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The Ultimate Pandas Bootcamp Advanced Python Data Analysis
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[TutsNode.com] - The Ultimate Pandas Bootcamp Advanced Python Data Analysis (Size: 9.79 GB) (Files: 1042)
[TutsNode.com] - The Ultimate Pandas Bootcamp Advanced Python Data Analysis
13. Data Formats And IO
3. Reading HTML.mp4
3. Reading HTML.srt
5. Creating Output The to_ Family Of Methods.mp4
5. Creating Output The to_ Family Of Methods.srt
4. Reading Excel.srt
10. Solution.srt
6. BONUS Introduction To Pickling.srt
7. Pickles In Pandas.srt
2. Reading JSON.srt
8. The Many Other Formats.srt
9. Skill Challenge.srt
1. Section Intro.srt
4. Reading Excel.mp4
10. Solution.mp4
6. BONUS Introduction To Pickling.mp4
8. The Many Other Formats.mp4
7. Pickles In Pandas.mp4
2. Reading JSON.mp4
9. Skill Challenge.mp4
1. Section Intro.mp4
Sources
MemoryLayout.pdf
Variance.pdf
Visualizing_Data.ipynb.zip
tech_giants (1).csv
ViewVsCopy.pdf
tech_giants.csv
games_sales (1).csv
Vectorization.pdf
SplitApplyCombine.pdf
games_sales (2).csv
games_sales.csv
SelectionRecap.pdf
WhatIsDtype.pdf
MultiIndexInternals.pdf
Working_With_DataFrames.zip
Handling_Time_And_Date.ipynb.zip
BrentOilPrices (1).csv
BrentOilPrices.csv
WhatIsASeries.pdf
scores (1).csv
scores.csv
SelectionTerminology.pdf
3KeyConcepts.pdf
ConcatVsMerge.pdf
WhatIsCSV.pdf
TwosComplement.pdf
mid_career_salaries.csv
folks.json
DataFrames_In_Depth.zip
DropnaWithSubset.pdf
2017BostonMarathonTop1000 (1).csv
2017BostonMarathonTop1000.csv
DroppingAndFillingNA.pdf
Lookup.pdf
AppendVsConcat.pdf
Transforms.pdf
SortValueOrIndex.pdf
BooleanMasks.pdf
InnerVsOuter.pdf
SeriesAtGlance.pdf
Diff.pdf
SizeAndShape.pdf
SeriesAccounting.pdf
Going_MultiDimensional.zip
SeqVsVectorizedOperations.pdf
LeftVsRight.pdf
IdxminIdxmax.pdf
RangeVSInt64Index.pdf
BoolsAsInts.pdf
ValueCounts.pdf
JoinCardinalities.pdf
soccer.csv
OurProcess.pdf
Median.pdf
MethodsVAttribtues.pdf
Series_Methods_And_Handling.zip
AtAndIat.pdf
Regex_And_Text_Manipulation.ipynb.zip
IndexingWithCallables.pdf
MoreWaysToBuildDataframes.pdf
Comparators.pdf
Working_With_Multiple_DataFrames.zip
ViewVsCopyHowDoWeTell.pdf
Appendix_A_Rapid_Fire_Python_Fundamentals.ipynb.zip
BinaryOperators.pdf
Duplicates.pdf
Data_Formats_And_I_O.ipynb.zip
GroupBy_And_Aggregates.ipynb.zip
WhatsInTheData.pdf
ArgsVParams.pdf
Reshaping_With_Pivots.ipynb.zip
Series_At_Glance.zip
state.csv
regions.csv
folks.xlsx
drinks (1).csv
drinks (2).csv
drinks.csv
liberal_arts.csv
eng.csv
portfolio.zip
ivies.csv
nutrition.csv
1. Introduction
1. Course Structure.srt
2. Pandas Is Not Single.srt
7. NumPy.srt
4. Jupyter Notebooks.srt
5. Cloud vs Local.srt
6. Hello, Python.srt
3. Anaconda.srt
7. NumPy.mp4
4. Jupyter Notebooks.mp4
6. Hello, Python.mp4
5. Cloud vs Local.mp4
3. Anaconda.mp4
2. Pandas Is Not Single.mp4
1. Course Structure.mp4
11. Regex And Text Manipulation
19. Is This A Valid Email.mp4
21. Pandas str contains(), split() And replace() With Regex.mp4
16. Introduction To Regular Expressions.mp4
19. Is This A Valid Email.srt
21. Pandas str contains(), split() And replace() With Regex.srt
16. Introduction To Regular Expressions.srt
23. Solution.srt
18. How To Approach Regex.srt
14. BONUS Parsing Indicators With get_dummies().srt
17. More Regex Concepts.srt
8. String Splitting And Concatenation.srt
9. More Split Parameters.srt
15. Text Replacement.srt
3. String Methods In Python.srt
23. Solution.mp4
7. Strips And Whitespace.srt
13. Masking With String Methods.srt
6. Finding Characters And Words.srt
12. Slicing Substrings.srt
11. Solution.srt
4. Vectorized String Operations In Pandas.srt
20. BONUS What's The Point Of re.compile().srt
2. Our Data Boston Marathon Runners.srt
5. Case Operations.srt
1. Section Intro.srt
22. Skill Challenge.srt
10. Skill Challenge.srt
14. BONUS Parsing Indicators With get_dummies().mp4
17. More Regex Concepts.mp4
18. How To Approach Regex.mp4
8. String Splitting And Concatenation.mp4
15. Text Replacement.mp4
9. More Split Parameters.mp4
13. Masking With String Methods.mp4
7. Strips And Whitespace.mp4
3. String Methods In Python.mp4
6. Finding Characters And Words.mp4
12. Slicing Substrings.mp4
2. Our Data Boston Marathon Runners.mp4
11. Solution.mp4
4. Vectorized String Operations In Pandas.mp4
20. BONUS What's The Point Of re.compile().mp4
1. Section Intro.mp4
5. Case Operations.mp4
22. Skill Challenge.mp4
10. Skill Challenge.mp4
9. Reshaping With Pivots
9. Adding Margins.srt
8. Replicating Pivot Tables With GroupBy.srt
7. BONUS The Problem With Average Percentage.srt
3. Pivoting Data.srt
6. The pivot_table().srt
5. What About Aggregates.srt
4. Undoing Pivots.srt
13. Solution.srt
2. New Data New York City SAT Scores.srt
11. Applying Multiple Functions.srt
10. MultiIndex Pivot Tables.srt
12. Skill Challenge.srt
1. Section Intro.srt
3. Pivoting Data.mp4
13. Solution.mp4
7. BONUS The Problem With Average Percentage.mp4
5. What About Aggregates.mp4
6. The pivot_table().mp4
4. Undoing Pivots.mp4
2. New Data New York City SAT Scores.mp4
9. Adding Margins.mp4
1. Section Intro.mp4
10. MultiIndex Pivot Tables.mp4
11. Applying Multiple Functions.mp4
8. Replicating Pivot Tables With GroupBy.mp4
12. Skill Challenge.mp4
2. Series At A Glance
1. Section Intro.srt
5. The .dtype Attribute.srt
9. Skill Challenge.srt
22. Skill Challenge.srt
19. BONUS Using Callables With .loc And .iloc.srt
17. Boolean Masks And The .loc Indexer.srt
13. Extracting By Index Position.srt
7. Index And RangeIndex.srt
14. Accessing Elements By Label.srt
4. What’s In The Data.srt
21. Selection Recap.srt
23. Solution.srt
8. Series And Index Names.srt
12. The head() And tail() Methods.srt
20. Selecting With .get().srt
2. What Is A Series.srt
10. Solution.srt
16. Using Dot Notation.srt
18. Extracting By Position With .iloc.srt
15. BONUS The add_prefix() And add_suffix() Methods.srt
6. BONUS What Is dtype('o'), Really.srt
11. Another Solution.srt
3. Parameters vs Arguments.srt
19. BONUS Using Callables With .loc And .iloc.mp4
7. Index And RangeIndex.mp4
20. Selecting With .get().mp4
17. Boolean Masks And The .loc Indexer.mp4
13. Extracting By Index Position.mp4
21. Selection Recap.mp4
14. Accessing Elements By Label.mp4
23. Solution.mp4
12. The head() And tail() Methods.mp4
10. Solution.mp4
4. What’s In The Data.mp4
8. Series And Index Names.mp4
15. BONUS The add_prefix() And add_suffix() Methods.mp4
16. Using Dot Notation.mp4
2. What Is A Series.mp4
18. Extracting By Position With .iloc.mp4
11. Another Solution.mp4
6. BONUS What Is dtype('o'), Really.mp4
3. Parameters vs Arguments.mp4
9. Skill Challenge.mp4
1. Section Intro.mp4
22. Skill Challenge.mp4
5. The .dtype Attribute.mp4
6. Working With Multiple DataFrames
8. The append() Method A Special Case Of concat().srt
11. Solution.srt
16. One-to-One and One-to-Many Joins.srt
17. Many-to-Many Joins.srt
5. Enforcing Unique Indices.srt
3. Concatenating DataFrames.srt
4. The Duplicated Index Issue.srt
21. Solution.srt
12. The merge() Method.srt
2. Introducing (Five) New Datasets.srt
14. Inner vs Outer Joins.srt
1. Section Intro.srt
18. Merging By Index.srt
9. Concat On Different Columns.srt
10. Skill Challenge.srt
6. BONUS - Creating Multiple Indices With concat().srt
20. Skill Challenge.srt
7. Column Axis Concatenation.srt
13. The left_on And right_on Params.srt
15. Left vs Right Joins.srt
19. The join() Method.srt
11. Solution.mp4
5. Enforcing Unique Indices.mp4
16. One-to-One and One-to-Many Joins.mp4
17. Many-to-Many Joins.mp4
4. The Duplicated Index Issue.mp4
21. Solution.mp4
3. Concatenating DataFrames.mp4
2. Introducing (Five) New Datasets.mp4
9. Concat On Different Columns.mp4
18. Merging By Index.mp4
12. The merge() Method.mp4
13. The left_on And right_on Params.mp4
6. BONUS - Creating Multiple Indices With concat().mp4
14. Inner vs Outer Joins.mp4
7. Column Axis Concatenation.mp4
19. The join() Method.mp4
15. Left vs Right Joins.mp4
8. The append() Method A Special Case Of concat().mp4
1. Section Intro.mp4
10. Skill Challenge.mp4
20. Skill Challenge.mp4
3. Series Methods And Handling
1. Section Intro.srt
5. The count() Method.srt
10. Skill Challenge.srt
14. The describe() Method.srt
20. Skill Challenge.srt
21. Solution.srt
28. Transforming With update(), apply() And map().srt
27. Filtering filter(), where(), And mask().srt
30. Solution I - Reading Data.srt
9. BONUS Booleans Are Literally Numbers In Python.srt
6. Accessing And Counting NAs.srt
2. Reading In Data With read_csv().srt
32. Solution III - Z-scores.srt
13. Descriptive Statistics.srt
22. Series Arithmetics And fill_value().srt
15. mode() And value_counts().srt
16. idxmax() And idxmin().srt
4. Unique Values And Series Monotonicity.srt
24. Cumulative Operations.srt
7. BONUS Another Approach.srt
17. Sorting With sort_values().srt
3. Series Sizing With .size, .shape, And len().srt
23. BONUS Calculating Variance And Standard Deviation.srt
12. Dropping And Filling NAs.srt
26. Series Iteration.srt
25. Pairwise Differences With diff().srt
31. Solution II - Mean, Median, And Standard Deviation.srt
19. Sorting With sort_index().srt
11. Solution.srt
18. nlargest() And nsmallest().srt
8. The Other Side notnull() And notna().srt
29. Skill Challenge.srt
28. Transforming With update(), apply() And map().mp4
27. Filtering filter(), where(), And mask().mp4
2. Reading In Data With read_csv().mp4
32. Solution III - Z-scores.mp4
22. Series Arithmetics And fill_value().mp4
6. Accessing And Counting NAs.mp4
13. Descriptive Statistics.mp4
15. mode() And value_counts().mp4
3. Series Sizing With .size, .shape, And len().mp4
16. idxmax() And idxmin().mp4
12. Dropping And Filling NAs.mp4
7. BONUS Another Approach.mp4
31. Solution II - Mean, Median, And Standard Deviation.mp4
17. Sorting With sort_values().mp4
24. Cumulative Operations.mp4
4. Unique Values And Series Monotonicity.mp4
23. BONUS Calculating Variance And Standard Deviation.mp4
26. Series Iteration.mp4
19. Sorting With sort_index().mp4
30. Solution I - Reading Data.mp4
11. Solution.mp4
1. Section Intro.mp4
25. Pairwise Differences With diff().mp4
18. nlargest() And nsmallest().mp4
9. BONUS Booleans Are Literally Numbers In Python.mp4
8. The Other Side notnull() And notna().mp4
29. Skill Challenge.mp4
21. Solution.mp4
14. The describe() Method.mp4
5. The count() Method.mp4
10. Skill Challenge.mp4
20. Skill Challenge.mp4
5. DataFrames In Depth
31. Same-shape Transforms.srt
32. More Flexibility With apply().srt
33. Element-wise Operations With applymap().srt
14. Sorting vs. Reordering.srt
6. BONUS - XOR and Complement Binary Ops.srt
19. Identifying Dupes.srt
5. Binary Operators With Booleans.srt
4. More Approaches To Boolean Masking.srt
11. 2d Indexing.srt
30. Calculating Aggregates With agg().srt
40. Adding Rows To DataFrames.srt
27. BONUS - Methods And Axes With fillna().srt
38. View vs Copy.srt
39. Adding DataFrame Columns.srt
12. Fancy Indexing With lookup().srt
37. The SettingWithCopy Warning.srt
26. Dropping And Filling DataFrame NAs.srt
9. Skill Challenge.srt
7. Combining Conditions.srt
25. Null Values In DataFrames.srt
15. BONUS - Another Way.srt
29. Solution.srt
17. Skill Challenge.srt
36. Setting DataFrame Values.srt
13. Sorting By Index Or Column.srt
10. Solution.srt
43. Solution.srt
28. Skill Challenge.srt
34. Skill Challenge.srt
20. Removing Duplicates.srt
42. Skill Challenge.srt
35. Solution.srt
24. BONUS - A Sophisticated Alternative.srt
8. Conditions As Variables.srt
23. BONUS - Another Way pop().srt
41. BONUS - How Are DataFrames Stored In Memory.srt
2. Introducing A New Dataset.srt
18. Solution.srt
16. 15. BONUS - Please Avoid Sorting Like This.srt
3. Quick Review Indexing With Boolean Masks.srt
22. BONUS - Removing Columns.srt
21. Removing DataFrame Rows.srt
1. Section Intro.srt
33. Element-wise Operations With applymap().mp4
4. More Approaches To Boolean Masking.mp4
31. Same-shape Transforms.mp4
14. Sorting vs. Reordering.mp4
19. Identifying Dupes.mp4
32. More Flexibility With apply().mp4
27. BONUS - Methods And Axes With fillna().mp4
6. BONUS - XOR and Complement Binary Ops.mp4
40. Adding Rows To DataFrames.mp4
38. View vs Copy.mp4
26. Dropping And Filling DataFrame NAs.mp4
12. Fancy Indexing With lookup().mp4
7. Combining Conditions.mp4
13. Sorting By Index Or Column.mp4
36. Setting DataFrame Values.mp4
29. Solution.mp4
25. Null Values In DataFrames.mp4
10. Solution.mp4
11. 2d Indexing.mp4
37. The SettingWithCopy Warning.mp4
5. Binary Operators With Booleans.mp4
30. Calculating Aggregates With agg().mp4
39. Adding DataFrame Columns.mp4
24. BONUS - A Sophisticated Alternative.mp4
43. Solution.mp4
20. Removing Duplicates.mp4
35. Solution.mp4
18. Solution.mp4
3. Quick Review Indexing With Boolean Masks.mp4
41. BONUS - How Are DataFrames Stored In Memory.mp4
1. Section Intro.mp4
8. Conditions As Variables.mp4
21. Removing DataFrame Rows.mp4
23. BONUS - Another Way pop().mp4
2. Introducing A New Dataset.mp4
16. 15. BONUS - Please Avoid Sorting Like This.mp4
22. BONUS - Removing Columns.mp4
15. BONUS - Another Way.mp4
34. Skill Challenge.mp4
28. Skill Challenge.mp4
42. Skill Challenge.mp4
17. Skill Challenge.mp4
9. Skill Challenge.mp4
4. Working With DataFrames
4. BONUS - Four More Ways To Build DataFrames.srt
22. Part I Collecting The Units.srt
26. Part II Merging Units With Column Names.srt
4. BONUS - Four More Ways To Build DataFrames.mp4
1. Section Intro.srt
21. DataFrame replace() + A Glimpse At Regex.srt
2. What Is A DataFrame.srt
24. DataFrame dropna().srt
17. Skill Challenge.srt
31. BONUS - Min, Max and Idx[MinMax], And Good Foods.srt
28. Filtering in 2D.srt
18. Solution.srt
14. DataFrame Extraction by Position.srt
33. Skill Challenge.srt
25. BONUS - dropna() With Subset.srt
35. Another Skill Challenge.srt
9. BONUS - Sampling With Replacement Or Weights.srt
23. The rename() Method.srt
29. DataFrame Sorting.srt
12. Changing The Index.srt
13. Extracting From DataFrames By Label.srt
16. BONUS - The get_loc() Method.srt
36. Solution.srt
27. Part III Removing Units From Values.srt
20. The astype() Method.srt
32. DataFrame nlargest() And nsmallest().srt
30. Using Series between() With DataFrames.srt
10. BONUS - How Are Random Numbers Generated.srt
34. Solution.srt
7. Some Cleanup Removing The Duplicated Index.srt
15. Single Value Access With .at And .iat.srt
3. Creating A DataFrame.srt
5. The info() Method.srt
11. DataFrame Axes.srt
8. The sample() Method.srt
6. Reading In Nutrition Data.srt
19. More Cleanup Going Numeric.srt
22. Part I Collecting The Units.mp4
31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4
26. Part II Merging Units With Column Names.mp4
12. Changing The Index.mp4
29. DataFrame Sorting.mp4
14. DataFrame Extraction by Position.mp4
2. What Is A DataFrame.mp4
18. Solution.mp4
21. DataFrame replace() + A Glimpse At Regex.mp4
10. BONUS - How Are Random Numbers Generated.mp4
28. Filtering in 2D.mp4
34. Solution.mp4
9. BONUS - Sampling With Replacement Or Weights.mp4
24. DataFrame dropna().mp4
36. Solution.mp4
13. Extracting From DataFrames By Label.mp4
27. Part III Removing Units From Values.mp4
7. Some Cleanup Removing The Duplicated Index.mp4
32. DataFrame nlargest() And nsmallest().mp4
30. Using Series between() With DataFrames.mp4
25. BONUS - dropna() With Subset.mp4
23. The rename() Method.mp4
6. Reading In Nutrition Data.mp4
15. Single Value Access With .at And .iat.mp4
20. The astype() Method.mp4
16. BONUS - The get_loc() Method.mp4
11. DataFrame Axes.mp4
8. The sample() Method.mp4
3. Creating A DataFrame.mp4
5. The info() Method.mp4
19. More Cleanup Going Numeric.mp4
1. Section Intro.mp4
35. Another Skill Challenge.mp4
33. Skill Challenge.mp4
17. Skill Challenge.mp4
7. Going MultiDimensional
7. Indexing Ranges And Slices.srt
20. BONUS Creating MultiLevel Columns Manually.srt
12. The Anatomy Of A MultiIndex Object.srt
6. Indexing Hierarchical DataFrames.srt
11. Solution.srt
17. More MultiIndex Methods.srt
24. Solution.srt
19. The Flipside unstack().srt
15. Removing MultiIndex Levels.srt
16. MultiIndex sort_index().srt
18. Reshaping With stack().srt
9. Cross Sections With xs().srt
13. Adding Another Level.srt
2. Introducing New Data.srt
14. Shuffling Levels.srt
23. Skill Challenge.srt
1. Section Intro.srt
3. Index And RangeIndex.srt
8. BONUS - Use With pd.IndexSlice!.srt
5. MultiIndex From read_csv().srt
10. Skill Challenge.srt
4. Creating A MultiIndex.srt
22. BONUS - What About Panels.srt
21. An Easier Way transpose().srt
7. Indexing Ranges And Slices.mp4
20. BONUS Creating MultiLevel Columns Manually.mp4
24. Solution.mp4
19. The Flipside unstack().mp4
11. Solution.mp4
6. Indexing Hierarchical DataFrames.mp4
17. More MultiIndex Methods.mp4
15. Removing MultiIndex Levels.mp4
16. MultiIndex sort_index().mp4
12. The Anatomy Of A MultiIndex Object.mp4
13. Adding Another Level.mp4
9. Cross Sections With xs().mp4
18. Reshaping With stack().mp4
22. BONUS - What About Panels.mp4
5. MultiIndex From read_csv().mp4
3. Index And RangeIndex.mp4
1. Section Intro.mp4
14. Shuffling Levels.mp4
2. Introducing New Data.mp4
4. Creating A MultiIndex.mp4
21. An Easier Way transpose().mp4
8. BONUS - Use With pd.IndexSlice!.mp4
23. Skill Challenge.mp4
10. Skill Challenge.mp4
12. Visualizing Data
3. The Preliminaries Of matplotlib.srt
4. Line Graphs.srt
8. Scatter Plots.srt
6. Pie Plots.srt
5. Bar Charts.srt
7. Histograms.srt
9. Other Visualization Options.srt
12. Solution.srt
10. BONUS Data Ink And Chartjunk.srt
2. The Art Of Data Visualization.srt
11. Skill Challenge.srt
1. Section Intro.srt
9. Other Visualization Options.mp4
8. Scatter Plots.mp4
3. The Preliminaries Of matplotlib.mp4
6. Pie Plots.mp4
12. Solution.mp4
4. Line Graphs.mp4
5. Bar Charts.mp4
7. Histograms.mp4
10. BONUS Data Ink And Chartjunk.mp4
2. The Art Of Data Visualization.mp4
1. Section Intro.mp4
11. Skill Challenge.mp4
14. Appendix A - Rapid-Fire Python Fundamentals
25. Defining Functions.srt
13. Containers III Sets.srt
5. Ints And Floats.srt
3. Variables.srt
17. Controlling Flow if, else, And elif.srt
15. Dictionary Keys And Values.srt
11. List Methods And Functions.srt
7. Strings.srt
24. List Comprehensions.srt
26. Function Arguments Positional vs Keyword.srt
10. Lists vs. Strings.srt
4. Arithmetic And Augmented Assignment Operators.srt
8. Methods.srt
21. While Loops.srt
9. Containers I Lists.srt
28. Importing Modules.srt
27. Lambdas.srt
19. For Loops.srt
14. Containers IV Dictionaries.srt
20. The range() Immutable Sequence.srt
6. Booleans And Comparison Operators.srt
22. Break And Continue.srt
12. Containers II Tuples.srt
16. Membership Operators.srt
18. Truth Value Of Non-booleans.srt
23. Zipping Iterables.srt
2. Data Types.srt
1. Section Intro.srt
25. Defining Functions.mp4
13. Containers III Sets.mp4
5. Ints And Floats.mp4
17. Controlling Flow if, else, And elif.mp4
3. Variables.mp4
15. Dictionary Keys And Values.mp4
28. Importing Modules.mp4
11. List Methods And Functions.mp4
7. Strings.mp4
24. List Comprehensions.mp4
26. Function Arguments Positional vs Keyword.mp4
9. Containers I Lists.mp4
21. While Loops.mp4
10. Lists vs. Strings.mp4
4. Arithmetic And Augmented Assignment Operators.mp4
8. Methods.mp4
20. The range() Immutable Sequence.mp4
27. Lambdas.mp4
14. Containers IV Dictionaries.mp4
6. Booleans And Comparison Operators.mp4
19. For Loops.mp4
12. Containers II Tuples.mp4
16. Membership Operators.mp4
22. Break And Continue.mp4
23. Zipping Iterables.mp4
18. Truth Value Of Non-booleans.mp4
2. Data Types.mp4
1. Section Intro.mp4
10. Handling Date And Time
21. BONUS Rolling Windows.srt
2. The Python datetime Module.srt
3. Parsing Dates From Text.srt
19. Upsampling And Interpolation.srt
20. What About asfreq().srt
6. Performant Datetimes With Numpy.srt
18. Resampling Timeseries.srt
14. DateTimeIndex Attribute Accessors.srt
16. Shifting Dates With pd.DateOffset.srt
17. BONUS Timedeltas And Absolute Time.srt
15. Creating Date Ranges.srt
23. Solution.srt
9. Date Parsing And DatetimeIndex.srt
7. The Pandas Timestamp.srt
5. From Datetime To String.srt
8. Our Dataset Brent Prices.srt
11. Indexing Dates.srt
4. Even Better dateutil.srt
10. A Cool Shorcut read_csv() With parse_dates.srt
13. Solution.srt
22. Skill Challenge.srt
1. Section Intro.srt
12. Skill Challenge.srt
3. Parsing Dates From Text.mp4
19. Upsampling And Interpolation.mp4
21. BONUS Rolling Windows.mp4
2. The Python datetime Module.mp4
18. Resampling Timeseries.mp4
14. DateTimeIndex Attribute Accessors.mp4
20. What About asfreq().mp4
15. Creating Date Ranges.mp4
16. Shifting Dates With pd.DateOffset.mp4
6. Performant Datetimes With Numpy.mp4
8. Our Dataset Brent Prices.mp4
17. BONUS Timedeltas And Absolute Time.mp4
11. Indexing Dates.mp4
9. Date Parsing And DatetimeIndex.mp4
7. The Pandas Timestamp.mp4
4. Even Better dateutil.mp4
23. Solution.mp4
5. From Datetime To String.mp4
1. Section Intro.mp4
10. A Cool Shorcut read_csv() With parse_dates.mp4
13. Solution.mp4
22. Skill Challenge.mp4
12. Skill Challenge.mp4
8. GroupBy And Aggregates
15. Fine-tuned Aggregates.srt
18. GroupBy Transformations.srt
19. BONUS - There's Also apply().srt
16. Named Aggregations.srt
14. MultiIndex Grouping.srt
17. The filter() Method.srt
4. Conditional Aggregates.srt
11. Solution.srt
3. Simple Aggregations Review.srt
21. Solution.srt
9. BONUS - Series groupby().srt
6. The groupby() Method.srt
13. Handpicking Subgroups.srt
5. The Split-Apply-Combine Pattern.srt
8. Customizing Index To Group Mappings.srt
7. The DataFrameGroupBy Object.srt
12. Iterating Through Groups.srt
1. Section Intro.srt
2. New Data Game Sales.srt
10. Skill Challenge.srt
20. Skill Challenge.srt
15. Fine-tuned Aggregates.mp4
19. BONUS - There's Also apply().mp4
18. GroupBy Transformations.mp4
16. Named Aggregations.mp4
3. Simple Aggregations Review.mp4
11. Solution.mp4
14. MultiIndex Grouping.mp4
17. The filter() Method.mp4
21. Solution.mp4
4. Conditional Aggregates.mp4
13. Handpicking Subgroups.mp4
5. The Split-Apply-Combine Pattern.mp4
6. The groupby() Method.mp4
12. Iterating Through Groups.mp4
9. BONUS - Series groupby().mp4
8. Customizing Index To Group Mappings.mp4
7. The DataFrameGroupBy Object.mp4
1. Section Intro.mp4
2. New Data Game Sales.mp4
20. Skill Challenge.mp4
10. Skill Challenge.mp4
15. Appendix B - Going Local Installation And Setup
1. Installing Anaconda And Python - Windows.srt
1. Installing Anaconda And Python - Windows.mp4
3. Installing Anaconda And Python - Linux.srt
2. Installing Anaconda And Python - Mac.srt
3. Installing Anaconda And Python - Linux.mp4
2. Installing Anaconda And Python - Mac.mp4
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