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

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文件列表

13. Data Formats And IO/3. Reading HTML.mp4 104MB
11. Regex And Text Manipulation/19. Is This A Valid Email.mp4 80MB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.mp4 76MB
11. Regex And Text Manipulation/16. Introduction To Regular Expressions.mp4 75MB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.mp4 74MB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.mp4 73MB
11. Regex And Text Manipulation/23. Solution.mp4 72MB
15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.mp4 71MB
3. Series Methods And Handling/28. Transforming With update(), apply() And map().mp4 70MB
5. DataFrames In Depth/33. Element-wise Operations With applymap().mp4 69MB
5. DataFrames In Depth/4. More Approaches To Boolean Masking.mp4 68MB
5. DataFrames In Depth/31. Same-shape Transforms.mp4 67MB
4. Working With DataFrames/22. Part I Collecting The Units.mp4 67MB
11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().mp4 66MB
5. DataFrames In Depth/14. Sorting vs. Reordering.mp4 65MB
11. Regex And Text Manipulation/17. More Regex Concepts.mp4 65MB
12. Visualizing Data/9. Other Visualization Options.mp4 64MB
11. Regex And Text Manipulation/18. How To Approach Regex.mp4 64MB
12. Visualizing Data/8. Scatter Plots.mp4 63MB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4 63MB
12. Visualizing Data/3. The Preliminaries Of matplotlib.mp4 63MB
1. Introduction/7. NumPy.mp4 62MB
5. DataFrames In Depth/19. Identifying Dupes.mp4 61MB
6. Working With Multiple DataFrames/11. Solution.mp4 59MB
5. DataFrames In Depth/32. More Flexibility With apply().mp4 59MB
7. Going MultiDimensional/7. Indexing Ranges And Slices.mp4 59MB
7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.mp4 59MB
6. Working With Multiple DataFrames/5. Enforcing Unique Indices.mp4 58MB
14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.mp4 58MB
5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().mp4 57MB
4. Working With DataFrames/26. Part II Merging Units With Column Names.mp4 57MB
6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.mp4 57MB
13. Data Formats And IO/4. Reading Excel.mp4 56MB
6. Working With Multiple DataFrames/17. Many-to-Many Joins.mp4 56MB
3. Series Methods And Handling/27. Filtering filter(), where(), And mask().mp4 55MB
12. Visualizing Data/6. Pie Plots.mp4 55MB
12. Visualizing Data/12. Solution.mp4 54MB
12. Visualizing Data/4. Line Graphs.mp4 54MB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.mp4 53MB
10. Handling Date And Time/3. Parsing Dates From Text.mp4 53MB
3. Series Methods And Handling/2. Reading In Data With read_csv().mp4 53MB
6. Working With Multiple DataFrames/4. The Duplicated Index Issue.mp4 51MB
5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.mp4 50MB
4. Working With DataFrames/12. Changing The Index.mp4 50MB
12. Visualizing Data/5. Bar Charts.mp4 50MB
5. DataFrames In Depth/40. Adding Rows To DataFrames.mp4 50MB
4. Working With DataFrames/29. DataFrame Sorting.mp4 49MB
10. Handling Date And Time/19. Upsampling And Interpolation.mp4 49MB
5. DataFrames In Depth/38. View vs Copy.mp4 49MB
7. Going MultiDimensional/24. Solution.mp4 49MB
5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.mp4 49MB
3. Series Methods And Handling/32. Solution III - Z-scores.mp4 48MB
1. Introduction/4. Jupyter Notebooks.mp4 48MB
4. Working With DataFrames/14. DataFrame Extraction by Position.mp4 47MB
11. Regex And Text Manipulation/8. String Splitting And Concatenation.mp4 46MB
5. DataFrames In Depth/12. Fancy Indexing With lookup().mp4 46MB
6. Working With Multiple DataFrames/21. Solution.mp4 46MB
7. Going MultiDimensional/19. The Flipside unstack().mp4 46MB
4. Working With DataFrames/2. What Is A DataFrame.mp4 46MB
13. Data Formats And IO/10. Solution.mp4 46MB
12. Visualizing Data/7. Histograms.mp4 46MB
5. DataFrames In Depth/7. Combining Conditions.mp4 46MB
4. Working With DataFrames/18. Solution.mp4 45MB
5. DataFrames In Depth/13. Sorting By Index Or Column.mp4 45MB
7. Going MultiDimensional/11. Solution.mp4 45MB
4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.mp4 44MB
8. GroupBy And Aggregates/15. Fine-tuned Aggregates.mp4 44MB
5. DataFrames In Depth/36. Setting DataFrame Values.mp4 44MB
10. Handling Date And Time/21. BONUS Rolling Windows.mp4 43MB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.mp4 43MB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.mp4 43MB
5. DataFrames In Depth/29. Solution.mp4 42MB
4. Working With DataFrames/28. Filtering in 2D.mp4 42MB
4. Working With DataFrames/34. Solution.mp4 42MB
5. DataFrames In Depth/25. Null Values In DataFrames.mp4 42MB
6. Working With Multiple DataFrames/3. Concatenating DataFrames.mp4 42MB
9. Reshaping With Pivots/3. Pivoting Data.mp4 42MB
11. Regex And Text Manipulation/15. Text Replacement.mp4 42MB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.mp4 42MB
8. GroupBy And Aggregates/19. BONUS - There's Also apply().mp4 41MB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.mp4 41MB
4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.mp4 40MB
10. Handling Date And Time/2. The Python datetime Module.mp4 40MB
3. Series Methods And Handling/22. Series Arithmetics And fill_value().mp4 40MB
11. Regex And Text Manipulation/9. More Split Parameters.mp4 40MB
4. Working With DataFrames/24. DataFrame dropna().mp4 40MB
5. DataFrames In Depth/10. Solution.mp4 40MB
5. DataFrames In Depth/11. 2d Indexing.mp4 40MB
5. DataFrames In Depth/37. The SettingWithCopy Warning.mp4 40MB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.mp4 39MB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.mp4 39MB
8. GroupBy And Aggregates/18. GroupBy Transformations.mp4 39MB
10. Handling Date And Time/18. Resampling Timeseries.mp4 39MB
6. Working With Multiple DataFrames/9. Concat On Different Columns.mp4 38MB
10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.mp4 38MB
6. Working With Multiple DataFrames/18. Merging By Index.mp4 38MB
5. DataFrames In Depth/5. Binary Operators With Booleans.mp4 38MB
7. Going MultiDimensional/17. More MultiIndex Methods.mp4 38MB
7. Going MultiDimensional/15. Removing MultiIndex Levels.mp4 38MB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.mp4 37MB
5. DataFrames In Depth/30. Calculating Aggregates With agg().mp4 37MB
11. Regex And Text Manipulation/13. Masking With String Methods.mp4 37MB
4. Working With DataFrames/36. Solution.mp4 37MB
3. Series Methods And Handling/6. Accessing And Counting NAs.mp4 37MB
9. Reshaping With Pivots/13. Solution.mp4 37MB
10. Handling Date And Time/20. What About asfreq().mp4 37MB
10. Handling Date And Time/15. Creating Date Ranges.mp4 37MB
8. GroupBy And Aggregates/16. Named Aggregations.mp4 36MB
5. DataFrames In Depth/39. Adding DataFrame Columns.mp4 36MB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.mp4 36MB
10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.mp4 36MB
9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.mp4 36MB
4. Working With DataFrames/13. Extracting From DataFrames By Label.mp4 36MB
4. Working With DataFrames/27. Part III Removing Units From Values.mp4 36MB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.mp4 36MB
7. Going MultiDimensional/16. MultiIndex sort_index().mp4 36MB
6. Working With Multiple DataFrames/12. The merge() Method.mp4 35MB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().mp4 35MB
10. Handling Date And Time/6. Performant Datetimes With Numpy.mp4 35MB
4. Working With DataFrames/30. Using Series between() With DataFrames.mp4 35MB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.mp4 35MB
9. Reshaping With Pivots/5. What About Aggregates.mp4 34MB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.mp4 34MB
3. Series Methods And Handling/13. Descriptive Statistics.mp4 34MB
9. Reshaping With Pivots/6. The pivot_table().mp4 34MB
7. Going MultiDimensional/13. Adding Another Level.mp4 34MB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.mp4 33MB
2. Series At A Glance/7. Index And RangeIndex.mp4 33MB
7. Going MultiDimensional/9. Cross Sections With xs().mp4 33MB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.mp4 33MB
1. Introduction/6. Hello, Python.mp4 33MB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.mp4 32MB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.mp4 32MB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.mp4 32MB
5. DataFrames In Depth/43. Solution.mp4 32MB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.mp4 32MB
3. Series Methods And Handling/15. mode() And value_counts().mp4 32MB
11. Regex And Text Manipulation/7. Strips And Whitespace.mp4 32MB
13. Data Formats And IO/6. BONUS Introduction To Pickling.mp4 32MB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.mp4 31MB
7. Going MultiDimensional/18. Reshaping With stack().mp4 31MB
2. Series At A Glance/20. Selecting With .get().mp4 31MB
14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.mp4 30MB
5. DataFrames In Depth/20. Removing Duplicates.mp4 30MB
14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.mp4 29MB
2. Series At A Glance/17. Boolean Masks And The .loc Indexer.mp4 29MB
10. Handling Date And Time/8. Our Dataset Brent Prices.mp4 29MB
4. Working With DataFrames/25. BONUS - dropna() With Subset.mp4 29MB
14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.mp4 29MB
2. Series At A Glance/13. Extracting By Index Position.mp4 29MB
8. GroupBy And Aggregates/3. Simple Aggregations Review.mp4 29MB
11. Regex And Text Manipulation/3. String Methods In Python.mp4 29MB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().mp4 28MB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.mp4 28MB
2. Series At A Glance/21. Selection Recap.mp4 28MB
13. Data Formats And IO/8. The Many Other Formats.mp4 28MB
9. Reshaping With Pivots/4. Undoing Pivots.mp4 28MB
7. Going MultiDimensional/22. BONUS - What About Panels.mp4 28MB
7. Going MultiDimensional/5. MultiIndex From read_csv().mp4 28MB
8. GroupBy And Aggregates/11. Solution.mp4 28MB
4. Working With DataFrames/23. The rename() Method.mp4 28MB
14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.mp4 28MB
14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.mp4 27MB
4. Working With DataFrames/6. Reading In Nutrition Data.mp4 27MB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.mp4 27MB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.mp4 27MB
2. Series At A Glance/14. Accessing Elements By Label.mp4 27MB
7. Going MultiDimensional/3. Index And RangeIndex.mp4 27MB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.mp4 27MB
10. Handling Date And Time/11. Indexing Dates.mp4 27MB
8. GroupBy And Aggregates/14. MultiIndex Grouping.mp4 27MB
1. Introduction/5. Cloud vs Local.mp4 27MB
5. DataFrames In Depth/35. Solution.mp4 26MB
7. Going MultiDimensional/1. Section Intro.mp4 26MB
4. Working With DataFrames/15. Single Value Access With .at And .iat.mp4 26MB
8. GroupBy And Aggregates/17. The filter() Method.mp4 26MB
5. DataFrames In Depth/18. Solution.mp4 26MB
11. Regex And Text Manipulation/6. Finding Characters And Words.mp4 26MB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.mp4 25MB
4. Working With DataFrames/20. The astype() Method.mp4 25MB
4. Working With DataFrames/16. BONUS - The get_loc() Method.mp4 25MB
9. Reshaping With Pivots/9. Adding Margins.mp4 25MB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.mp4 25MB
8. GroupBy And Aggregates/21. Solution.mp4 25MB
8. GroupBy And Aggregates/4. Conditional Aggregates.mp4 25MB
7. Going MultiDimensional/14. Shuffling Levels.mp4 24MB
11. Regex And Text Manipulation/12. Slicing Substrings.mp4 24MB
10. Handling Date And Time/7. The Pandas Timestamp.mp4 24MB
10. Handling Date And Time/4. Even Better dateutil.mp4 24MB
9. Reshaping With Pivots/1. Section Intro.mp4 24MB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.mp4 24MB
8. GroupBy And Aggregates/13. Handpicking Subgroups.mp4 24MB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.mp4 24MB
2. Series At A Glance/23. Solution.mp4 23MB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.mp4 23MB
4. Working With DataFrames/11. DataFrame Axes.mp4 23MB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().mp4 23MB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.mp4 23MB
2. Series At A Glance/12. The head() And tail() Methods.mp4 23MB
13. Data Formats And IO/7. Pickles In Pandas.mp4 23MB
10. Handling Date And Time/23. Solution.mp4 23MB
2. Series At A Glance/10. Solution.mp4 23MB
6. Working With Multiple DataFrames/19. The join() Method.mp4 23MB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.mp4 23MB
4. Working With DataFrames/8. The sample() Method.mp4 23MB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.mp4 23MB
4. Working With DataFrames/3. Creating A DataFrame.mp4 22MB
10. Handling Date And Time/5. From Datetime To String.mp4 22MB
10. Handling Date And Time/1. Section Intro.mp4 22MB
7. Going MultiDimensional/2. Introducing New Data.mp4 22MB
3. Series Methods And Handling/16. idxmax() And idxmin().mp4 22MB
11. Regex And Text Manipulation/11. Solution.mp4 22MB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.mp4 22MB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.mp4 22MB
8. GroupBy And Aggregates/6. The groupby() Method.mp4 22MB
3. Series Methods And Handling/12. Dropping And Filling NAs.mp4 22MB
3. Series Methods And Handling/7. BONUS Another Approach.mp4 21MB
5. DataFrames In Depth/1. Section Intro.mp4 21MB
8. GroupBy And Aggregates/12. Iterating Through Groups.mp4 21MB
8. GroupBy And Aggregates/9. BONUS - Series groupby().mp4 21MB
1. Introduction/3. Anaconda.mp4 21MB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.mp4 21MB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.mp4 20MB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.mp4 20MB
2. Series At A Glance/4. What’s In The Data.mp4 20MB
6. Working With Multiple DataFrames/15. Left vs Right Joins.mp4 20MB
7. Going MultiDimensional/4. Creating A MultiIndex.mp4 20MB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.mp4 20MB
5. DataFrames In Depth/8. Conditions As Variables.mp4 20MB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.mp4 20MB
5. DataFrames In Depth/21. Removing DataFrame Rows.mp4 20MB
13. Data Formats And IO/2. Reading JSON.mp4 20MB
3. Series Methods And Handling/17. Sorting With sort_values().mp4 20MB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.mp4 19MB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.mp4 19MB
2. Series At A Glance/8. Series And Index Names.mp4 19MB
5. DataFrames In Depth/23. BONUS - Another Way pop().mp4 19MB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.mp4 19MB
4. Working With DataFrames/5. The info() Method.mp4 19MB
4. Working With DataFrames/19. More Cleanup Going Numeric.mp4 19MB
7. Going MultiDimensional/21. An Easier Way transpose().mp4 19MB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.mp4 18MB
9. Reshaping With Pivots/11. Applying Multiple Functions.mp4 18MB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().mp4 18MB
5. DataFrames In Depth/2. Introducing A New Dataset.mp4 18MB
3. Series Methods And Handling/24. Cumulative Operations.mp4 18MB
1. Introduction/2. Pandas Is Not Single.mp4 18MB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.mp4 18MB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.mp4 18MB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.mp4 17MB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.mp4 17MB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.mp4 17MB
10. Handling Date And Time/13. Solution.mp4 17MB
8. GroupBy And Aggregates/1. Section Intro.mp4 17MB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.mp4 17MB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.mp4 17MB
11. Regex And Text Manipulation/1. Section Intro.mp4 17MB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.mp4 16MB
5. DataFrames In Depth/22. BONUS - Removing Columns.mp4 16MB
3. Series Methods And Handling/26. Series Iteration.mp4 16MB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.mp4 16MB
3. Series Methods And Handling/19. Sorting With sort_index().mp4 15MB
8. GroupBy And Aggregates/2. New Data Game Sales.mp4 15MB
3. Series Methods And Handling/30. Solution I - Reading Data.mp4 15MB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().mp4 14MB
1. Introduction/1. Course Structure.mp4 14MB
11. Regex And Text Manipulation/5. Case Operations.mp4 14MB
3. Series Methods And Handling/11. Solution.mp4 13MB
2. Series At A Glance/16. Using Dot Notation.mp4 13MB
12. Visualizing Data/2. The Art Of Data Visualization.mp4 13MB
5. DataFrames In Depth/15. BONUS - Another Way.mp4 13MB
3. Series Methods And Handling/1. Section Intro.mp4 13MB
3. Series Methods And Handling/25. Pairwise Differences With diff().mp4 13MB
2. Series At A Glance/2. What Is A Series.mp4 13MB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.mp4 13MB
3. Series Methods And Handling/18. nlargest() And nsmallest().mp4 12MB
13. Data Formats And IO/9. Skill Challenge.mp4 12MB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.mp4 12MB
2. Series At A Glance/18. Extracting By Position With .iloc.mp4 12MB
2. Series At A Glance/11. Another Solution.mp4 11MB
3. Series Methods And Handling/8. The Other Side notnull() And notna().mp4 11MB
4. Working With DataFrames/1. Section Intro.mp4 11MB
12. Visualizing Data/1. Section Intro.mp4 10MB
3. Series Methods And Handling/29. Skill Challenge.mp4 10MB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.mp4 10MB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.mp4 10MB
3. Series Methods And Handling/21. Solution.mp4 10MB
3. Series Methods And Handling/14. The describe() Method.mp4 10MB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.mp4 9MB
5. DataFrames In Depth/34. Skill Challenge.mp4 9MB
2. Series At A Glance/3. Parameters vs Arguments.mp4 8MB
7. Going MultiDimensional/23. Skill Challenge.mp4 8MB
6. Working With Multiple DataFrames/1. Section Intro.mp4 8MB
2. Series At A Glance/9. Skill Challenge.mp4 8MB
12. Visualizing Data/11. Skill Challenge.mp4 8MB
2. Series At A Glance/1. Section Intro.mp4 7MB
4. Working With DataFrames/35. Another Skill Challenge.mp4 7MB
2. Series At A Glance/22. Skill Challenge.mp4 6MB
2. Series At A Glance/5. The .dtype Attribute.mp4 6MB
3. Series Methods And Handling/5. The count() Method.mp4 6MB
6. Working With Multiple DataFrames/10. Skill Challenge.mp4 6MB
9. Reshaping With Pivots/12. Skill Challenge.mp4 5MB
11. Regex And Text Manipulation/22. Skill Challenge.mp4 5MB
5. DataFrames In Depth/28. Skill Challenge.mp4 5MB
13. Data Formats And IO/1. Section Intro.mp4 5MB
5. DataFrames In Depth/42. Skill Challenge.mp4 5MB
10. Handling Date And Time/22. Skill Challenge.mp4 5MB
5. DataFrames In Depth/17. Skill Challenge.mp4 4MB
Sources/nutrition.csv 4MB
4. Working With DataFrames/33. Skill Challenge.mp4 4MB
4. Working With DataFrames/17. Skill Challenge.mp4 4MB
8. GroupBy And Aggregates/20. Skill Challenge.mp4 4MB
3. Series Methods And Handling/10. Skill Challenge.mp4 4MB
5. DataFrames In Depth/9. Skill Challenge.mp4 4MB
6. Working With Multiple DataFrames/20. Skill Challenge.mp4 4MB
10. Handling Date And Time/12. Skill Challenge.mp4 4MB
7. Going MultiDimensional/10. Skill Challenge.mp4 4MB
11. Regex And Text Manipulation/10. Skill Challenge.mp4 3MB
8. GroupBy And Aggregates/10. Skill Challenge.mp4 3MB
3. Series Methods And Handling/20. Skill Challenge.mp4 3MB
Sources/Visualizing_Data.ipynb.zip 501KB
Sources/tech_giants (1).csv 467KB
Sources/tech_giants.csv 467KB
Sources/MemoryLayout.pdf 246KB
Sources/games_sales (1).csv 237KB
Sources/games_sales (2).csv 237KB
Sources/games_sales.csv 237KB
Sources/Vectorization.pdf 115KB
Sources/SplitApplyCombine.pdf 115KB
Sources/SelectionRecap.pdf 111KB
Sources/WhatIsDtype.pdf 111KB
Sources/MultiIndexInternals.pdf 111KB
Sources/Working_With_DataFrames.zip 106KB
Sources/Handling_Time_And_Date.ipynb.zip 105KB
Sources/BrentOilPrices (1).csv 79KB
Sources/BrentOilPrices.csv 79KB
Sources/WhatIsASeries.pdf 75KB
Sources/scores (1).csv 75KB
Sources/scores.csv 75KB
Sources/SelectionTerminology.pdf 67KB
Sources/3KeyConcepts.pdf 63KB
Sources/ConcatVsMerge.pdf 63KB
Sources/WhatIsCSV.pdf 63KB
Sources/TwosComplement.pdf 60KB
Sources/DataFrames_In_Depth.zip 59KB
Sources/DropnaWithSubset.pdf 59KB
Sources/2017BostonMarathonTop1000 (1).csv 58KB
Sources/2017BostonMarathonTop1000.csv 58KB
Sources/DroppingAndFillingNA.pdf 57KB
Sources/ViewVsCopy.pdf 53KB
Sources/Lookup.pdf 50KB
Sources/AppendVsConcat.pdf 49KB
Sources/Transforms.pdf 47KB
Sources/SortValueOrIndex.pdf 44KB
Sources/BooleanMasks.pdf 44KB
Sources/InnerVsOuter.pdf 44KB
Sources/SeriesAtGlance.pdf 43KB
Sources/Diff.pdf 42KB
Sources/SizeAndShape.pdf 42KB
Sources/SeriesAccounting.pdf 42KB
Sources/Going_MultiDimensional.zip 42KB
Sources/SeqVsVectorizedOperations.pdf 41KB
Sources/LeftVsRight.pdf 41KB
Sources/IdxminIdxmax.pdf 40KB
Sources/Variance.pdf 38KB
Sources/RangeVSInt64Index.pdf 38KB
Sources/BoolsAsInts.pdf 37KB
Sources/ValueCounts.pdf 36KB
Sources/JoinCardinalities.pdf 35KB
Sources/soccer.csv 34KB
Sources/OurProcess.pdf 33KB
Sources/Median.pdf 32KB
Sources/MethodsVAttribtues.pdf 32KB
Sources/Series_Methods_And_Handling.zip 32KB
Sources/AtAndIat.pdf 31KB
Sources/Regex_And_Text_Manipulation.ipynb.zip 30KB
Sources/IndexingWithCallables.pdf 29KB
Sources/MoreWaysToBuildDataframes.pdf 29KB
Sources/Comparators.pdf 29KB
Sources/Working_With_Multiple_DataFrames.zip 27KB
Sources/ViewVsCopyHowDoWeTell.pdf 27KB
Sources/Appendix_A_Rapid_Fire_Python_Fundamentals.ipynb.zip 26KB
Sources/BinaryOperators.pdf 24KB
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Sources/Data_Formats_And_I_O.ipynb.zip 24KB
Sources/mid_career_salaries.csv 23KB
Sources/GroupBy_And_Aggregates.ipynb.zip 22KB
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11. Regex And Text Manipulation/19. Is This A Valid Email.srt 19KB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.srt 19KB
Sources/ArgsVParams.pdf 18KB
5. DataFrames In Depth/31. Same-shape Transforms.srt 18KB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.srt 17KB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.srt 17KB
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13. Data Formats And IO/3. Reading HTML.srt 16KB
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1. Introduction/4. Jupyter Notebooks.srt 14KB
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11. Regex And Text Manipulation/17. More Regex Concepts.srt 12KB
12. Visualizing Data/8. Scatter Plots.srt 12KB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.srt 12KB
5. DataFrames In Depth/5. Binary Operators With Booleans.srt 12KB
4. Working With DataFrames/2. What Is A DataFrame.srt 12KB
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12. Visualizing Data/5. Bar Charts.srt 12KB
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5. DataFrames In Depth/4. More Approaches To Boolean Masking.srt 12KB
12. Visualizing Data/7. Histograms.srt 11KB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.srt 11KB
5. DataFrames In Depth/11. 2d Indexing.srt 11KB
5. DataFrames In Depth/30. Calculating Aggregates With agg().srt 11KB
5. DataFrames In Depth/40. Adding Rows To DataFrames.srt 11KB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.srt 11KB
10. Handling Date And Time/19. Upsampling And Interpolation.srt 11KB
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10. Handling Date And Time/20. What About asfreq().srt 11KB
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11. Regex And Text Manipulation/8. String Splitting And Concatenation.srt 11KB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.srt 11KB
3. Series Methods And Handling/6. Accessing And Counting NAs.srt 11KB
5. DataFrames In Depth/38. View vs Copy.srt 11KB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.srt 11KB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.srt 11KB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.srt 10KB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.srt 10KB
4. Working With DataFrames/28. Filtering in 2D.srt 10KB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.srt 10KB
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10. Handling Date And Time/6. Performant Datetimes With Numpy.srt 10KB
3. Series Methods And Handling/2. Reading In Data With read_csv().srt 10KB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.srt 10KB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.srt 10KB
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7. Going MultiDimensional/24. Solution.srt 10KB
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13. Data Formats And IO/4. Reading Excel.srt 10KB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.srt 10KB
11. Regex And Text Manipulation/9. More Split Parameters.srt 10KB
12. Visualizing Data/12. Solution.srt 10KB
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14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.srt 9KB
5. DataFrames In Depth/37. The SettingWithCopy Warning.srt 9KB
4. Working With DataFrames/23. The rename() Method.srt 9KB
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13. Data Formats And IO/10. Solution.srt 9KB
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6. Working With Multiple DataFrames/4. The Duplicated Index Issue.srt 9KB
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11. Regex And Text Manipulation/3. String Methods In Python.srt 9KB
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14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.srt 9KB
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14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.srt 9KB
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9. Reshaping With Pivots/3. Pivoting Data.srt 8KB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.srt 8KB
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4. Working With DataFrames/13. Extracting From DataFrames By Label.srt 8KB
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14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.srt 8KB
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7. Going MultiDimensional/19. The Flipside unstack().srt 8KB
11. Regex And Text Manipulation/6. Finding Characters And Words.srt 8KB
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7. Going MultiDimensional/15. Removing MultiIndex Levels.srt 8KB
7. Going MultiDimensional/16. MultiIndex sort_index().srt 8KB
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4. Working With DataFrames/20. The astype() Method.srt 7KB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.srt 7KB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.srt 7KB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().srt 7KB
5. DataFrames In Depth/43. Solution.srt 7KB
7. Going MultiDimensional/18. Reshaping With stack().srt 7KB
1. Introduction/5. Cloud vs Local.srt 7KB
11. Regex And Text Manipulation/12. Slicing Substrings.srt 7KB
9. Reshaping With Pivots/6. The pivot_table().srt 7KB
4. Working With DataFrames/30. Using Series between() With DataFrames.srt 7KB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.srt 7KB
7. Going MultiDimensional/9. Cross Sections With xs().srt 7KB
10. Handling Date And Time/15. Creating Date Ranges.srt 7KB
7. Going MultiDimensional/13. Adding Another Level.srt 7KB
2. Series At A Glance/4. What’s In The Data.srt 7KB
6. Working With Multiple DataFrames/12. The merge() Method.srt 7KB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.srt 7KB
10. Handling Date And Time/23. Solution.srt 7KB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.srt 7KB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.srt 7KB
9. Reshaping With Pivots/5. What About Aggregates.srt 7KB
8. GroupBy And Aggregates/14. MultiIndex Grouping.srt 7KB
5. DataFrames In Depth/20. Removing Duplicates.srt 7KB
8. GroupBy And Aggregates/17. The filter() Method.srt 7KB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.srt 7KB
9. Reshaping With Pivots/4. Undoing Pivots.srt 7KB
2. Series At A Glance/21. Selection Recap.srt 7KB
4. Working With DataFrames/34. Solution.srt 7KB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.srt 7KB
2. Series At A Glance/23. Solution.srt 7KB
3. Series Methods And Handling/16. idxmax() And idxmin().srt 6KB
9. Reshaping With Pivots/13. Solution.srt 6KB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.srt 6KB
8. GroupBy And Aggregates/4. Conditional Aggregates.srt 6KB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.srt 6KB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.srt 6KB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.srt 6KB
8. GroupBy And Aggregates/11. Solution.srt 6KB
8. GroupBy And Aggregates/3. Simple Aggregations Review.srt 6KB
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8. GroupBy And Aggregates/21. Solution.srt 6KB
2. Series At A Glance/12. The head() And tail() Methods.srt 6KB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.srt 6KB
10. Handling Date And Time/7. The Pandas Timestamp.srt 6KB
5. DataFrames In Depth/35. Solution.srt 6KB
7. Going MultiDimensional/2. Introducing New Data.srt 6KB
13. Data Formats And IO/7. Pickles In Pandas.srt 6KB
7. Going MultiDimensional/14. Shuffling Levels.srt 6KB
10. Handling Date And Time/5. From Datetime To String.srt 6KB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.srt 6KB
6. Working With Multiple DataFrames/9. Concat On Different Columns.srt 6KB
4. Working With DataFrames/15. Single Value Access With .at And .iat.srt 6KB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.srt 6KB
3. Series Methods And Handling/24. Cumulative Operations.srt 6KB
8. GroupBy And Aggregates/9. BONUS - Series groupby().srt 6KB
3. Series Methods And Handling/7. BONUS Another Approach.srt 6KB
2. Series At A Glance/20. Selecting With .get().srt 6KB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.srt 6KB
10. Handling Date And Time/8. Our Dataset Brent Prices.srt 6KB
3. Series Methods And Handling/17. Sorting With sort_values().srt 6KB
10. Handling Date And Time/11. Indexing Dates.srt 6KB
13. Data Formats And IO/2. Reading JSON.srt 6KB
9. Reshaping With Pivots/9. Adding Margins.srt 6KB
8. GroupBy And Aggregates/6. The groupby() Method.srt 6KB
4. Working With DataFrames/3. Creating A DataFrame.srt 5KB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().srt 5KB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.srt 5KB
8. GroupBy And Aggregates/13. Handpicking Subgroups.srt 5KB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().srt 5KB
5. DataFrames In Depth/8. Conditions As Variables.srt 5KB
4. Working With DataFrames/5. The info() Method.srt 5KB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.srt 5KB
5. DataFrames In Depth/23. BONUS - Another Way pop().srt 5KB
1. Introduction/6. Hello, Python.srt 5KB
10. Handling Date And Time/4. Even Better dateutil.srt 5KB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.srt 5KB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.srt 5KB
3. Series Methods And Handling/12. Dropping And Filling NAs.srt 5KB
7. Going MultiDimensional/3. Index And RangeIndex.srt 5KB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.srt 5KB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.srt 5KB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.srt 5KB
4. Working With DataFrames/11. DataFrame Axes.srt 5KB
11. Regex And Text Manipulation/11. Solution.srt 5KB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.srt 5KB
7. Going MultiDimensional/5. MultiIndex From read_csv().srt 5KB
4. Working With DataFrames/8. The sample() Method.srt 5KB
13. Data Formats And IO/8. The Many Other Formats.srt 5KB
2. Series At A Glance/2. What Is A Series.srt 5KB
9. Reshaping With Pivots/11. Applying Multiple Functions.srt 5KB
2. Series At A Glance/10. Solution.srt 5KB
3. Series Methods And Handling/26. Series Iteration.srt 5KB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.srt 5KB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.srt 5KB
7. Going MultiDimensional/4. Creating A MultiIndex.srt 5KB
4. Working With DataFrames/6. Reading In Nutrition Data.srt 5KB
5. DataFrames In Depth/2. Introducing A New Dataset.srt 5KB
2. Series At A Glance/16. Using Dot Notation.srt 5KB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.srt 4KB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.srt 4KB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.srt 4KB
6. Working With Multiple DataFrames/15. Left vs Right Joins.srt 4KB
5. DataFrames In Depth/18. Solution.srt 4KB
2. Series At A Glance/18. Extracting By Position With .iloc.srt 4KB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.srt 4KB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.srt 4KB
3. Series Methods And Handling/25. Pairwise Differences With diff().srt 4KB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.srt 4KB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.srt 4KB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().srt 4KB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.srt 4KB
8. GroupBy And Aggregates/12. Iterating Through Groups.srt 4KB
Sources/drinks (1).csv 4KB
Sources/drinks (2).csv 4KB
Sources/drinks.csv 4KB
3. Series Methods And Handling/19. Sorting With sort_index().srt 4KB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.srt 4KB
7. Going MultiDimensional/22. BONUS - What About Panels.srt 4KB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.srt 4KB
10. Handling Date And Time/13. Solution.srt 4KB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.srt 4KB
4. Working With DataFrames/19. More Cleanup Going Numeric.srt 4KB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.srt 4KB
8. GroupBy And Aggregates/2. New Data Game Sales.srt 4KB
1. Introduction/3. Anaconda.srt 4KB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.srt 4KB
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11. Regex And Text Manipulation/5. Case Operations.srt 4KB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.srt 4KB
2. Series At A Glance/11. Another Solution.srt 4KB
12. Visualizing Data/2. The Art Of Data Visualization.srt 4KB
5. DataFrames In Depth/22. BONUS - Removing Columns.srt 4KB
13. Data Formats And IO/9. Skill Challenge.srt 4KB
5. DataFrames In Depth/21. Removing DataFrame Rows.srt 3KB
2. Series At A Glance/3. Parameters vs Arguments.srt 3KB
3. Series Methods And Handling/18. nlargest() And nsmallest().srt 3KB
3. Series Methods And Handling/8. The Other Side notnull() And notna().srt 3KB
7. Going MultiDimensional/21. An Easier Way transpose().srt 3KB
3. Series Methods And Handling/29. Skill Challenge.srt 3KB
6. Working With Multiple DataFrames/19. The join() Method.srt 3KB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().srt 3KB
5. DataFrames In Depth/1. Section Intro.srt 3KB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.srt 3KB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.srt 3KB
Sources/liberal_arts.csv 3KB
3. Series Methods And Handling/5. The count() Method.srt 3KB
2. Series At A Glance/9. Skill Challenge.srt 3KB
5. DataFrames In Depth/15. BONUS - Another Way.srt 3KB
5. DataFrames In Depth/34. Skill Challenge.srt 3KB
3. Series Methods And Handling/30. Solution I - Reading Data.srt 3KB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.srt 3KB
2. Series At A Glance/5. The .dtype Attribute.srt 3KB
3. Series Methods And Handling/14. The describe() Method.srt 3KB
3. Series Methods And Handling/21. Solution.srt 2KB
1. Introduction/2. Pandas Is Not Single.srt 2KB
3. Series Methods And Handling/1. Section Intro.srt 2KB
4. Working With DataFrames/35. Another Skill Challenge.srt 2KB
2. Series At A Glance/22. Skill Challenge.srt 2KB
7. Going MultiDimensional/1. Section Intro.srt 2KB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.srt 2KB
4. Working With DataFrames/1. Section Intro.srt 2KB
11. Regex And Text Manipulation/1. Section Intro.srt 2KB
6. Working With Multiple DataFrames/10. Skill Challenge.srt 2KB
12. Visualizing Data/11. Skill Challenge.srt 2KB
5. DataFrames In Depth/42. Skill Challenge.srt 2KB
7. Going MultiDimensional/23. Skill Challenge.srt 2KB
11. Regex And Text Manipulation/22. Skill Challenge.srt 2KB
5. DataFrames In Depth/28. Skill Challenge.srt 2KB
1. Introduction/1. Course Structure.srt 2KB
10. Handling Date And Time/22. Skill Challenge.srt 2KB
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4. Working With DataFrames/33. Skill Challenge.srt 2KB
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9. Reshaping With Pivots/12. Skill Challenge.srt 2KB
10. Handling Date And Time/1. Section Intro.srt 2KB
9. Reshaping With Pivots/1. Section Intro.srt 2KB
Sources/eng.csv 2KB
8. GroupBy And Aggregates/20. Skill Challenge.srt 2KB
6. Working With Multiple DataFrames/1. Section Intro.srt 2KB
5. DataFrames In Depth/9. Skill Challenge.srt 1KB
3. Series Methods And Handling/10. Skill Challenge.srt 1KB
8. GroupBy And Aggregates/1. Section Intro.srt 1KB
5. DataFrames In Depth/17. Skill Challenge.srt 1KB
Sources/portfolio.zip 1KB
6. Working With Multiple DataFrames/20. Skill Challenge.srt 1KB
11. Regex And Text Manipulation/10. Skill Challenge.srt 1KB
2. Series At A Glance/1. Section Intro.srt 1KB
10. Handling Date And Time/12. Skill Challenge.srt 1KB
3. Series Methods And Handling/20. Skill Challenge.srt 1KB
8. GroupBy And Aggregates/10. Skill Challenge.srt 1KB
13. Data Formats And IO/1. Section Intro.srt 1KB
Sources/ivies.csv 548B
Sources/folks.json 244B
0. Websites you may like/[CourseClub.Me].url 122B
12. Visualizing Data/[CourseClub.Me].url 122B
5. DataFrames In Depth/[CourseClub.Me].url 122B
[CourseClub.Me].url 122B
0. Websites you may like/[GigaCourse.Com].url 49B
12. Visualizing Data/[GigaCourse.Com].url 49B
5. DataFrames In Depth/[GigaCourse.Com].url 49B
[GigaCourse.Com].url 49B