首页
磁力链接怎么用
한국어
English
日本語
简体中文
繁體中文
[FreeCourseSite.com] Udemy - The Ultimate Pandas Bootcamp Advanced Python Data Analysis
文件类型
收录时间
最后活跃
资源热度
文件大小
文件数量
视频
2022-4-25 12:36
2024-9-9 17:46
162
9.62 GB
319
磁力链接
magnet:?xt=urn:btih:a0c4d102befdc70c9df1368c0ee9f671ad3da227
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOmEwYzRkMTAyYmVmZGM3MGM5ZGYxMzY4YzBlZTlmNjcxYWQzZGEyMjdaWg==
二维码链接
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接,内容跟本站无关!
相关链接
FreeCourseSite
com
Udemy
-
The
Ultimate
Pandas
Bootcamp
Advanced
Python
Data
Analysis
文件列表
1. Introduction/1. Course Structure.mp4
14.06MB
1. Introduction/2. Pandas Is Not Single.mp4
17.81MB
1. Introduction/3. Anaconda.mp4
20.71MB
1. Introduction/4. Jupyter Notebooks.mp4
48.02MB
1. Introduction/5. Cloud vs Local.mp4
26.53MB
1. Introduction/6. Hello, Python.mp4
32.79MB
1. Introduction/7. NumPy.mp4
62.19MB
10. Handling Date And Time/1. Section Intro.mp4
22.33MB
10. Handling Date And Time/10. A Cool Shorcut read_csv() With parse_dates.mp4
17.61MB
10. Handling Date And Time/11. Indexing Dates.mp4
26.63MB
10. Handling Date And Time/12. Skill Challenge.mp4
3.79MB
10. Handling Date And Time/13. Solution.mp4
17.1MB
10. Handling Date And Time/14. DateTimeIndex Attribute Accessors.mp4
38.15MB
10. Handling Date And Time/15. Creating Date Ranges.mp4
36.53MB
10. Handling Date And Time/16. Shifting Dates With pd.DateOffset.mp4
36.22MB
10. Handling Date And Time/17. BONUS Timedeltas And Absolute Time.mp4
28.36MB
10. Handling Date And Time/18. Resampling Timeseries.mp4
38.53MB
10. Handling Date And Time/19. Upsampling And Interpolation.mp4
49.4MB
10. Handling Date And Time/2. The Python datetime Module.mp4
40.29MB
10. Handling Date And Time/20. What About asfreq().mp4
36.61MB
10. Handling Date And Time/21. BONUS Rolling Windows.mp4
43.49MB
10. Handling Date And Time/22. Skill Challenge.mp4
4.65MB
10. Handling Date And Time/23. Solution.mp4
22.9MB
10. Handling Date And Time/3. Parsing Dates From Text.mp4
52.82MB
10. Handling Date And Time/4. Even Better dateutil.mp4
23.85MB
10. Handling Date And Time/5. From Datetime To String.mp4
22.37MB
10. Handling Date And Time/6. Performant Datetimes With Numpy.mp4
35.33MB
10. Handling Date And Time/7. The Pandas Timestamp.mp4
24.04MB
10. Handling Date And Time/8. Our Dataset Brent Prices.mp4
29.43MB
10. Handling Date And Time/9. Date Parsing And DatetimeIndex.mp4
24.53MB
11. Regex And Text Manipulation/1. Section Intro.mp4
16.68MB
11. Regex And Text Manipulation/10. Skill Challenge.mp4
3.23MB
11. Regex And Text Manipulation/11. Solution.mp4
21.97MB
11. Regex And Text Manipulation/12. Slicing Substrings.mp4
24.19MB
11. Regex And Text Manipulation/13. Masking With String Methods.mp4
36.91MB
11. Regex And Text Manipulation/14. BONUS Parsing Indicators With get_dummies().mp4
66.3MB
11. Regex And Text Manipulation/15. Text Replacement.mp4
41.78MB
11. Regex And Text Manipulation/16. Introduction To Regular Expressions.mp4
75.02MB
11. Regex And Text Manipulation/17. More Regex Concepts.mp4
65.17MB
11. Regex And Text Manipulation/18. How To Approach Regex.mp4
63.52MB
11. Regex And Text Manipulation/19. Is This A Valid Email.mp4
80.08MB
11. Regex And Text Manipulation/2. Our Data Boston Marathon Runners.mp4
23.57MB
11. Regex And Text Manipulation/20. BONUS What's The Point Of re.compile().mp4
18.31MB
11. Regex And Text Manipulation/21. Pandas str contains(), split() And replace() With Regex.mp4
76.29MB
11. Regex And Text Manipulation/22. Skill Challenge.mp4
5.42MB
11. Regex And Text Manipulation/23. Solution.mp4
72.37MB
11. Regex And Text Manipulation/3. String Methods In Python.mp4
28.77MB
11. Regex And Text Manipulation/4. Vectorized String Operations In Pandas.mp4
18.43MB
11. Regex And Text Manipulation/5. Case Operations.mp4
14.03MB
11. Regex And Text Manipulation/6. Finding Characters And Words.mp4
25.73MB
11. Regex And Text Manipulation/7. Strips And Whitespace.mp4
31.73MB
11. Regex And Text Manipulation/8. String Splitting And Concatenation.mp4
46.35MB
11. Regex And Text Manipulation/9. More Split Parameters.mp4
40.08MB
12. Visualizing Data/1. Section Intro.mp4
10.33MB
12. Visualizing Data/10. BONUS Data Ink And Chartjunk.mp4
32.34MB
12. Visualizing Data/11. Skill Challenge.mp4
7.52MB
12. Visualizing Data/12. Solution.mp4
54.25MB
12. Visualizing Data/2. The Art Of Data Visualization.mp4
13.01MB
12. Visualizing Data/3. The Preliminaries Of matplotlib.mp4
62.88MB
12. Visualizing Data/4. Line Graphs.mp4
54.18MB
12. Visualizing Data/5. Bar Charts.mp4
50.14MB
12. Visualizing Data/6. Pie Plots.mp4
54.89MB
12. Visualizing Data/7. Histograms.mp4
45.78MB
12. Visualizing Data/8. Scatter Plots.mp4
63.39MB
12. Visualizing Data/9. Other Visualization Options.mp4
63.65MB
13. Data Formats And IO/1. Section Intro.mp4
5.21MB
13. Data Formats And IO/10. Solution.mp4
45.82MB
13. Data Formats And IO/2. Reading JSON.mp4
19.74MB
13. Data Formats And IO/3. Reading HTML.mp4
103.72MB
13. Data Formats And IO/4. Reading Excel.mp4
55.72MB
13. Data Formats And IO/5. Creating Output The to_ Family Of Methods.mp4
74.01MB
13. Data Formats And IO/6. BONUS Introduction To Pickling.mp4
31.71MB
13. Data Formats And IO/7. Pickles In Pandas.mp4
22.93MB
13. Data Formats And IO/8. The Many Other Formats.mp4
27.91MB
13. Data Formats And IO/9. Skill Challenge.mp4
11.71MB
14. Appendix A - Rapid-Fire Python Fundamentals/1. Section Intro.mp4
8.88MB
14. Appendix A - Rapid-Fire Python Fundamentals/10. Lists vs. Strings.mp4
27.56MB
14. Appendix A - Rapid-Fire Python Fundamentals/11. List Methods And Functions.mp4
32.99MB
14. Appendix A - Rapid-Fire Python Fundamentals/12. Containers II Tuples.mp4
20.03MB
14. Appendix A - Rapid-Fire Python Fundamentals/13. Containers III Sets.mp4
52.97MB
14. Appendix A - Rapid-Fire Python Fundamentals/14. Containers IV Dictionaries.mp4
22.74MB
14. Appendix A - Rapid-Fire Python Fundamentals/15. Dictionary Keys And Values.mp4
36.32MB
14. Appendix A - Rapid-Fire Python Fundamentals/16. Membership Operators.mp4
19.28MB
14. Appendix A - Rapid-Fire Python Fundamentals/17. Controlling Flow if, else, And elif.mp4
41.66MB
14. Appendix A - Rapid-Fire Python Fundamentals/18. Truth Value Of Non-booleans.mp4
15.92MB
14. Appendix A - Rapid-Fire Python Fundamentals/19. For Loops.mp4
20.57MB
14. Appendix A - Rapid-Fire Python Fundamentals/2. Data Types.mp4
10.16MB
14. Appendix A - Rapid-Fire Python Fundamentals/20. The range() Immutable Sequence.mp4
23.72MB
14. Appendix A - Rapid-Fire Python Fundamentals/21. While Loops.mp4
29.23MB
14. Appendix A - Rapid-Fire Python Fundamentals/22. Break And Continue.mp4
19.14MB
14. Appendix A - Rapid-Fire Python Fundamentals/23. Zipping Iterables.mp4
17.19MB
14. Appendix A - Rapid-Fire Python Fundamentals/24. List Comprehensions.mp4
31.78MB
14. Appendix A - Rapid-Fire Python Fundamentals/25. Defining Functions.mp4
57.77MB
14. Appendix A - Rapid-Fire Python Fundamentals/26. Function Arguments Positional vs Keyword.mp4
30.44MB
14. Appendix A - Rapid-Fire Python Fundamentals/27. Lambdas.mp4
23.21MB
14. Appendix A - Rapid-Fire Python Fundamentals/28. Importing Modules.mp4
34.15MB
14. Appendix A - Rapid-Fire Python Fundamentals/3. Variables.mp4
39.13MB
14. Appendix A - Rapid-Fire Python Fundamentals/4. Arithmetic And Augmented Assignment Operators.mp4
27.46MB
14. Appendix A - Rapid-Fire Python Fundamentals/5. Ints And Floats.mp4
42.8MB
14. Appendix A - Rapid-Fire Python Fundamentals/6. Booleans And Comparison Operators.mp4
21.88MB
14. Appendix A - Rapid-Fire Python Fundamentals/7. Strings.mp4
32.13MB
14. Appendix A - Rapid-Fire Python Fundamentals/8. Methods.mp4
25.33MB
14. Appendix A - Rapid-Fire Python Fundamentals/9. Containers I Lists.mp4
29.49MB
15. Appendix B - Going Local Installation And Setup/1. Installing Anaconda And Python - Windows.mp4
71.34MB
15. Appendix B - Going Local Installation And Setup/2. Installing Anaconda And Python - Mac.mp4
17.14MB
15. Appendix B - Going Local Installation And Setup/3. Installing Anaconda And Python - Linux.mp4
30.95MB
2. Series At A Glance/1. Section Intro.mp4
6.93MB
2. Series At A Glance/10. Solution.mp4
22.9MB
2. Series At A Glance/11. Another Solution.mp4
11.24MB
2. Series At A Glance/12. The head() And tail() Methods.mp4
22.98MB
2. Series At A Glance/13. Extracting By Index Position.mp4
29.06MB
2. Series At A Glance/14. Accessing Elements By Label.mp4
27.06MB
2. Series At A Glance/15. BONUS The add_prefix() And add_suffix() Methods.mp4
16.49MB
2. Series At A Glance/16. Using Dot Notation.mp4
13.25MB
2. Series At A Glance/17. Boolean Masks And The .loc Indexer.mp4
29.47MB
2. Series At A Glance/18. Extracting By Position With .iloc.mp4
11.61MB
2. Series At A Glance/19. BONUS Using Callables With .loc And .iloc.mp4
37.14MB
2. Series At A Glance/2. What Is A Series.mp4
12.54MB
2. Series At A Glance/20. Selecting With .get().mp4
30.55MB
2. Series At A Glance/21. Selection Recap.mp4
28.19MB
2. Series At A Glance/22. Skill Challenge.mp4
6.38MB
2. Series At A Glance/23. Solution.mp4
23.39MB
2. Series At A Glance/3. Parameters vs Arguments.mp4
8.07MB
2. Series At A Glance/4. What’s In The Data.mp4
20.41MB
2. Series At A Glance/5. The .dtype Attribute.mp4
6.37MB
2. Series At A Glance/6. BONUS What Is dtype('o'), Really.mp4
10.1MB
2. Series At A Glance/7. Index And RangeIndex.mp4
33.16MB
2. Series At A Glance/8. Series And Index Names.mp4
19.12MB
2. Series At A Glance/9. Skill Challenge.mp4
7.71MB
3. Series Methods And Handling/1. Section Intro.mp4
12.93MB
3. Series Methods And Handling/10. Skill Challenge.mp4
4.05MB
3. Series Methods And Handling/11. Solution.mp4
13.45MB
3. Series Methods And Handling/12. Dropping And Filling NAs.mp4
21.52MB
3. Series Methods And Handling/13. Descriptive Statistics.mp4
33.67MB
3. Series Methods And Handling/14. The describe() Method.mp4
9.7MB
3. Series Methods And Handling/15. mode() And value_counts().mp4
31.73MB
3. Series Methods And Handling/16. idxmax() And idxmin().mp4
22MB
3. Series Methods And Handling/17. Sorting With sort_values().mp4
19.63MB
3. Series Methods And Handling/18. nlargest() And nsmallest().mp4
12.17MB
3. Series Methods And Handling/19. Sorting With sort_index().mp4
15.3MB
3. Series Methods And Handling/2. Reading In Data With read_csv().mp4
52.81MB
3. Series Methods And Handling/20. Skill Challenge.mp4
3.18MB
3. Series Methods And Handling/21. Solution.mp4
9.91MB
3. Series Methods And Handling/22. Series Arithmetics And fill_value().mp4
40.2MB
3. Series Methods And Handling/23. BONUS Calculating Variance And Standard Deviation.mp4
17.36MB
3. Series Methods And Handling/24. Cumulative Operations.mp4
17.94MB
3. Series Methods And Handling/25. Pairwise Differences With diff().mp4
12.79MB
3. Series Methods And Handling/26. Series Iteration.mp4
16.07MB
3. Series Methods And Handling/27. Filtering filter(), where(), And mask().mp4
55.05MB
3. Series Methods And Handling/28. Transforming With update(), apply() And map().mp4
69.92MB
3. Series Methods And Handling/29. Skill Challenge.mp4
10.2MB
3. Series Methods And Handling/3. Series Sizing With .size, .shape, And len().mp4
23.26MB
3. Series Methods And Handling/30. Solution I - Reading Data.mp4
14.55MB
3. Series Methods And Handling/31. Solution II - Mean, Median, And Standard Deviation.mp4
20.47MB
3. Series Methods And Handling/32. Solution III - Z-scores.mp4
48.2MB
3. Series Methods And Handling/4. Unique Values And Series Monotonicity.mp4
17.8MB
3. Series Methods And Handling/5. The count() Method.mp4
6.03MB
3. Series Methods And Handling/6. Accessing And Counting NAs.mp4
36.79MB
3. Series Methods And Handling/7. BONUS Another Approach.mp4
21.33MB
3. Series Methods And Handling/8. The Other Side notnull() And notna().mp4
11.04MB
3. Series Methods And Handling/9. BONUS Booleans Are Literally Numbers In Python.mp4
11.62MB
4. Working With DataFrames/1. Section Intro.mp4
10.81MB
4. Working With DataFrames/10. BONUS - How Are Random Numbers Generated.mp4
42.94MB
4. Working With DataFrames/11. DataFrame Axes.mp4
23.31MB
4. Working With DataFrames/12. Changing The Index.mp4
50.38MB
4. Working With DataFrames/13. Extracting From DataFrames By Label.mp4
36.01MB
4. Working With DataFrames/14. DataFrame Extraction by Position.mp4
46.71MB
4. Working With DataFrames/15. Single Value Access With .at And .iat.mp4
26.34MB
4. Working With DataFrames/16. BONUS - The get_loc() Method.mp4
25.07MB
4. Working With DataFrames/17. Skill Challenge.mp4
4.1MB
4. Working With DataFrames/18. Solution.mp4
45.19MB
4. Working With DataFrames/19. More Cleanup Going Numeric.mp4
18.63MB
4. Working With DataFrames/2. What Is A DataFrame.mp4
45.86MB
4. Working With DataFrames/20. The astype() Method.mp4
25.17MB
4. Working With DataFrames/21. DataFrame replace() + A Glimpse At Regex.mp4
44.28MB
4. Working With DataFrames/22. Part I Collecting The Units.mp4
66.82MB
4. Working With DataFrames/23. The rename() Method.mp4
27.59MB
4. Working With DataFrames/24. DataFrame dropna().mp4
40.08MB
4. Working With DataFrames/25. BONUS - dropna() With Subset.mp4
29.26MB
4. Working With DataFrames/26. Part II Merging Units With Column Names.mp4
57.28MB
4. Working With DataFrames/27. Part III Removing Units From Values.mp4
35.62MB
4. Working With DataFrames/28. Filtering in 2D.mp4
42.35MB
4. Working With DataFrames/29. DataFrame Sorting.mp4
49.42MB
4. Working With DataFrames/3. Creating A DataFrame.mp4
22.42MB
4. Working With DataFrames/30. Using Series between() With DataFrames.mp4
34.97MB
4. Working With DataFrames/31. BONUS - Min, Max and Idx[MinMax], And Good Foods.mp4
62.98MB
4. Working With DataFrames/32. DataFrame nlargest() And nsmallest().mp4
35.36MB
4. Working With DataFrames/33. Skill Challenge.mp4
4.31MB
4. Working With DataFrames/34. Solution.mp4
42.25MB
4. Working With DataFrames/35. Another Skill Challenge.mp4
6.79MB
4. Working With DataFrames/36. Solution.mp4
36.86MB
4. Working With DataFrames/4. BONUS - Four More Ways To Build DataFrames.mp4
73.23MB
4. Working With DataFrames/5. The info() Method.mp4
19.04MB
4. Working With DataFrames/6. Reading In Nutrition Data.mp4
27.29MB
4. Working With DataFrames/7. Some Cleanup Removing The Duplicated Index.mp4
35.62MB
4. Working With DataFrames/8. The sample() Method.mp4
22.61MB
4. Working With DataFrames/9. BONUS - Sampling With Replacement Or Weights.mp4
40.48MB
5. DataFrames In Depth/1. Section Intro.mp4
21.13MB
5. DataFrames In Depth/10. Solution.mp4
40.04MB
5. DataFrames In Depth/11. 2d Indexing.mp4
40.02MB
5. DataFrames In Depth/12. Fancy Indexing With lookup().mp4
46.21MB
5. DataFrames In Depth/13. Sorting By Index Or Column.mp4
45.02MB
5. DataFrames In Depth/14. Sorting vs. Reordering.mp4
65.24MB
5. DataFrames In Depth/15. BONUS - Another Way.mp4
12.95MB
5. DataFrames In Depth/16. 15. BONUS - Please Avoid Sorting Like This.mp4
17.07MB
5. DataFrames In Depth/17. Skill Challenge.mp4
4.48MB
5. DataFrames In Depth/18. Solution.mp4
25.76MB
5. DataFrames In Depth/19. Identifying Dupes.mp4
60.88MB
5. DataFrames In Depth/2. Introducing A New Dataset.mp4
18.3MB
5. DataFrames In Depth/20. Removing Duplicates.mp4
29.82MB
5. DataFrames In Depth/21. Removing DataFrame Rows.mp4
19.78MB
5. DataFrames In Depth/22. BONUS - Removing Columns.mp4
16.19MB
5. DataFrames In Depth/23. BONUS - Another Way pop().mp4
19.07MB
5. DataFrames In Depth/24. BONUS - A Sophisticated Alternative.mp4
33.17MB
5. DataFrames In Depth/25. Null Values In DataFrames.mp4
42.16MB
5. DataFrames In Depth/26. Dropping And Filling DataFrame NAs.mp4
49MB
5. DataFrames In Depth/27. BONUS - Methods And Axes With fillna().mp4
57.38MB
5. DataFrames In Depth/28. Skill Challenge.mp4
5.3MB
5. DataFrames In Depth/29. Solution.mp4
42.49MB
5. DataFrames In Depth/3. Quick Review Indexing With Boolean Masks.mp4
23.33MB
5. DataFrames In Depth/30. Calculating Aggregates With agg().mp4
37.08MB
5. DataFrames In Depth/31. Same-shape Transforms.mp4
66.98MB
5. DataFrames In Depth/32. More Flexibility With apply().mp4
59.38MB
5. DataFrames In Depth/33. Element-wise Operations With applymap().mp4
68.51MB
5. DataFrames In Depth/34. Skill Challenge.mp4
8.76MB
5. DataFrames In Depth/35. Solution.mp4
26.47MB
5. DataFrames In Depth/36. Setting DataFrame Values.mp4
43.55MB
5. DataFrames In Depth/37. The SettingWithCopy Warning.mp4
39.81MB
5. DataFrames In Depth/38. View vs Copy.mp4
49.3MB
5. DataFrames In Depth/39. Adding DataFrame Columns.mp4
36.47MB
5. DataFrames In Depth/4. More Approaches To Boolean Masking.mp4
68.42MB
5. DataFrames In Depth/40. Adding Rows To DataFrames.mp4
49.9MB
5. DataFrames In Depth/41. BONUS - How Are DataFrames Stored In Memory.mp4
21.73MB
5. DataFrames In Depth/42. Skill Challenge.mp4
5.04MB
5. DataFrames In Depth/43. Solution.mp4
31.94MB
5. DataFrames In Depth/5. Binary Operators With Booleans.mp4
37.94MB
5. DataFrames In Depth/6. BONUS - XOR and Complement Binary Ops.mp4
50.47MB
5. DataFrames In Depth/7. Combining Conditions.mp4
45.57MB
5. DataFrames In Depth/8. Conditions As Variables.mp4
19.9MB
5. DataFrames In Depth/9. Skill Challenge.mp4
3.96MB
6. Working With Multiple DataFrames/1. Section Intro.mp4
7.95MB
6. Working With Multiple DataFrames/10. Skill Challenge.mp4
5.99MB
6. Working With Multiple DataFrames/11. Solution.mp4
59.47MB
6. Working With Multiple DataFrames/12. The merge() Method.mp4
35.38MB
6. Working With Multiple DataFrames/13. The left_on And right_on Params.mp4
32.2MB
6. Working With Multiple DataFrames/14. Inner vs Outer Joins.mp4
27.11MB
6. Working With Multiple DataFrames/15. Left vs Right Joins.mp4
20.27MB
6. Working With Multiple DataFrames/16. One-to-One and One-to-Many Joins.mp4
57.01MB
6. Working With Multiple DataFrames/17. Many-to-Many Joins.mp4
55.62MB
6. Working With Multiple DataFrames/18. Merging By Index.mp4
38.15MB
6. Working With Multiple DataFrames/19. The join() Method.mp4
22.87MB
6. Working With Multiple DataFrames/2. Introducing (Five) New Datasets.mp4
40.6MB
6. Working With Multiple DataFrames/20. Skill Challenge.mp4
3.81MB
6. Working With Multiple DataFrames/21. Solution.mp4
46.08MB
6. Working With Multiple DataFrames/3. Concatenating DataFrames.mp4
42.12MB
6. Working With Multiple DataFrames/4. The Duplicated Index Issue.mp4
51.32MB
6. Working With Multiple DataFrames/5. Enforcing Unique Indices.mp4
58.39MB
6. Working With Multiple DataFrames/6. BONUS - Creating Multiple Indices With concat().mp4
28.45MB
6. Working With Multiple DataFrames/7. Column Axis Concatenation.mp4
27.09MB
6. Working With Multiple DataFrames/8. The append() Method A Special Case Of concat().mp4
14.48MB
6. Working With Multiple DataFrames/9. Concat On Different Columns.mp4
38.21MB
7. Going MultiDimensional/1. Section Intro.mp4
26.42MB
7. Going MultiDimensional/10. Skill Challenge.mp4
3.78MB
7. Going MultiDimensional/11. Solution.mp4
44.8MB
7. Going MultiDimensional/12. The Anatomy Of A MultiIndex Object.mp4
34.85MB
7. Going MultiDimensional/13. Adding Another Level.mp4
33.59MB
7. Going MultiDimensional/14. Shuffling Levels.mp4
24.32MB
7. Going MultiDimensional/15. Removing MultiIndex Levels.mp4
37.7MB
7. Going MultiDimensional/16. MultiIndex sort_index().mp4
35.62MB
7. Going MultiDimensional/17. More MultiIndex Methods.mp4
37.92MB
7. Going MultiDimensional/18. Reshaping With stack().mp4
30.57MB
7. Going MultiDimensional/19. The Flipside unstack().mp4
45.95MB
7. Going MultiDimensional/2. Introducing New Data.mp4
22.11MB
7. Going MultiDimensional/20. BONUS Creating MultiLevel Columns Manually.mp4
58.73MB
7. Going MultiDimensional/21. An Easier Way transpose().mp4
18.6MB
7. Going MultiDimensional/22. BONUS - What About Panels.mp4
27.89MB
7. Going MultiDimensional/23. Skill Challenge.mp4
8.01MB
7. Going MultiDimensional/24. Solution.mp4
49.18MB
7. Going MultiDimensional/3. Index And RangeIndex.mp4
26.87MB
7. Going MultiDimensional/4. Creating A MultiIndex.mp4
20.15MB
7. Going MultiDimensional/5. MultiIndex From read_csv().mp4
27.7MB
7. Going MultiDimensional/6. Indexing Hierarchical DataFrames.mp4
39.39MB
7. Going MultiDimensional/7. Indexing Ranges And Slices.mp4
59.11MB
7. Going MultiDimensional/8. BONUS - Use With pd.IndexSlice!.mp4
16.97MB
7. Going MultiDimensional/9. Cross Sections With xs().mp4
33.15MB
8. GroupBy And Aggregates/1. Section Intro.mp4
17.09MB
8. GroupBy And Aggregates/10. Skill Challenge.mp4
3.22MB
8. GroupBy And Aggregates/11. Solution.mp4
27.59MB
8. GroupBy And Aggregates/12. Iterating Through Groups.mp4
21.03MB
8. GroupBy And Aggregates/13. Handpicking Subgroups.mp4
23.65MB
8. GroupBy And Aggregates/14. MultiIndex Grouping.mp4
26.54MB
8. GroupBy And Aggregates/15. Fine-tuned Aggregates.mp4
44.14MB
8. GroupBy And Aggregates/16. Named Aggregations.mp4
36.49MB
8. GroupBy And Aggregates/17. The filter() Method.mp4
26.12MB
8. GroupBy And Aggregates/18. GroupBy Transformations.mp4
38.79MB
8. GroupBy And Aggregates/19. BONUS - There's Also apply().mp4
41.18MB
8. GroupBy And Aggregates/2. New Data Game Sales.mp4
14.89MB
8. GroupBy And Aggregates/20. Skill Challenge.mp4
4.05MB
8. GroupBy And Aggregates/21. Solution.mp4
24.51MB
8. GroupBy And Aggregates/3. Simple Aggregations Review.mp4
29.02MB
8. GroupBy And Aggregates/4. Conditional Aggregates.mp4
24.51MB
8. GroupBy And Aggregates/5. The Split-Apply-Combine Pattern.mp4
22.51MB
8. GroupBy And Aggregates/6. The groupby() Method.mp4
21.56MB
8. GroupBy And Aggregates/7. The DataFrameGroupBy Object.mp4
19.81MB
8. GroupBy And Aggregates/8. Customizing Index To Group Mappings.mp4
20.48MB
8. GroupBy And Aggregates/9. BONUS - Series groupby().mp4
20.8MB
9. Reshaping With Pivots/1. Section Intro.mp4
23.83MB
9. Reshaping With Pivots/10. MultiIndex Pivot Tables.mp4
19.05MB
9. Reshaping With Pivots/11. Applying Multiple Functions.mp4
18.33MB
9. Reshaping With Pivots/12. Skill Challenge.mp4
5.48MB
9. Reshaping With Pivots/13. Solution.mp4
36.64MB
9. Reshaping With Pivots/2. New Data New York City SAT Scores.mp4
26.77MB
9. Reshaping With Pivots/3. Pivoting Data.mp4
41.9MB
9. Reshaping With Pivots/4. Undoing Pivots.mp4
27.89MB
9. Reshaping With Pivots/5. What About Aggregates.mp4
34.25MB
9. Reshaping With Pivots/6. The pivot_table().mp4
33.66MB
9. Reshaping With Pivots/7. BONUS The Problem With Average Percentage.mp4
36.16MB
9. Reshaping With Pivots/8. Replicating Pivot Tables With GroupBy.mp4
12.5MB
9. Reshaping With Pivots/9. Adding Margins.mp4
24.59MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载,或者bt下载软件里即可下载文件,或者直接复制迅雷链接到迅雷里下载! 亲,你造吗?将网页分享给您的基友,下载的人越多速度越快哦!
违规内容投诉邮箱:
[email protected]
概述 838888磁力搜索是一个磁力链接搜索引擎,是学术研究的副产品,用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络,实时的自动采集数据,仅存储文件的标题、大小、文件列表、文件标识符(磁力链接)等基础信息 838888磁力搜索不下载任何真实资源,无法判断资源的合法性及真实性,使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源,不提供Tracker服务,不提供种子文件的下载,这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统