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The Ultimate Pandas Bootcamp Advanced Python Data Analysis

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Added Saturday 1st July 2023 04:39:58 PM (3 years ago)
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Torrent Files (1042)
FilenameSize
3. Reading HTML.mp4103.7 MB
TutsNode.com.txt63 bytes
MemoryLayout.pdf246.3 KB
1. Course Structure.srt1.8 KB
Variance.pdf38.0 KB
2. Pandas Is Not Single.srt2.5 KB
Visualizing_Data.ipynb.zip500.7 KB
tech_giants (1).csv467.2 KB
ViewVsCopy.pdf53.3 KB
[TGx]Downloaded from torrentgalaxy.to .txt585 bytes
090 bytes
19. Is This A Valid Email.mp480.1 MB
tech_giants.csv467.2 KB
games_sales (1).csv236.9 KB
Vectorization.pdf115.3 KB
SplitApplyCombine.pdf114.8 KB
9. Adding Margins.srt5.5 KB
1. Section Intro.srt1.3 KB
games_sales (2).csv236.9 KB
games_sales.csv236.9 KB
SelectionRecap.pdf111.4 KB
WhatIsDtype.pdf110.9 KB
MultiIndexInternals.pdf110.7 KB
Working_With_DataFrames.zip105.5 KB
Handling_Time_And_Date.ipynb.zip104.7 KB
5. The .dtype Attribute.srt2.5 KB
8. The append() Method A Special Case Of concat().srt3.1 KB
143 bytes
21. Pandas str contains(), split() And replace() With Regex.mp476.3 MB
BrentOilPrices (1).csv78.8 KB
BrentOilPrices.csv78.8 KB
WhatIsASeries.pdf74.8 KB
scores (1).csv74.7 KB
9. Skill Challenge.srt2.8 KB
scores.csv74.7 KB
SelectionTerminology.pdf66.7 KB
3KeyConcepts.pdf63.0 KB
ConcatVsMerge.pdf62.7 KB
WhatIsCSV.pdf62.6 KB
TwosComplement.pdf60.5 KB
mid_career_salaries.csv22.7 KB
folks.json244 bytes
2129 bytes
16. Introduction To Regular Expressions.mp475.0 MB
DataFrames_In_Depth.zip59.4 KB
DropnaWithSubset.pdf58.8 KB
2017BostonMarathonTop1000 (1).csv57.5 KB
2017BostonMarathonTop1000.csv57.5 KB
DroppingAndFillingNA.pdf56.5 KB
Lookup.pdf49.7 KB
AppendVsConcat.pdf49.4 KB
Transforms.pdf47.3 KB
SortValueOrIndex.pdf44.2 KB
BooleanMasks.pdf43.9 KB
InnerVsOuter.pdf43.7 KB
SeriesAtGlance.pdf43.0 KB
Diff.pdf42.5 KB
SizeAndShape.pdf42.3 KB
SeriesAccounting.pdf42.0 KB
22. Skill Challenge.srt2.3 KB
Going_MultiDimensional.zip41.9 KB
SeqVsVectorizedOperations.pdf41.5 KB
LeftVsRight.pdf40.8 KB
1. Section Intro.srt2.4 KB
IdxminIdxmax.pdf40.1 KB
RangeVSInt64Index.pdf37.8 KB
BoolsAsInts.pdf37.5 KB
3. Reading HTML.srt16.4 KB
3526 bytes
5. Creating Output The to_ Family Of Methods.mp474.0 MB
ValueCounts.pdf36.0 KB
5. The count() Method.srt2.8 KB
JoinCardinalities.pdf35.3 KB
soccer.csv33.7 KB
OurProcess.pdf32.6 KB
Median.pdf32.5 KB
MethodsVAttribtues.pdf32.5 KB
Series_Methods_And_Handling.zip31.8 KB
AtAndIat.pdf30.6 KB
Regex_And_Text_Manipulation.ipynb.zip29.8 KB
IndexingWithCallables.pdf29.1 KB
10. Skill Challenge.srt1.5 KB
MoreWaysToBuildDataframes.pdf29.1 KB
Comparators.pdf28.7 KB
Working_With_Multiple_DataFrames.zip27.4 KB
ViewVsCopyHowDoWeTell.pdf27.1 KB
Appendix_A_Rapid_Fire_Python_Fundamentals.ipynb.zip25.6 KB
BinaryOperators.pdf24.4 KB
Duplicates.pdf24.3 KB
14. The describe() Method.srt2.5 KB
Data_Formats_And_I_O.ipynb.zip23.6 KB
GroupBy_And_Aggregates.ipynb.zip22.4 KB
WhatsInTheData.pdf19.2 KB
19. Is This A Valid Email.srt18.6 KB
5. Creating Output The to_ Family Of Methods.srt18.5 KB
ArgsVParams.pdf18.4 KB
31. Same-shape Transforms.srt18.1 KB
21. Pandas str contains(), split() And replace() With Regex.srt17.5 KB
4. BONUS - Four More Ways To Build DataFrames.srt17.4 KB
Reshaping_With_Pivots.ipynb.zip17.1 KB
32. More Flexibility With apply().srt16.4 KB
20. Skill Challenge.srt1.2 KB
16. Introduction To Regular Expressions.srt16.3 KB
21. Solution.srt2.5 KB
33. Element-wise Operations With applymap().srt16.0 KB
22. Part I Collecting The Units.srt15.5 KB
7. Indexing Ranges And Slices.srt14.9 KB
23. Solution.srt14.8 KB
28. Transforming With update(), apply() And map().srt14.6 KB
14. Sorting vs. Reordering.srt14.5 KB
3. The Preliminaries Of matplotlib.srt14.4 KB
7. NumPy.srt14.3 KB
6. BONUS - XOR and Complement Binary Ops.srt14.3 KB
4. Jupyter Notebooks.srt14.0 KB
25. Defining Functions.srt13.7 KB
Series_At_Glance.zip13.6 KB
4. Line Graphs.srt13.6 KB
27. Filtering filter(), where(), And mask().srt13.3 KB
18. How To Approach Regex.srt13.3 KB
21. BONUS Rolling Windows.srt13.2 KB
11. Solution.srt13.1 KB
30. Solution I - Reading Data.srt2.6 KB
26. Part II Merging Units With Column Names.srt12.9 KB
19. Identifying Dupes.srt12.9 KB
9. BONUS Booleans Are Literally Numbers In Python.srt3.8 KB
413 bytes
4. BONUS - Four More Ways To Build DataFrames.mp473.2 MB
1. Section Intro.srt2.3 KB
21. DataFrame replace() + A Glimpse At Regex.srt12.9 KB
20. BONUS Creating MultiLevel Columns Manually.srt12.7 KB
14. BONUS Parsing Indicators With get_dummies().srt12.6 KB
2. The Python datetime Module.srt12.5 KB
17. More Regex Concepts.srt12.4 KB
8. Scatter Plots.srt12.2 KB
13. Containers III Sets.srt12.2 KB
5. Binary Operators With Booleans.srt12.2 KB
2. What Is A DataFrame.srt12.0 KB
6. Pie Plots.srt12.0 KB
24. DataFrame dropna().srt11.9 KB
5. Bar Charts.srt11.9 KB
state.csv11.6 KB
3. Parsing Dates From Text.srt11.6 KB
4. More Approaches To Boolean Masking.srt11.6 KB
7. Histograms.srt11.4 KB
5. Ints And Floats.srt11.4 KB
11. 2d Indexing.srt11.4 KB
30. Calculating Aggregates With agg().srt11.4 KB
40. Adding Rows To DataFrames.srt11.3 KB
3. Variables.srt11.1 KB
19. Upsampling And Interpolation.srt11.1 KB
regions.csv11.0 KB
20. What About asfreq().srt10.9 KB
27. BONUS - Methods And Axes With fillna().srt10.9 KB
8. String Splitting And Concatenation.srt10.8 KB
17. Controlling Flow if, else, And elif.srt10.8 KB
6. Accessing And Counting NAs.srt10.8 KB
38. View vs Copy.srt10.7 KB
19. BONUS Using Callables With .loc And .iloc.srt10.7 KB
15. Dictionary Keys And Values.srt10.6 KB
17. Skill Challenge.srt1.7 KB
31. BONUS - Min, Max and Idx[MinMax], And Good Foods.srt10.5 KB
11. List Methods And Functions.srt10.5 KB
28. Filtering in 2D.srt10.5 KB
12. The Anatomy Of A MultiIndex Object.srt10.4 KB
15. Fine-tuned Aggregates.srt10.4 KB
16. One-to-One and One-to-Many Joins.srt10.4 KB
6. Performant Datetimes With Numpy.srt10.3 KB
2. Reading In Data With read_csv().srt10.3 KB
7. Strings.srt10.2 KB
6. Indexing Hierarchical DataFrames.srt10.2 KB
17. Boolean Masks And The .loc Indexer.srt10.2 KB
11. Solution.srt10.2 KB
9. Other Visualization Options.srt10.2 KB
17. More MultiIndex Methods.srt10.1 KB
24. Solution.srt10.1 KB
39. Adding DataFrame Columns.srt9.9 KB
4. Reading Excel.srt9.8 KB
24. List Comprehensions.srt9.8 KB
9. More Split Parameters.srt9.8 KB
12. Solution.srt9.8 KB
12. Fancy Indexing With lookup().srt9.7 KB
18. Solution.srt9.7 KB
14. DataFrame Extraction by Position.srt9.7 KB
32. Solution III - Z-scores.srt9.6 KB
folks.xlsx9.5 KB
18. Resampling Timeseries.srt9.4 KB
18. GroupBy Transformations.srt9.3 KB
17. Many-to-Many Joins.srt9.3 KB
13. Descriptive Statistics.srt9.2 KB
14. DateTimeIndex Attribute Accessors.srt9.1 KB
22. Series Arithmetics And fill_value().srt9.1 KB
33. Skill Challenge.srt1.7 KB
15. Text Replacement.srt9.1 KB
5. Enforcing Unique Indices.srt9.1 KB
25. BONUS - dropna() With Subset.srt9.0 KB
35. Another Skill Challenge.srt2.3 KB
9. BONUS - Sampling With Replacement Or Weights.srt8.9 KB
26. Function Arguments Positional vs Keyword.srt8.9 KB
37. The SettingWithCopy Warning.srt8.9 KB
23. The rename() Method.srt8.9 KB
3. Concatenating DataFrames.srt8.8 KB
10. Solution.srt8.7 KB
29. DataFrame Sorting.srt8.7 KB
4. The Duplicated Index Issue.srt8.7 KB
12. Changing The Index.srt8.7 KB
3. String Methods In Python.srt8.7 KB
8. Replicating Pivot Tables With GroupBy.srt2.9 KB
518 bytes
23. Solution.mp472.4 MB
13. Extracting By Index Position.srt8.6 KB
10. Lists vs. Strings.srt8.6 KB
7. BONUS The Problem With Average Percentage.srt8.5 KB
4. Arithmetic And Augmented Assignment Operators.srt8.5 KB
26. Dropping And Filling DataFrame NAs.srt8.5 KB
19. BONUS - There's Also apply().srt8.5 KB
9. Skill Challenge.srt1.5 KB
7. Index And RangeIndex.srt8.5 KB
3. Pivoting Data.srt8.5 KB
8. Methods.srt8.4 KB
7. Combining Conditions.srt8.4 KB
21. Solution.srt8.3 KB
16. Shifting Dates With pd.DateOffset.srt8.3 KB
7. Strips And Whitespace.srt8.3 KB
25. Null Values In DataFrames.srt8.2 KB
13. Masking With String Methods.srt8.2 KB
15. mode() And value_counts().srt8.1 KB
13. Extracting From DataFrames By Label.srt8.1 KB
15. BONUS - Another Way.srt2.6 KB
6. BONUS Introduction To Pickling.srt8.0 KB
29. Solution.srt8.0 KB
14. Accessing Elements By Label.srt7.9 KB
17. Skill Challenge.srt1.5 KB
16. Named Aggregations.srt7.9 KB
21. While Loops.srt7.9 KB
9. Containers I Lists.srt7.8 KB
36. Setting DataFrame Values.srt7.8 KB
19. The Flipside unstack().srt7.7 KB
6. Finding Characters And Words.srt7.6 KB
1. Installing Anaconda And Python - Windows.srt7.6 KB
13. Sorting By Index Or Column.srt7.6 KB
15. Removing MultiIndex Levels.srt7.6 KB
16. MultiIndex sort_index().srt7.6 KB
10. Solution.srt7.5 KB
16. BONUS - The get_loc() Method.srt7.4 KB
36. Solution.srt7.4 KB
27. Part III Removing Units From Values.srt7.3 KB
20. The astype() Method.srt7.3 KB
17. BONUS Timedeltas And Absolute Time.srt7.2 KB
28. Importing Modules.srt7.1 KB
32. DataFrame nlargest() And nsmallest().srt7.1 KB
43. Solution.srt7.1 KB
18. Reshaping With stack().srt7.1 KB
5. Cloud vs Local.srt7.0 KB
28. Skill Challenge.srt1.8 KB
12. Slicing Substrings.srt7.0 KB
6. The pivot_table().srt7.0 KB
30. Using Series between() With DataFrames.srt7.0 KB
27. Lambdas.srt6.9 KB
9. Cross Sections With xs().srt6.9 KB
15. Creating Date Ranges.srt6.9 KB
13. Adding Another Level.srt6.8 KB
12. The merge() Method.srt6.8 KB
4. What’s In The Data.srt6.8 KB
19. For Loops.srt6.8 KB
23. Solution.srt6.7 KB
34. Skill Challenge.srt2.6 KB
10. BONUS - How Are Random Numbers Generated.srt6.7 KB
14. Containers IV Dictionaries.srt6.7 KB
5. What About Aggregates.srt6.7 KB
14. MultiIndex Grouping.srt6.6 KB
20. Removing Duplicates.srt6.6 KB
17. The filter() Method.srt6.6 KB
2. Introducing (Five) New Datasets.srt6.6 KB
4. Undoing Pivots.srt6.6 KB
21. Selection Recap.srt6.5 KB
34. Solution.srt6.5 KB
7. Some Cleanup Removing The Duplicated Index.srt6.5 KB
23. Solution.srt6.5 KB
16. idxmax() And idxmin().srt6.5 KB
13. Solution.srt6.4 KB
20. The range() Immutable Sequence.srt6.4 KB
42. Skill Challenge.srt2.0 KB
4. Conditional Aggregates.srt6.4 KB
9. Date Parsing And DatetimeIndex.srt6.4 KB
14. Inner vs Outer Joins.srt6.3 KB
1. Section Intro.srt1.5 KB
6. Booleans And Comparison Operators.srt6.3 KB
11. Solution.srt6.3 KB
3. Simple Aggregations Review.srt6.2 KB
8. Series And Index Names.srt6.2 KB
18. Merging By Index.srt6.2 KB
21. Solution.srt6.2 KB
12. The head() And tail() Methods.srt6.2 KB
4. Unique Values And Series Monotonicity.srt6.2 KB
7. The Pandas Timestamp.srt6.1 KB
35. Solution.srt6.1 KB
2. Introducing New Data.srt6.0 KB
7. Pickles In Pandas.srt6.0 KB
14. Shuffling Levels.srt5.9 KB
5. From Datetime To String.srt5.9 KB
24. BONUS - A Sophisticated Alternative.srt5.9 KB
15. Single Value Access With .at And .iat.srt5.8 KB
9. Concat On Different Columns.srt5.9 KB
10. Skill Challenge.srt2.1 KB
22. Break And Continue.srt5.8 KB
24. Cumulative Operations.srt5.7 KB
23. Skill Challenge.srt1.9 KB
6134 bytes
1. Installing Anaconda And Python - Windows.mp471.3 MB
9. BONUS - Series groupby().srt5.7 KB
7. BONUS Another Approach.srt5.7 KB
20. Selecting With .get().srt5.7 KB
12. Containers II Tuples.srt5.7 KB
8. Our Dataset Brent Prices.srt5.7 KB
17. Sorting With sort_values().srt5.7 KB
11. Indexing Dates.srt5.6 KB
2. Reading JSON.srt5.6 KB
6. The groupby() Method.srt5.5 KB
3. Creating A DataFrame.srt5.5 KB
3. Series Sizing With .size, .shape, And len().srt5.4 KB
2. New Data New York City SAT Scores.srt5.4 KB
13. Handpicking Subgroups.srt5.4 KB
6. BONUS - Creating Multiple Indices With concat().srt5.3 KB
20. Skill Challenge.srt1.4 KB
8. Conditions As Variables.srt5.3 KB
7. Column Axis Concatenation.srt5.3 KB
5. The info() Method.srt5.3 KB
1. Section Intro.srt2.3 KB
23. BONUS - Another Way pop().srt5.2 KB
6. Hello, Python.srt5.2 KB
4. Even Better dateutil.srt5.2 KB
23. BONUS Calculating Variance And Standard Deviation.srt5.2 KB
13. The left_on And right_on Params.srt5.2 KB
12. Dropping And Filling NAs.srt5.1 KB
3. Index And RangeIndex.srt5.1 KB
5. The Split-Apply-Combine Pattern.srt5.1 KB
41. BONUS - How Are DataFrames Stored In Memory.srt5.1 KB
16. Membership Operators.srt5.0 KB
11. DataFrame Axes.srt5.0 KB
11. Solution.srt4.9 KB
8. BONUS - Use With pd.IndexSlice!.srt4.9 KB
5. MultiIndex From read_csv().srt4.8 KB
8. The sample() Method.srt4.8 KB
8. The Many Other Formats.srt4.8 KB
2. What Is A Series.srt4.8 KB
10. Skill Challenge.srt1.7 KB
11. Applying Multiple Functions.srt4.8 KB
10. Solution.srt4.7 KB
26. Series Iteration.srt4.7 KB
10. A Cool Shorcut read_csv() With parse_dates.srt4.7 KB
8. Customizing Index To Group Mappings.srt4.6 KB
4. Creating A MultiIndex.srt4.6 KB
6. Reading In Nutrition Data.srt4.6 KB
2. Introducing A New Dataset.srt4.5 KB
16. Using Dot Notation.srt4.5 KB
3. Installing Anaconda And Python - Linux.srt4.5 KB
7. The DataFrameGroupBy Object.srt4.4 KB
18. Truth Value Of Non-booleans.srt4.4 KB
15. Left vs Right Joins.srt4.4 KB
18. Solution.srt4.4 KB
18. Extracting By Position With .iloc.srt4.4 KB
16. 15. BONUS - Please Avoid Sorting Like This.srt4.3 KB
23. Zipping Iterables.srt4.3 KB
25. Pairwise Differences With diff().srt4.3 KB
4. Vectorized String Operations In Pandas.srt4.3 KB
3. Quick Review Indexing With Boolean Masks.srt4.3 KB
20. BONUS What's The Point Of re.compile().srt4.2 KB
31. Solution II - Mean, Median, And Standard Deviation.srt4.1 KB
12. Iterating Through Groups.srt4.1 KB
drinks (1).csv4.1 KB
drinks (2).csv4.1 KB
drinks.csv4.1 KB
19. Sorting With sort_index().srt4.0 KB
15. BONUS The add_prefix() And add_suffix() Methods.srt4.0 KB
22. BONUS - What About Panels.srt4.0 KB
1. Section Intro.srt1.5 KB
6. BONUS What Is dtype('o'), Really.srt4.0 KB
13. Solution.srt3.9 KB
10. BONUS Data Ink And Chartjunk.srt3.9 KB
19. More Cleanup Going Numeric.srt3.9 KB
2. New Data Game Sales.srt3.8 KB
3. Anaconda.srt3.8 KB
2. Our Data Boston Marathon Runners.srt3.7 KB
11. Solution.srt3.7 KB
5. Case Operations.srt3.6 KB
10. MultiIndex Pivot Tables.srt3.6 KB
11. Another Solution.srt3.6 KB
2. The Art Of Data Visualization.srt3.6 KB
22. BONUS - Removing Columns.srt3.5 KB
9. Skill Challenge.srt3.5 KB
21. Removing DataFrame Rows.srt3.4 KB
3. Parameters vs Arguments.srt3.3 KB
18. nlargest() And nsmallest().srt3.3 KB
10. Skill Challenge.srt1.2 KB
8. The Other Side notnull() And notna().srt3.2 KB
21. An Easier Way transpose().srt3.2 KB
29. Skill Challenge.srt3.2 KB
19. The join() Method.srt3.2 KB
1. Section Intro.srt3.1 KB
2. Data Types.srt3.0 KB
liberal_arts.csv2.9 KB
2. Installing Anaconda And Python - Mac.srt2.6 KB
1. Section Intro.srt2.3 KB
1. Section Intro.srt2.3 KB
11. Skill Challenge.srt2.0 KB
22. Skill Challenge.srt1.9 KB
22. Skill Challenge.srt1.7 KB
1. Section Intro.srt1.7 KB
12. Skill Challenge.srt1.6 KB
1. Section Intro.srt1.6 KB
1. Section Intro.srt1.5 KB
eng.csv1.5 KB
20. Skill Challenge.srt1.5 KB
portfolio.zip1.4 KB
10. Skill Challenge.srt1.3 KB
12. Skill Challenge.srt1.3 KB
1. Section Intro.srt1.1 KB
ivies.csv548 bytes
7251.9 KB
28. Transforming With update(), apply() And map().mp469.9 MB
883.4 KB
33. Element-wise Operations With applymap().mp468.5 MB
9503.7 KB
4. More Approaches To Boolean Masking.mp468.4 MB
10596.8 KB
31. Same-shape Transforms.mp467.0 MB
1118.3 KB
22. Part I Collecting The Units.mp466.8 MB
12180.3 KB
14. BONUS Parsing Indicators With get_dummies().mp466.3 MB
13717.6 KB
14. Sorting vs. Reordering.mp465.2 MB
14775.1 KB
17. More Regex Concepts.mp465.2 MB
15854.2 KB
9. Other Visualization Options.mp463.6 MB
16363.2 KB
18. How To Approach Regex.mp463.5 MB
17486.7 KB
8. Scatter Plots.mp463.4 MB
18627.6 KB
31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp463.0 MB
1917.1 KB
3. The Preliminaries Of matplotlib.mp462.9 MB
20120.1 KB
7. NumPy.mp462.2 MB
21826.1 KB
19. Identifying Dupes.mp460.9 MB
22121.4 KB
11. Solution.mp459.5 MB
23542.5 KB
32. More Flexibility With apply().mp459.4 MB
24636.9 KB
7. Indexing Ranges And Slices.mp459.1 MB
25915.3 KB
20. BONUS Creating MultiLevel Columns Manually.mp458.7 MB
26281.0 KB
5. Enforcing Unique Indices.mp458.4 MB
27625.6 KB
25. Defining Functions.mp457.8 MB
28233.7 KB
27. BONUS - Methods And Axes With fillna().mp457.4 MB
29634.5 KB
26. Part II Merging Units With Column Names.mp457.3 MB
30734.6 KB
16. One-to-One and One-to-Many Joins.mp457.0 MB
311014.0 KB
4. Reading Excel.mp455.7 MB
32283.1 KB
17. Many-to-Many Joins.mp455.6 MB
33391.3 KB
27. Filtering filter(), where(), And mask().mp455.1 MB
34970.8 KB
6. Pie Plots.mp454.9 MB
35116.5 KB
12. Solution.mp454.2 MB
36768.6 KB
4. Line Graphs.mp454.2 MB
37843.7 KB
13. Containers III Sets.mp453.0 MB
3833.1 KB
3. Parsing Dates From Text.mp452.8 MB
39187.5 KB
2. Reading In Data With read_csv().mp452.8 MB
40194.6 KB
4. The Duplicated Index Issue.mp451.3 MB
41693.8 KB
6. BONUS - XOR and Complement Binary Ops.mp450.5 MB
42538.5 KB
12. Changing The Index.mp450.4 MB
43638.1 KB
5. Bar Charts.mp450.1 MB
44881.9 KB
40. Adding Rows To DataFrames.mp449.9 MB
4597.4 KB
29. DataFrame Sorting.mp449.4 MB
46591.0 KB
19. Upsampling And Interpolation.mp449.4 MB
47611.9 KB
38. View vs Copy.mp449.3 MB
48712.5 KB
24. Solution.mp449.2 MB
49840.1 KB
26. Dropping And Filling DataFrame NAs.mp449.0 MB
501020.3 KB
32. Solution III - Z-scores.mp448.2 MB
51819.2 KB
4. Jupyter Notebooks.mp448.0 MB
521007.5 KB
14. DataFrame Extraction by Position.mp446.7 MB
53296.5 KB
8. String Splitting And Concatenation.mp446.3 MB
54666.2 KB
12. Fancy Indexing With lookup().mp446.2 MB
55809.1 KB
21. Solution.mp446.1 MB
56945.2 KB
19. The Flipside unstack().mp445.9 MB
5755.3 KB
2. What Is A DataFrame.mp445.9 MB
58147.3 KB
10. Solution.mp445.8 MB
59185.9 KB
7. Histograms.mp445.8 MB
60224.5 KB
7. Combining Conditions.mp445.6 MB
61442.2 KB
18. Solution.mp445.2 MB
62826.1 KB
13. Sorting By Index Or Column.mp445.0 MB
631001.2 KB
11. Solution.mp444.8 MB
64203.0 KB
21. DataFrame replace() + A Glimpse At Regex.mp444.3 MB
65738.7 KB
15. Fine-tuned Aggregates.mp444.1 MB
66881.8 KB
36. Setting DataFrame Values.mp443.6 MB
67459.3 KB
21. BONUS Rolling Windows.mp443.5 MB
68521.2 KB
10. BONUS - How Are Random Numbers Generated.mp442.9 MB
6960.1 KB
5. Ints And Floats.mp442.8 MB
70203.6 KB
29. Solution.mp442.5 MB
71522.8 KB
28. Filtering in 2D.mp442.3 MB
72668.5 KB
34. Solution.mp442.3 MB
73764.6 KB
25. Null Values In DataFrames.mp442.2 MB
74860.4 KB
3. Concatenating DataFrames.mp442.1 MB
75896.5 KB
3. Pivoting Data.mp441.9 MB
76101.8 KB
15. Text Replacement.mp441.8 MB
77225.7 KB
17. Controlling Flow if, else, And elif.mp441.7 MB
78343.9 KB
19. BONUS - There's Also apply().mp441.2 MB
79837.8 KB
2. Introducing (Five) New Datasets.mp440.6 MB
80412.6 KB
9. BONUS - Sampling With Replacement Or Weights.mp440.5 MB
81534.2 KB
2. The Python datetime Module.mp440.3 MB
82726.5 KB
22. Series Arithmetics And fill_value().mp440.2 MB
83821.7 KB
9. More Split Parameters.mp440.1 MB
84939.0 KB
24. DataFrame dropna().mp440.1 MB
85942.4 KB
10. Solution.mp440.0 MB
86985.1 KB
11. 2d Indexing.mp440.0 MB
871007.0 KB
37. The SettingWithCopy Warning.mp439.8 MB
88194.4 KB
6. Indexing Hierarchical DataFrames.mp439.4 MB
89622.0 KB
3. Variables.mp439.1 MB
90889.8 KB
18. GroupBy Transformations.mp438.8 MB
91210.0 KB
18. Resampling Timeseries.mp438.5 MB
92476.9 KB
9. Concat On Different Columns.mp438.2 MB
93812.0 KB
14. DateTimeIndex Attribute Accessors.mp438.1 MB
94872.8 KB
18. Merging By Index.mp438.1 MB
95874.7 KB
5. Binary Operators With Booleans.mp437.9 MB
9659.6 KB
17. More MultiIndex Methods.mp437.9 MB
9782.7 KB
15. Removing MultiIndex Levels.mp437.7 MB
98306.9 KB
19. BONUS Using Callables With .loc And .iloc.mp437.1 MB
99881.8 KB
30. Calculating Aggregates With agg().mp437.1 MB
100942.4 KB
13. Masking With String Methods.mp436.9 MB
10194.5 KB
36. Solution.mp436.9 MB
102144.5 KB
6. Accessing And Counting NAs.mp436.8 MB
103213.6 KB
13. Solution.mp436.6 MB
104366.1 KB
20. What About asfreq().mp436.6 MB
105401.7 KB
15. Creating Date Ranges.mp436.5 MB
106481.8 KB
16. Named Aggregations.mp436.5 MB
107524.5 KB
39. Adding DataFrame Columns.mp436.5 MB
108538.8 KB
15. Dictionary Keys And Values.mp436.3 MB
109697.1 KB
16. Shifting Dates With pd.DateOffset.mp436.2 MB
110799.0 KB
7. BONUS The Problem With Average Percentage.mp436.2 MB
111864.9 KB
13. Extracting From DataFrames By Label.mp436.0 MB
1121015.0 KB
27. Part III Removing Units From Values.mp435.6 MB
113384.2 KB
7. Some Cleanup Removing The Duplicated Index.mp435.6 MB
114386.2 KB
16. MultiIndex sort_index().mp435.6 MB
115390.8 KB
12. The merge() Method.mp435.4 MB
116630.3 KB
32. DataFrame nlargest() And nsmallest().mp435.4 MB
117656.1 KB
6. Performant Datetimes With Numpy.mp435.3 MB
118687.0 KB
30. Using Series between() With DataFrames.mp435.0 MB
11935.3 KB
12. The Anatomy Of A MultiIndex Object.mp434.8 MB
120155.4 KB
5. What About Aggregates.mp434.3 MB
121764.6 KB
28. Importing Modules.mp434.2 MB
122868.2 KB
13. Descriptive Statistics.mp433.7 MB
123337.5 KB
6. The pivot_table().mp433.7 MB
124343.4 KB
13. Adding Another Level.mp433.6 MB
125420.0 KB
24. BONUS - A Sophisticated Alternative.mp433.2 MB
126851.9 KB
7. Index And RangeIndex.mp433.2 MB
127864.6 KB
9. Cross Sections With xs().mp433.2 MB
128866.5 KB
11. List Methods And Functions.mp433.0 MB
12914.2 KB
6. Hello, Python.mp432.8 MB
130215.9 KB
10. BONUS Data Ink And Chartjunk.mp432.3 MB
131678.3 KB
13. The left_on And right_on Params.mp432.2 MB
132820.2 KB
7. Strings.mp432.1 MB
133894.2 KB
43. Solution.mp431.9 MB
13460.3 KB
24. List Comprehensions.mp431.8 MB
135225.2 KB
15. mode() And value_counts().mp431.7 MB
136271.9 KB
7. Strips And Whitespace.mp431.7 MB
137275.6 KB
6. BONUS Introduction To Pickling.mp431.7 MB
138296.2 KB
3. Installing Anaconda And Python - Linux.mp431.0 MB
13948.7 KB
18. Reshaping With stack().mp430.6 MB
140442.8 KB
20. Selecting With .get().mp430.5 MB
141462.4 KB
26. Function Arguments Positional vs Keyword.mp430.4 MB
142568.7 KB
20. Removing Duplicates.mp429.8 MB
143184.9 KB
9. Containers I Lists.mp429.5 MB
144526.3 KB
17. Boolean Masks And The .loc Indexer.mp429.5 MB
145543.7 KB
8. Our Dataset Brent Prices.mp429.4 MB
146587.4 KB
25. BONUS - dropna() With Subset.mp429.3 MB
147759.3 KB
21. While Loops.mp429.2 MB
148786.5 KB
13. Extracting By Index Position.mp429.1 MB
149966.5 KB
3. Simple Aggregations Review.mp429.0 MB
1501005.6 KB
3. String Methods In Python.mp428.8 MB
151233.8 KB
6. BONUS - Creating Multiple Indices With concat().mp428.5 MB
152561.4 KB
17. BONUS Timedeltas And Absolute Time.mp428.4 MB
153652.0 KB
21. Selection Recap.mp428.2 MB
154829.2 KB
8. The Many Other Formats.mp427.9 MB
15591.0 KB
4. Undoing Pivots.mp427.9 MB
156111.5 KB
22. BONUS - What About Panels.mp427.9 MB
157111.9 KB
5. MultiIndex From read_csv().mp427.7 MB
158312.2 KB
11. Solution.mp427.6 MB
159416.3 KB
23. The rename() Method.mp427.6 MB
160420.7 KB
10. Lists vs. Strings.mp427.6 MB
161447.4 KB
4. Arithmetic And Augmented Assignment Operators.mp427.5 MB
162556.5 KB
6. Reading In Nutrition Data.mp427.3 MB
163731.0 KB
14. Inner vs Outer Joins.mp427.1 MB
164908.5 KB
7. Column Axis Concatenation.mp427.1 MB
165928.2 KB
14. Accessing Elements By Label.mp427.1 MB
166960.0 KB
3. Index And RangeIndex.mp426.9 MB
167133.2 KB
2. New Data New York City SAT Scores.mp426.8 MB
168239.1 KB
11. Indexing Dates.mp426.6 MB
169378.4 KB
14. MultiIndex Grouping.mp426.5 MB
170468.1 KB
5. Cloud vs Local.mp426.5 MB
171481.8 KB
35. Solution.mp426.5 MB
172546.7 KB
1. Section Intro.mp426.4 MB
173590.1 KB
15. Single Value Access With .at And .iat.mp426.3 MB
174677.2 KB
17. The filter() Method.mp426.1 MB
175902.5 KB
18. Solution.mp425.8 MB
176244.9 KB
6. Finding Characters And Words.mp425.7 MB
177275.6 KB
8. Methods.mp425.3 MB
178688.8 KB
20. The astype() Method.mp425.2 MB
179846.1 KB
16. BONUS - The get_loc() Method.mp425.1 MB
180955.8 KB
9. Adding Margins.mp424.6 MB
181423.4 KB
9. Date Parsing And DatetimeIndex.mp424.5 MB
182483.2 KB
21. Solution.mp424.5 MB
183500.7 KB
4. Conditional Aggregates.mp424.5 MB
184502.0 KB
14. Shuffling Levels.mp424.3 MB
185697.7 KB
12. Slicing Substrings.mp424.2 MB
186831.4 KB
7. The Pandas Timestamp.mp424.0 MB
187978.6 KB
4. Even Better dateutil.mp423.9 MB
188152.3 KB
1. Section Intro.mp423.8 MB
189176.6 KB
20. The range() Immutable Sequence.mp423.7 MB
190288.6 KB
13. Handpicking Subgroups.mp423.6 MB
191361.4 KB
2. Our Data Boston Marathon Runners.mp423.6 MB
192435.4 KB
23. Solution.mp423.4 MB
193620.7 KB
3. Quick Review Indexing With Boolean Masks.mp423.3 MB
194688.3 KB
11. DataFrame Axes.mp423.3 MB
195709.2 KB
3. Series Sizing With .size, .shape, And len().mp423.3 MB
196760.4 KB
27. Lambdas.mp423.2 MB
197806.4 KB
12. The head() And tail() Methods.mp423.0 MB
19822.6 KB
7. Pickles In Pandas.mp422.9 MB
19972.1 KB
23. Solution.mp422.9 MB
200105.8 KB
10. Solution.mp422.9 MB
201107.0 KB
19. The join() Method.mp422.9 MB
202129.6 KB
14. Containers IV Dictionaries.mp422.7 MB
203271.2 KB
8. The sample() Method.mp422.6 MB
204403.0 KB
5. The Split-Apply-Combine Pattern.mp422.5 MB
205499.7 KB
3. Creating A DataFrame.mp422.4 MB
206593.5 KB
5. From Datetime To String.mp422.4 MB
207648.5 KB
1. Section Intro.mp422.3 MB
208688.6 KB
2. Introducing New Data.mp422.1 MB
209915.5 KB
16. idxmax() And idxmin().mp422.0 MB
2101023.8 KB
11. Solution.mp422.0 MB
21131.4 KB
6. Booleans And Comparison Operators.mp421.9 MB
212126.6 KB
41. BONUS - How Are DataFrames Stored In Memory.mp421.7 MB
213277.1 KB
6. The groupby() Method.mp421.6 MB
214450.9 KB
12. Dropping And Filling NAs.mp421.5 MB
215493.2 KB
7. BONUS Another Approach.mp421.3 MB
216689.7 KB
1. Section Intro.mp421.1 MB
217894.0 KB
12. Iterating Through Groups.mp421.0 MB
218989.5 KB
9. BONUS - Series groupby().mp420.8 MB
219206.0 KB
3. Anaconda.mp420.7 MB
220299.5 KB
19. For Loops.mp420.6 MB
221437.7 KB
8. Customizing Index To Group Mappings.mp420.5 MB
222535.3 KB
31. Solution II - Mean, Median, And Standard Deviation.mp420.5 MB
223537.8 KB
4. What’s In The Data.mp420.4 MB
224603.5 KB
15. Left vs Right Joins.mp420.3 MB
225750.3 KB
4. Creating A MultiIndex.mp420.1 MB
226874.7 KB
12. Containers II Tuples.mp420.0 MB
227992.8 KB
8. Conditions As Variables.mp419.9 MB
228105.7 KB
7. The DataFrameGroupBy Object.mp419.8 MB
229191.6 KB
21. Removing DataFrame Rows.mp419.8 MB
230222.4 KB
2. Reading JSON.mp419.7 MB
231265.6 KB
17. Sorting With sort_values().mp419.6 MB
232374.4 KB
16. Membership Operators.mp419.3 MB
233741.5 KB
22. Break And Continue.mp419.1 MB
234881.9 KB
8. Series And Index Names.mp419.1 MB
235899.7 KB
23. BONUS - Another Way pop().mp419.1 MB
236956.7 KB
10. MultiIndex Pivot Tables.mp419.0 MB
237973.9 KB
5. The info() Method.mp419.0 MB
238983.8 KB
19. More Cleanup Going Numeric.mp418.6 MB
239383.1 KB
21. An Easier Way transpose().mp418.6 MB
240414.0 KB
4. Vectorized String Operations In Pandas.mp418.4 MB
241579.3 KB
11. Applying Multiple Functions.mp418.3 MB
242685.2 KB
20. BONUS What's The Point Of re.compile().mp418.3 MB
243710.6 KB
2. Introducing A New Dataset.mp418.3 MB
244717.6 KB
24. Cumulative Operations.mp417.9 MB
24556.7 KB
2. Pandas Is Not Single.mp417.8 MB
246199.4 KB
4. Unique Values And Series Monotonicity.mp417.8 MB
247208.4 KB
10. A Cool Shorcut read_csv() With parse_dates.mp417.6 MB
248395.7 KB
23. BONUS Calculating Variance And Standard Deviation.mp417.4 MB
249651.1 KB
23. Zipping Iterables.mp417.2 MB
250833.9 KB
2. Installing Anaconda And Python - Mac.mp417.1 MB
251877.0 KB
13. Solution.mp417.1 MB
252916.9 KB
1. Section Intro.mp417.1 MB
253926.7 KB
16. 15. BONUS - Please Avoid Sorting Like This.mp417.1 MB
254947.8 KB
8. BONUS - Use With pd.IndexSlice!.mp417.0 MB
25533.4 KB
1. Section Intro.mp416.7 MB
256325.1 KB
15. BONUS The add_prefix() And add_suffix() Methods.mp416.5 MB
257526.2 KB
22. BONUS - Removing Columns.mp416.2 MB
258828.4 KB
26. Series Iteration.mp416.1 MB
259950.2 KB
18. Truth Value Of Non-booleans.mp415.9 MB
26079.8 KB
19. Sorting With sort_index().mp415.3 MB
261714.6 KB
2. New Data Game Sales.mp414.9 MB
262108.4 KB
30. Solution I - Reading Data.mp414.6 MB
263458.0 KB
8. The append() Method A Special Case Of concat().mp414.5 MB
264527.6 KB
1. Course Structure.mp414.1 MB
265964.3 KB
5. Case Operations.mp414.0 MB
266995.9 KB
11. Solution.mp413.4 MB
267567.3 KB
16. Using Dot Notation.mp413.2 MB
268768.6 KB
2. The Art Of Data Visualization.mp413.0 MB
2691008.7 KB
15. BONUS - Another Way.mp412.9 MB
27055.1 KB
1. Section Intro.mp412.9 MB
27168.2 KB
25. Pairwise Differences With diff().mp412.8 MB
272216.6 KB
2. What Is A Series.mp412.5 MB
273472.2 KB
8. Replicating Pivot Tables With GroupBy.mp412.5 MB
274507.7 KB
18. nlargest() And nsmallest().mp412.2 MB
275853.7 KB
9. Skill Challenge.mp411.7 MB
276302.0 KB
9. BONUS Booleans Are Literally Numbers In Python.mp411.6 MB
277390.4 KB
18. Extracting By Position With .iloc.mp411.6 MB
278395.1 KB
11. Another Solution.mp411.2 MB
279779.1 KB
8. The Other Side notnull() And notna().mp411.0 MB
280985.5 KB
1. Section Intro.mp410.8 MB
281193.9 KB
1. Section Intro.mp410.3 MB
282689.8 KB
29. Skill Challenge.mp410.2 MB
283822.1 KB
2. Data Types.mp410.2 MB
284861.6 KB
6. BONUS What Is dtype('o'), Really.mp410.1 MB
285922.4 KB
21. Solution.mp49.9 MB
28692.7 KB
14. The describe() Method.mp49.7 MB
287303.4 KB
1. Section Intro.mp48.9 MB
288119.9 KB
34. Skill Challenge.mp48.8 MB
289249.0 KB
3. Parameters vs Arguments.mp48.1 MB
290948.4 KB
23. Skill Challenge.mp48.0 MB
2911017.4 KB
1. Section Intro.mp48.0 MB
29250.2 KB
9. Skill Challenge.mp47.7 MB
293292.9 KB
11. Skill Challenge.mp47.5 MB
294491.0 KB
1. Section Intro.mp46.9 MB
29572.2 KB
35. Another Skill Challenge.mp46.8 MB
296210.5 KB
22. Skill Challenge.mp46.4 MB
297635.9 KB
5. The .dtype Attribute.mp46.4 MB
298647.2 KB
5. The count() Method.mp46.0 MB
299990.6 KB
10. Skill Challenge.mp46.0 MB
30011.7 KB
12. Skill Challenge.mp45.5 MB
301533.4 KB
22. Skill Challenge.mp45.4 MB
302591.4 KB
28. Skill Challenge.mp45.3 MB
303720.0 KB
1. Section Intro.mp45.2 MB
304811.2 KB
42. Skill Challenge.mp45.0 MB
305987.9 KB
22. Skill Challenge.mp44.7 MB
306357.8 KB
17. Skill Challenge.mp44.5 MB
307536.6 KB
nutrition.csv4.4 MB
308583.9 KB
33. Skill Challenge.mp44.3 MB
309710.9 KB
17. Skill Challenge.mp44.1 MB
310916.5 KB
20. Skill Challenge.mp44.1 MB
311969.0 KB
10. Skill Challenge.mp44.0 MB
312977.2 KB
9. Skill Challenge.mp44.0 MB
31338.7 KB
20. Skill Challenge.mp43.8 MB
314192.3 KB
12. Skill Challenge.mp43.8 MB
315215.9 KB
10. Skill Challenge.mp43.8 MB
316222.9 KB
10. Skill Challenge.mp43.2 MB
317788.7 KB
10. Skill Challenge.mp43.2 MB
318799.5 KB
20. Skill Challenge.mp43.2 MB
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