 5. DataFrames In Depth/21. Removing DataFrame Rows.mp4 20.7 MB
  • 13. Data Formats And IO/2. Reading JSON.mp4 20.7 MB
  • 3. Series Methods And Handling/17. Sorting With sort_values().mp4 20.6 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.mp4 20.2 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.mp4 20.1 MB
  • 2. Series At A Glance/8. Series And Index Names.mp4 20.1 MB
  • 5. DataFrames In Depth/23. BONUS - Another Way pop().mp4 20.0 MB
  • 9. Reshaping With Pivots/10. MultiIndex Pivot Tables.mp4 20.0 MB
  • 4. Working With DataFrames/5. The info() Method.mp4 20.0 MB
  • 4. Working With DataFrames/19. More Cleanup Going Numeric.mp4 19.5 MB
  • 7. Going MultiDimensional/21. An Easier Way transpose().mp4 19.5 MB
  • 11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.mp4 19.3 MB
  • 9. Reshaping With Pivots/11. Applying Multiple Functions.mp4 19.2 MB
  • 11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().mp4 19.2 MB
  • 5. DataFrames In Depth/2. Introducing A New Dataset.mp4 19.2 MB
  • 3. Series Methods And Handling/24. Cumulative Operations.mp4 18.8 MB
  • 1. Introduction/2. Pandas Is Not Single.mp4 18.7 MB
  • 3. Series Methods And Handling/4. Unique Values And Series Monotonicity.mp4 18.7 MB
  • 10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.mp4 18.5 MB
  • 3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.mp4 18.2 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.mp4 18.0 MB
  • 15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.mp4 18.0 MB
  • 10. Handling Date And Time/13. Solution.mp4 17.9 MB
  • 8. GroupBy And Aggregates/1. Section Intro.mp4 17.9 MB
  • 5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.mp4 17.9 MB
  • 7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.mp4 17.8 MB
  • 11. Regex And Text Manipulation/1. Section Intro.mp4 17.5 MB
  • 2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.mp4 17.3 MB
  • 5. DataFrames In Depth/22. BONUS - Removing Columns.mp4 17.0 MB
  • 3. Series Methods And Handling/26. Series Iteration.mp4 16.9 MB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.mp4 16.7 MB
  • 3. Series Methods And Handling/19. Sorting With sort_index().mp4 16.0 MB
  • 8. GroupBy And Aggregates/2. New Data Game Sales.mp4 15.6 MB
  • 3. Series Methods And Handling/30. Solution I - Reading Data.mp4 15.3 MB
  • 6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().mp4 15.2 MB
  • 1. Introduction/1. Course Structure.mp4 14.7 MB
  • 11. Regex And Text Manipulation/5. Case Operations.mp4 14.7 MB
  • 3. Series Methods And Handling/11. Solution.mp4 14.1 MB
  • 2. Series At A Glance/16. Using Dot Notation.mp4 13.9 MB
  • 12. Visualizing Data/2. The Art Of Data Visualization.mp4 13.6 MB
  • 5. DataFrames In Depth/15. BONUS - Another Way.mp4 13.6 MB
  • 3. Series Methods And Handling/1. Section Intro.mp4 13.6 MB
  • 3. Series Methods And Handling/25. Pairwise Differences With diff().mp4 13.4 MB
  • 2. Series At A Glance/2. What Is A Series.mp4 13.1 MB
  • 9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.mp4 13.1 MB
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  • 3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.mp4 12.2 MB
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  • 11. Regex And Text Manipulation/19. Is This A Valid Email.srt 19.1 kB
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  • 1. Introduction/4. Jupyter Notebooks.srt 14.3 kB
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  • 14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.srt 11.1 kB
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  • 14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.srt 5.8 kB
  • 10. Handling Date And Time/8. Our Dataset Brent Prices.srt 5.8 kB
  • 3. Series Methods And Handling/17. Sorting With sort_values().srt 5.8 kB
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  • 8. GroupBy And Aggregates/6. The groupby() Method.srt 5.7 kB
  • 4. Working With DataFrames/3. Creating A DataFrame.srt 5.6 kB
  • 3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().srt 5.6 kB
  • 9. Reshaping With Pivots/2. New Data New York City SAT Scores.srt 5.5 kB
  • 8. GroupBy And Aggregates/13. Handpicking Subgroups.srt 5.5 kB
  • 6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().srt 5.4 kB
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  • 4. Working With DataFrames/5. The info() Method.srt 5.4 kB
  • 6. Working With Multiple DataFrames/7. Column Axis Concatenation.srt 5.4 kB
  • 5. DataFrames In Depth/23. BONUS - Another Way pop().srt 5.4 kB
  • 1. Introduction/6. Hello, Python.srt 5.4 kB
  • 10. Handling Date And Time/4. Even Better dateutil.srt 5.3 kB
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  • 6. Working With Multiple DataFrames/13. The left_on And right_on Params.srt 5.3 kB
  • 3. Series Methods And Handling/12. Dropping And Filling NAs.srt 5.3 kB
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  • 5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.srt 5.2 kB
  • 14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.srt 5.2 kB
  • 4. Working With DataFrames/11. DataFrame Axes.srt 5.1 kB
  • 11. Regex And Text Manipulation/11. Solution.srt 5.0 kB
  • 7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.srt 5.0 kB
  • 7. Going MultiDimensional/5. MultiIndex From read_csv().srt 4.9 kB
  • 4. Working With DataFrames/8. The sample() Method.srt 4.9 kB
  • 13. Data Formats And IO/8. The Many Other Formats.srt 4.9 kB
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  • 2. Series At A Glance/10. Solution.srt 4.9 kB
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  • 5. DataFrames In Depth/2. Introducing A New Dataset.srt 4.6 kB
  • 2. Series At A Glance/16. Using Dot Notation.srt 4.6 kB
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  • 14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.srt 4.5 kB
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  • 5. DataFrames In Depth/18. Solution.srt 4.5 kB
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  • 11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().srt 4.3 kB
  • 3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.srt 4.2 kB
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  • 3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.srt 3.9 kB
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  • 5. DataFrames In Depth/22. BONUS - Removing Columns.srt 3.6 kB
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  • 14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.srt 3.0 kB
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  • 5. DataFrames In Depth/15. BONUS - Another Way.srt 2.7 kB
  • 5. DataFrames In Depth/34. Skill Challenge.srt 2.7 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 2.6 kB
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  • 3. Series Methods And Handling/21. Solution.srt 2.5 kB
  • 1. Introduction/2. Pandas Is Not Single.srt 2.5 kB
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  • 4. Working With DataFrames/1. Section Intro.srt 2.3 kB
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  • 1. Introduction/1. Course Structure.srt 1.8 kB
  • 10. Handling Date And Time/22. Skill Challenge.srt 1.8 kB
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  • 5. DataFrames In Depth/17. Skill Challenge.srt 1.5 kB
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  • 6. Working With Multiple DataFrames/20. Skill Challenge.srt 1.4 kB
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  • 13. Data Formats And IO/1. Section Intro.srt 1.1 kB
  • Sources/ivies.csv 548 Bytes
  • Sources/folks.json 244 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 12. Visualizing Data/[CourseClub.Me].url 122 Bytes
  • 5. DataFrames In Depth/[CourseClub.Me].url 122 Bytes
  • [CourseClub.Me].url 122 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 12. Visualizing Data/[GigaCourse.Com].url 49 Bytes
  • 5. DataFrames In Depth/[GigaCourse.Com].url 49 Bytes
  • [GigaCourse.Com].url 49 Bytes

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