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| [CourseClub.Me].url |
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| [CourseClub.Me].url |
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| [DesireCourse.Net].url |
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| [FreeCourseWorld.Com].url |
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| 1.1 Course_Materials_Part1.zip |
1.42Мб |
| 1.1 Course_Materials_Part3.zip |
8.46Мб |
| 1.1 Numpy_basics.zip |
105.78Кб |
| 1.1 Overview.pdf |
1022.89Кб |
| 1.1 tabdata.pdf |
472.13Кб |
| 1.2 Course_Materials_Part2.zip |
6.16Мб |
| 1. Create your very first Pandas DataFrame (from csv).mp4 |
59.42Мб |
| 1. Create your very first Pandas DataFrame (from csv).srt |
10.55Кб |
| 1. Download Part 3 Course Materials.html |
131б |
| 1. First Inspection & Handling of inconsistent Data.mp4 |
68.24Мб |
| 1. First Inspection & Handling of inconsistent Data.srt |
13.12Кб |
| 1. Get your special BONUS here!.html |
3.54Кб |
| 1. Importing csv-files with pd.read_csv.mp4 |
90.94Мб |
| 1. Importing Time Series Data from csv-files.mp4 |
41.75Мб |
| 1. Importing Time Series Data from csv-files.srt |
9.59Кб |
| 1. Intro.html |
585б |
| 1. Intro.html |
894б |
| 1. Intro.html |
710б |
| 1. Intro.html |
775б |
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406б |
| 1. Intro.html |
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| 1. Intro.html |
643б |
| 1. Intro.html |
680б |
| 1. Intro.mp4 |
10.09Мб |
| 1. Intro.mp4 |
5.89Мб |
| 1. Intro.srt |
2.62Кб |
| 1. Intro.srt |
2.88Кб |
| 1. Intro and Overview.mp4 |
15.50Мб |
| 1. Intro and Overview.srt |
2.57Кб |
| 1. Introduction to Numpy Arrays.mp4 |
41.13Мб |
| 1. Introduction to Numpy Arrays.srt |
8.84Кб |
| 1. Intro to Tabular Data Pandas.mp4 |
18.07Мб |
| 1. Intro to Tabular Data Pandas.srt |
5.46Кб |
| 1. Overview Student FAQ.mp4 |
48.47Мб |
| 1. Overview Student FAQ.srt |
12.03Кб |
| 1. Parts 1 & 2 .py files.html |
64б |
| 1. Statistics - Overview, Terms and Vocabulary.mp4 |
93.36Мб |
| 1. Statistics - Overview, Terms and Vocabulary.srt |
14.91Кб |
| 1. Welcome to PART 2 Full Data Workflow A-Z.html |
814б |
| 1. Welcome to PART 4 Time Series Data with Pandas.html |
637б |
| 1. Welcome to the Appendix.html |
422б |
| 10. Advanced Indexing with reindex().mp4 |
50.50Мб |
| 10. Advanced Indexing with reindex().srt |
10.13Кб |
| 10. Creating Columns based on other Columns.mp4 |
34.56Мб |
| 10. Creating Columns based on other Columns.srt |
7.92Кб |
| 10. Financial Time Series - Covariance and Correlation.mp4 |
25.73Мб |
| 10. Financial Time Series - Covariance and Correlation.srt |
5.51Кб |
| 10. Handling Removing Duplicates.mp4 |
88.67Мб |
| 10. Handling Removing Duplicates.srt |
88.70Мб |
| 10. Hierarchical Indexing (Part 1).mp4 |
72.59Мб |
| 10. Hierarchical Indexing (Part 1).srt |
12.73Кб |
| 10. idxmin() and idxmax().mp4 |
28.69Мб |
| 10. idxmin() and idxmax().srt |
6.04Кб |
| 10. Minimum, Maximum and Range with PythonNumpy.mp4 |
12.30Мб |
| 10. Minimum, Maximum and Range with PythonNumpy.srt |
2.48Кб |
| 10. Operators & Booleans.mp4 |
59.52Мб |
| 10. Operators & Booleans.srt |
11.09Кб |
| 10. Replacing NA Values by group-specific Values.mp4 |
44.75Мб |
| 10. Replacing NA Values by group-specific Values.srt |
8.65Кб |
| 10. Right Joins (without Intersection) with merge().mp4 |
15.03Мб |
| 10. Right Joins (without Intersection) with merge().srt |
2.58Кб |
| 10. Scaling Standardization.mp4 |
56.33Мб |
| 10. Scaling Standardization.srt |
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| 10. Selecting one Column with the dot notation.mp4 |
8.53Мб |
| 10. Selecting one Column with the dot notation.srt |
2.97Кб |
| 10. Summary Statistics.mp4 |
44.82Мб |
| 10. Summary Statistics.srt |
8.53Кб |
| 10. The NEW StringDtype.mp4 |
32.10Мб |
| 10. The NEW StringDtype.srt |
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| 11.1 positions.pdf |
194.16Кб |
| 11. Adding Columns with insert().mp4 |
13.07Мб |
| 11. Adding Columns with insert().srt |
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| 11. Conditional Statements (if, elif, else, while).mp4 |
86.04Мб |
| 11. Conditional Statements (if, elif, else, while).srt |
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| 11. Creating Dummy Variables.mp4 |
55.25Мб |
| 11. Creating Dummy Variables.srt |
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| 11. Generalizing split-apply-combine with apply().mp4 |
42.78Мб |
| 11. Generalizing split-apply-combine with apply().srt |
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| 11. Helpful DatetimeIndex Attributes and Methods.mp4 |
44.30Мб |
| 11. Helpful DatetimeIndex Attributes and Methods.srt |
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| 11. Hierarchical Indexing (Part 2).mp4 |
72.59Мб |
| 11. Hierarchical Indexing (Part 2).srt |
14.65Кб |
| 11. Left Joins with merge().mp4 |
24.09Мб |
| 11. Left Joins with merge().srt |
5.17Кб |
| 11. Manipulating Pandas Series.mp4 |
37.87Мб |
| 11. Manipulating Pandas Series.srt |
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| 11. Percentiles with PythonNumpy.mp4 |
17.57Мб |
| 11. Percentiles with PythonNumpy.srt |
4.11Кб |
| 11. The ignore_index parameter (NEW in Pandas 1.0).mp4 |
5.67Мб |
| 11. The ignore_index parameter (NEW in Pandas 1.0).srt |
2.17Кб |
| 11. The NEW nullable BooleanDtype.mp4 |
23.20Мб |
| 11. The NEW nullable BooleanDtype.srt |
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| 11. Visualization and (Linear) Regression.mp4 |
84.55Мб |
| 11. Visualization and (Linear) Regression.srt |
14.32Кб |
| 11. Zero-based Indexing and Negative Indexing.mp4 |
10.18Мб |
| 11. Zero-based Indexing and Negative Indexing.srt |
3.68Кб |
| 12. Addition of the ignore_index parameter.mp4 |
21.75Мб |
| 12. Addition of the ignore_index parameter.srt |
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| 12. Creating DataFrames from Scratch with pd.DataFrame().mp4 |
43.30Мб |
| 12. Creating DataFrames from Scratch with pd.DataFrame().srt |
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| 12. Detection of Outliers.mp4 |
44.07Мб |
| 12. Detection of Outliers.srt |
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| 12. Filling NA Values with bfill, ffill and interpolation.mp4 |
78.44Мб |
| 12. Filling NA Values with bfill, ffill and interpolation.srt |
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| 12. For Loops.mp4 |
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| 12. For Loops.srt |
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| 12. Hierarchical Indexing with Groupby.mp4 |
32.86Мб |
| 12. Hierarchical Indexing with Groupby.srt |
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| 12. Numpy.html |
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| 12. Pandas Series.html |
130б |
| 12. Right Joins with merge().mp4 |
27.41Мб |
| 12. Right Joins with merge().srt |
4.58Кб |
| 12. Selecting Rows with iloc (position-based indexing).mp4 |
65.00Мб |
| 12. Selecting Rows with iloc (position-based indexing).srt |
11.29Кб |
| 12. String Operations.mp4 |
29.66Мб |
| 12. String Operations.srt |
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| 12. String Operations (Part 1).mp4 |
41.19Мб |
| 12. String Operations (Part 1).srt |
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| 12. Variance and Standard Deviation with PythonNumpy.mp4 |
16.35Мб |
| 12. Variance and Standard Deviation with PythonNumpy.srt |
4.00Кб |
| 13.1 skew_kurtosis.pdf |
425.14Кб |
| 13. Adding new Rows (hands-on approach).mp4 |
16.95Мб |
| 13. Adding new Rows (hands-on approach).srt |
3.76Кб |
| 13. Coding Exercise 15.html |
557б |
| 13. Coding Exercise 17.html |
557б |
| 13. Coding Exercise 3 (Intro).html |
158б |
| 13. Handling Removing Outliers.mp4 |
29.69Мб |
| 13. Handling Removing Outliers.srt |
6.80Кб |
| 13. Joining on different Column Names Indexes.mp4 |
95.32Мб |
| 13. Joining on different Column Names Indexes.srt |
16.30Кб |
| 13. Key words break, pass, continue.mp4 |
36.71Мб |
| 13. Key words break, pass, continue.srt |
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| 13. Numpy Quiz Solution.mp4 |
45.45Мб |
| 13. Numpy Quiz Solution.srt |
16.45Кб |
| 13. Removal of prior Version Deprecations.mp4 |
42.87Мб |
| 13. Removal of prior Version Deprecations.srt |
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| 13. Skew and Kurtosis (Theory).mp4 |
18.02Мб |
| 13. Skew and Kurtosis (Theory).srt |
5.24Кб |
| 13. Slicing Rows and Columns with iloc (position-based indexing).mp4 |
24.29Мб |
| 13. Slicing Rows and Columns with iloc (position-based indexing).srt |
5.23Кб |
| 13. stack() and unstack().mp4 |
78.81Мб |
| 13. stack() and unstack().srt |
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| 13. String Operations (Part 2).mp4 |
55.19Мб |
| 13. String Operations (Part 2).srt |
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| 14.1 pandas-iloc.pdf |
72.00Кб |
| 14. Categorical Data.mp4 |
45.48Мб |
| 14. Categorical Data.srt |
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| 14. Coding Exercise 3 (Solution).mp4 |
38.65Мб |
| 14. Coding Exercise 3 (Solution).srt |
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| 14. Coding Exercise 8 (Intro).html |
158б |
| 14. DataFrame Basics II.html |
130б |
| 14. Generating Random Numbers.mp4 |
38.13Мб |
| 14. Generating Random Numbers.srt |
7.81Кб |
| 14. GroupBy 2.html |
130б |
| 14. How to calculate Skew and Kurtosis with scipy.stats.mp4 |
27.44Мб |
| 14. How to calculate Skew and Kurtosis with scipy.stats.srt |
6.86Кб |
| 14. Joining on more than one Column.mp4 |
38.69Мб |
| 14. Joining on more than one Column.srt |
9.45Кб |
| 14. Position-based Indexing Cheat Sheets.html |
495б |
| 15. Coding Exercise 13 (Intro).html |
159б |
| 15. Coding Exercise 5 (Intro).html |
158б |
| 15. Coding Exercise 8 (Solution).mp4 |
58.22Мб |
| 15. Coding Exercise 8 (Solution).srt |
10.67Кб |
| 15. First Steps with Pandas Index Objects.mp4 |
43.09Мб |
| 15. First Steps with Pandas Index Objects.srt |
6.56Кб |
| 15. How to generate Random Numbers with Numpy.mp4 |
25.21Мб |
| 15. How to generate Random Numbers with Numpy.srt |
5.52Кб |
| 15. Pandas Version 1.0 New dtypes and pd.NA.mp4 |
18.47Мб |
| 15. Pandas Version 1.0 New dtypes and pd.NA.srt |
18.32Мб |
| 15. pd.merge() and join().mp4 |
35.48Мб |
| 15. pd.merge() and join().srt |
6.84Кб |
| 15. Selecting Rows with loc (label-based indexing).mp4 |
21.34Мб |
| 15. Selecting Rows with loc (label-based indexing).srt |
3.66Кб |
| 15. User Defined Functions (Part 1).mp4 |
64.35Мб |
| 15. User Defined Functions (Part 1).srt |
10.46Кб |
| 16. Coding Exercise 11 (Intro).html |
159б |
| 16. Coding Exercise 12.html |
557б |
| 16. Coding Exercise 13 (Solution).mp4 |
81.56Мб |
| 16. Coding Exercise 13 (Solution).srt |
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| 16. Coding Exercise 5 (Solution).mp4 |
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| 16. Coding Exercise 5 (Solution).srt |
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| 16. Creating Index Objects from Scratch.mp4 |
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| 16. Creating Index Objects from Scratch.srt |
3.45Кб |
| 16. Reproducibility with np.random.seed().mp4 |
17.25Мб |
| 16. Reproducibility with np.random.seed().srt |
4.28Кб |
| 16. Slicing Rows and Columns with loc (label-based indexing).mp4 |
77.55Мб |
| 16. Slicing Rows and Columns with loc (label-based indexing).srt |
11.40Кб |
| 16. User Defined Functions (Part 2).mp4 |
57.39Мб |
| 16. User Defined Functions (Part 2).srt |
7.68Кб |
| 17.1 Pandas-loc.pdf |
67.80Кб |
| 17.1 Prob_distr.pdf |
477.98Кб |
| 17. Changing Row Index with set_index() and reset_index().mp4 |
75.03Мб |
| 17. Changing Row Index with set_index() and reset_index().srt |
11.79Кб |
| 17. Coding Exercise 11 (Solution).mp4 |
129.71Мб |
| 17. Coding Exercise 11 (Solution).srt |
19.55Кб |
| 17. Label-based Indexing Cheat Sheets.html |
786б |
| 17. Probability Distributions - Overview.mp4 |
35.69Мб |
| 17. Probability Distributions - Overview.srt |
7.91Кб |
| 17. User Defined Functions (Part 3).mp4 |
52.12Мб |
| 17. User Defined Functions (Part 3).srt |
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| 18. Changing Column Labels.mp4 |
21.16Мб |
| 18. Changing Column Labels.srt |
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| 18. Discrete Uniform Distributions.mp4 |
28.19Мб |
| 18. Discrete Uniform Distributions.srt |
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| 18. Indexing and Slicing with reindex().mp4 |
38.92Мб |
| 18. Indexing and Slicing with reindex().srt |
6.23Кб |
| 18. Visualization with Matplotlib.mp4 |
124.22Мб |
| 18. Visualization with Matplotlib.srt |
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| 19. Continuous Uniform Distributions.mp4 |
20.11Мб |
| 19. Continuous Uniform Distributions.srt |
4.70Кб |
| 19. Python Basics.html |
130б |
| 19. Renaming Index & Column Labels with rename().mp4 |
28.00Мб |
| 19. Renaming Index & Column Labels with rename().srt |
4.79Кб |
| 19. Summary, Best Practices and Outlook.mp4 |
41.99Мб |
| 19. Summary, Best Practices and Outlook.srt |
7.66Кб |
| 2.1 Course_Materials_Part1.zip |
1.05Мб |
| 2.1 Course_Materials_Part2.zip |
5.34Мб |
| 2.1 Course_Materials_Part4.zip |
831.46Кб |
| 2.1 Course_Materials_Statistics.zip |
12.45Мб |
| 2. Adding Rows with append() and pd.concat() (Part 1).mp4 |
88.07Мб |
| 2. Adding Rows with append() and pd.concat() (Part 1).srt |
15.66Кб |
| 2. Arithmetic Operations (Part 1).mp4 |
63.52Мб |
| 2. Arithmetic Operations (Part 1).srt |
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| 2. Best Practice (How you should do it).mp4 |
52.60Мб |
| 2. Best Practice (How you should do it).srt |
10.79Кб |
| 2. Converting strings to datetime objects with pd.to_datetime().mp4 |
58.00Мб |
| 2. Converting strings to datetime objects with pd.to_datetime().srt |
11.08Кб |
| 2. Download Part 1 Course Materials.mp4 |
18.73Мб |
| 2. Download Part 1 Course Materials.srt |
2.89Кб |
| 2. Download Part 2 Course Materials.html |
131б |
| 2. Download Part 4 Course Materials.html |
131б |
| 2. Downloads for this Section.html |
84б |
| 2. Filtering DataFrames by one Condition.mp4 |
52.92Мб |
| 2. Filtering DataFrames by one Condition.srt |
12.66Кб |
| 2. First Steps.mp4 |
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| 2. First Steps.srt |
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| 2. First Steps in Seaborn.mp4 |
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| 2. First Steps in Seaborn.srt |
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| 2. First Steps with Pandas Series.mp4 |
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| 2. First Steps with Pandas Series.srt |
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| 2. Getting Ready (Installing required package).mp4 |
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| 2. Getting Ready (Installing required package).srt |
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| 2. How to update Pandas to Version 1.0.html |
313б |
| 2. Importing messy csv-files with pd.read_csv.mp4 |
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| 2. Importing messy csv-files with pd.read_csv.srt |
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| 2. Numpy Arrays Vectorization.mp4 |
64.74Мб |
| 2. Numpy Arrays Vectorization.srt |
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| 2. Olympic Medal Tables (Instruction & Hints).mp4 |
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| 2. Olympic Medal Tables (Instruction & Hints).srt |
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| 2. Pandas Display Options and the methods head() & tail().mp4 |
40.46Мб |
| 2. Pandas Display Options and the methods head() & tail().srt |
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| 2. Sorting DataFrames with sort_index() and sort_values() (Version 1.0 Update).mp4 |
68.86Мб |
| 2. Sorting DataFrames with sort_index() and sort_values() (Version 1.0 Update).srt |
10.37Кб |
| 2. String Operations.mp4 |
80.88Мб |
| 2. String Operations.srt |
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| 2. The plot() method.mp4 |
70.25Мб |
| 2. The plot() method.srt |
10.86Кб |
| 2. Tips How to get the most out of this course.mp4 |
43.63Мб |
| 2. Tips How to get the most out of this course.srt |
6.53Кб |
| 2. Transposing Rows and Columns.mp4 |
68.43Мб |
| 2. Transposing Rows and Columns.srt |
12.95Кб |
| 2. Understanding the GroupBy Object.mp4 |
46.27Мб |
| 2. Understanding the GroupBy Object.srt |
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| 20.1 Normal.pdf |
412.36Кб |
| 20. Indexing and Slicing.html |
130б |
| 20. Pandas Index objects.html |
130б |
| 20. Python Basics Quiz Solution.mp4 |
38.25Мб |
| 20. Python Basics Quiz Solution.srt |
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| 20. The Normal Distribution (Theory).mp4 |
18.42Мб |
| 20. The Normal Distribution (Theory).srt |
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| 21. Coding Exercise 2 (Intro).mp4 |
8.06Мб |
| 21. Coding Exercise 2 (Intro).srt |
1.74Кб |
| 21. Coding Exercise 4 (Intro).html |
158б |
| 21. Creating a normally distributed Random Variable.mp4 |
24.11Мб |
| 21. Creating a normally distributed Random Variable.srt |
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| 22. Coding Exercise 2 (Solution).mp4 |
28.07Мб |
| 22. Coding Exercise 2 (Solution).srt |
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| 22. Coding Exercise 4 (Solution).mp4 |
26.35Мб |
| 22. Coding Exercise 4 (Solution).srt |
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| 22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4 |
26.95Мб |
| 22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.srt |
4.46Кб |
| 23. Advanced Indexing and Slicing (optional).mp4 |
34.11Мб |
| 23. Advanced Indexing and Slicing (optional).srt |
6.17Кб |
| 23. Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4 |
15.39Мб |
| 23. Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.srt |
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| 24. The Standard Normal Distribution and Z-Values.mp4 |
38.66Мб |
| 24. The Standard Normal Distribution and Z-Values.srt |
7.41Кб |
| 25.1 standard_normal.pdf |
393.93Кб |
| 25. Properties of the Standard Normal Distribution (Theory).mp4 |
14.85Мб |
| 25. Properties of the Standard Normal Distribution (Theory).srt |
3.70Кб |
| 26. Probabilities and Z-Values with scipy.stats.mp4 |
59.28Мб |
| 26. Probabilities and Z-Values with scipy.stats.srt |
12.74Кб |
| 27. Confidence Intervals with scipy.stats.mp4 |
48.10Мб |
| 27. Confidence Intervals with scipy.stats.srt |
8.46Кб |
| 28.1 Cov_Corr.pdf |
228.13Кб |
| 28. Covariance and Correlation Coefficient (Theory).mp4 |
27.58Мб |
| 28. Covariance and Correlation Coefficient (Theory).srt |
8.80Кб |
| 29. Cleaning and preparing the Data - Movies Database (Part 1).mp4 |
47.00Мб |
| 29. Cleaning and preparing the Data - Movies Database (Part 1).srt |
7.59Кб |
| 3.1 Course_Materials_Version_1_0.zip |
27.36Кб |
| 3. Adding Rows with pd.concat() (Part 2).mp4 |
56.90Мб |
| 3. Adding Rows with pd.concat() (Part 2).srt |
11.45Кб |
| 3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 |
67.12Мб |
| 3. Analyzing Numerical Series with unique(), nunique() and value_counts().srt |
16.84Кб |
| 3. Arithmetic Operations (Part 2).mp4 |
58.45Мб |
| 3. Arithmetic Operations (Part 2).srt |
14.57Кб |
| 3. Categorical Plots.mp4 |
85.20Мб |
| 3. Categorical Plots.srt |
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| 3. Chained Indexing How you should NOT do it (Part 1).mp4 |
60.07Мб |
| 3. Chained Indexing How you should NOT do it (Part 1).srt |
10.70Кб |
| 3. Changing Datatype of Columns with astype().mp4 |
38.80Мб |
| 3. Changing Datatype of Columns with astype().srt |
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| 3. Customization of Plots.mp4 |
102.99Мб |
| 3. Customization of Plots.srt |
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| 3. Did you know that....mp4 |
31.24Мб |
| 3. Did you know that....srt |
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| 3. Downloads for this Section.html |
84б |
| 3. Filtering DataFrames by many Conditions (AND).mp4 |
25.93Мб |
| 3. Filtering DataFrames by many Conditions (AND).srt |
5.14Кб |
| 3. First Data Inspection.mp4 |
56.01Мб |
| 3. First Data Inspection.srt |
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| 3. Importing Data from Excel with pd.read_excel().mp4 |
73.90Мб |
| 3. Importing Data from Excel with pd.read_excel().srt |
14.41Кб |
| 3. Importing Stock Price Data from Yahoo Finance (it still works!).mp4 |
71.92Мб |
| 3. Importing Stock Price Data from Yahoo Finance (it still works!).srt |
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| 3. Initial Analysis Visualization of Time Series.mp4 |
35.00Мб |
| 3. Initial Analysis Visualization of Time Series.srt |
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| 3. Numpy Arrays Indexing and Slicing.mp4 |
53.44Мб |
| 3. Numpy Arrays Indexing and Slicing.srt |
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| 3. Olympic Medal Tables (Solution Part 1).mp4 |
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| 3. Olympic Medal Tables (Solution Part 1).srt |
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| 3. Pivoting DataFrames with pivot().mp4 |
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| 3. Pivoting DataFrames with pivot().srt |
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| 3. Population vs. Sample.mp4 |
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| 3. Population vs. Sample.srt |
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| 3. Ranking DataFrames with rank().mp4 |
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| 3. Ranking DataFrames with rank().srt |
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| 3. Splitting with many Keys.mp4 |
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| 3. Splitting with many Keys.srt |
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| 3. Variables.mp4 |
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| 3. Variables.srt |
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| 30. Cleaning and preparing the Data - Movies Database (Part 2).mp4 |
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| 30. Cleaning and preparing the Data - Movies Database (Part 2).srt |
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| 31. How to calculate Covariance and Correlation in Python.mp4 |
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| 31. How to calculate Covariance and Correlation in Python.srt |
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| 32. Correlation and Scatterplots – visual Interpretation.mp4 |
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| 32. Correlation and Scatterplots – visual Interpretation.srt |
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| 33.1 Regression.pdf |
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| 33. What is Linear Regression (Theory).mp4 |
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| 33. What is Linear Regression (Theory).srt |
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| 34. A simple Linear Regression Model with numpy & Scipy.mp4 |
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| 34. A simple Linear Regression Model with numpy & Scipy.srt |
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| 35.1 Coeff.pdf |
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| 35. How to interpret Intercept and Slope Coefficient.mp4 |
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| 35. How to interpret Intercept and Slope Coefficient.srt |
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| 36. Case Study (Part 1) The Market Model (Single Factor Model).mp4 |
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| 36. Case Study (Part 1) The Market Model (Single Factor Model).srt |
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| 37. Case Study (Part 2) The Market Model (Single Factor Model).mp4 |
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| 37. Case Study (Part 2) The Market Model (Single Factor Model).srt |
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| 4.1 DataFrame Methods and Attributes.html |
141б |
| 4.2 Pandas Series Methods and Attributes.html |
138б |
| 4. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 |
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| 4. Analyzing non-numerical Series with unique(), nunique(), value_counts().srt |
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| 4. Arithmetic with Pandas Objects Data Alignment.mp4 |
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| 4. Built-in Functions, Attributes and Methods with Pandas.mp4 |
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| 4. Built-in Functions, Attributes and Methods with Pandas.srt |
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| 4. Chained Indexing How you should NOT do it (Part 2).mp4 |
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| 4. Chained Indexing How you should NOT do it (Part 2).srt |
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| 4. Data Types Integers and Floats.mp4 |
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| 4. Data Types Integers and Floats.srt |
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| 4. Filtering DataFrames by many Conditions (OR).mp4 |
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| 4. Filtering DataFrames by many Conditions (OR).srt |
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| 4. Histograms (Part 1).mp4 |
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| 4. Important Recap Pandas Display Options (Changed in Version 0.25).mp4 |
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| 4. Importing messy Data from Excel with pd.read_excel().mp4 |
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| 4. Importing messy Data from Excel with pd.read_excel().srt |
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| 4. Indexing and Slicing Time Series.mp4 |
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| 4. Indexing and Slicing Time Series.srt |
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| 4. Initial Inspection and Visualization.mp4 |
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| 4. Intro NA values missing values.mp4 |
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| 4. Joint Plots Regression Plots.mp4 |
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| 4. Limits of pivot().mp4 |
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| 4. Limits of pivot().srt |
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| 4. More FAQ Important Information.html |
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| 4. Numpy Arrays Shape and Dimensions.mp4 |
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| 4. Numpy Arrays Shape and Dimensions.srt |
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| 4. nunique() and nlargest() nsmallest() with DataFrames.mp4 |
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| 4. nunique() and nlargest() nsmallest() with DataFrames.srt |
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| 4. Olympic Medal Tables (Solution Part 2).mp4 |
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| 4. split-apply-combine explained.mp4 |
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| 4. split-apply-combine explained.srt |
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| 4. TransformationMapping with map().mp4 |
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| 4. TransformationMapping with map().srt |
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| 4. Visualizing Frequency Distributions with plt.hist().mp4 |
22.64Мб |
| 4. Visualizing Frequency Distributions with plt.hist().srt |
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| 5.1 Installing on Windows.html |
112б |
| 5.2 Installing on macOS.html |
111б |
| 5.3 Installing on Linux.html |
110б |
| 5. Advanced Filtering with between(), isin() and ~.mp4 |
65.68Мб |
| 5. Advanced Filtering with between(), isin() and ~.srt |
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| 5. Conditional Transformation.mp4 |
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| 5. Conditional Transformation.srt |
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| 5. Creating a customized DatetimeIndex with pd.date_range().mp4 |
114.64Мб |
| 5. Creating a customized DatetimeIndex with pd.date_range().srt |
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| 5. Creating Pandas Series (Part 1).mp4 |
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| 5. Data Types Strings.mp4 |
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| 5. Data Types Strings.srt |
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| 5. Detection of missing Values.mp4 |
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| 5. Detection of missing Values.srt |
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| 5. EXCURSUS Comparing two DataFrames Identify Differences.html |
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| 5. Histograms (Part 2).mp4 |
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| 5. Histograms (Part 2).srt |
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| 5. Importing Data from the Web with pd.read_html().mp4 |
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| 5. Importing Data from the Web with pd.read_html().srt |
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| 5. Info() method - new and extended output.mp4 |
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| 5. Installation of Anaconda.mp4 |
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| 5. Make it easy TAB Completion and Tooltip.mp4 |
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| 5. Matrixplots Heatmaps.mp4 |
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| 5. Matrixplots Heatmaps.srt |
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| 5. Normalizing Time Series to a Base Value (100).mp4 |
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| 5. Normalizing Time Series to a Base Value (100).srt |
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| 5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4 |
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| 5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.srt |
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| 5. Olympic Medal Tables (Solution Part 3).mp4 |
26.99Мб |
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| 5. pivot_table().mp4 |
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| 5. pivot_table().srt |
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| 5. Relative and Cumulative Frequencies with plt.hist().mp4 |
36.41Мб |
| 5. Relative and Cumulative Frequencies with plt.hist().srt |
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| 5. split-apply-combine applied.mp4 |
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| 5. split-apply-combine applied.srt |
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| 5. Summary Statistics and Accumulations.mp4 |
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| 5. Summary Statistics and Accumulations.srt |
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| 5. View vs. Copy.mp4 |
34.54Мб |
| 5. View vs. Copy.srt |
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| 6.1 Central_tendency.pdf |
299.27Кб |
| 6. any() and all().mp4 |
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| 6. any() and all().srt |
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| 6. Barcharts and Piecharts.mp4 |
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| 6. Barcharts and Piecharts.srt |
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| 6. Coding Exercise 10.html |
557б |
| 6. Coding Exercise 16.html |
557б |
| 6. Creating Pandas Series (Part 2).mp4 |
26.74Мб |
| 6. Creating Pandas Series (Part 2).srt |
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| 6. Data Types Lists (Part 1).mp4 |
62.70Мб |
| 6. Data Types Lists (Part 1).srt |
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| 6. Discretization and Binning with pd.cut() (Part 1).mp4 |
73.03Мб |
| 6. Discretization and Binning with pd.cut() (Part 1).srt |
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| 6. First Steps.html |
130б |
| 6. GroupBy 1.html |
130б |
| 6. Measures of Central Tendency (Theory).mp4 |
20.74Мб |
| 6. Measures of Central Tendency (Theory).srt |
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| 6. More on pd.date_range().mp4 |
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| 6. More on pd.date_range().srt |
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| 6. NEW Extension dtypes (nullable dtypes) Why do we need them.mp4 |
28.29Мб |
| 6. NEW Extension dtypes (nullable dtypes) Why do we need them.srt |
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| 6. Numpy Arrays Boolean Indexing.mp4 |
44.22Мб |
| 6. Numpy Arrays Boolean Indexing.srt |
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| 6. Opening a Jupyter Notebook.mp4 |
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| 6. Opening a Jupyter Notebook.srt |
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| 6. Outer Joins with merge().mp4 |
80.10Мб |
| 6. Outer Joins with merge().srt |
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| 6. pd.crosstab().mp4 |
99.48Мб |
| 6. pd.crosstab().srt |
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| 6. Removing missing values.mp4 |
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| 6. Removing missing values.srt |
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| 6. Simple Rules what to do when....mp4 |
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| 6. Simple Rules what to do when....srt |
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| 6. The agg() method.mp4 |
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| 6. The agg() method.srt |
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| 6. The shift() method.mp4 |
35.78Мб |
| 6. The shift() method.srt |
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| 7. Advanced aggregation with agg().mp4 |
30.26Мб |
| 7. Advanced aggregation with agg().srt |
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| 7. Coding Exercise 7 (Intro).html |
158б |
| 7. Coding Measures of Central Tendency - Mean and Median.mp4 |
22.34Мб |
| 7. Coding Measures of Central Tendency - Mean and Median.srt |
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| 7. Creating the NEW extension dtypes with convert_dtypes().mp4 |
25.70Мб |
| 7. Creating the NEW extension dtypes with convert_dtypes().srt |
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| 7. Data Types Lists (Part 2).mp4 |
134.41Мб |
| 7. Data Types Lists (Part 2).srt |
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| 7. Discretization and Binning with pd.cut() (Part 2).mp4 |
32.70Мб |
| 7. Discretization and Binning with pd.cut() (Part 2).srt |
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| 7. Downsampling Time Series with resample() (Part 1).mp4 |
85.50Мб |
| 7. Downsampling Time Series with resample() (Part 1).srt |
16.35Кб |
| 7. Explore your own Dataset Coding Exercise 1 (Intro).mp4 |
26.55Мб |
| 7. Explore your own Dataset Coding Exercise 1 (Intro).srt |
4.28Кб |
| 7. Generating Random Numbers.mp4 |
67.53Мб |
| 7. Generating Random Numbers.srt |
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| 7. How to use Jupyter Notebooks.mp4 |
66.29Мб |
| 7. How to use Jupyter Notebooks.srt |
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| 7. Indexing and Slicing Pandas Series.mp4 |
66.22Мб |
| 7. Indexing and Slicing Pandas Series.srt |
11.36Кб |
| 7. Inner Joins with merge().mp4 |
15.56Мб |
| 7. Inner Joins with merge().srt |
3.33Кб |
| 7. Manipulating DataFrames Slices.html |
130б |
| 7. melting DataFrames with melt().mp4 |
49.45Мб |
| 7. melting DataFrames with melt().srt |
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| 7. Removing Columns.mp4 |
36.02Мб |
| 7. Removing Columns.srt |
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| 7. Replacing missing values.mp4 |
24.59Мб |
| 7. Replacing missing values.srt |
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| 7. Scatterplots.mp4 |
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| 7. Scatterplots.srt |
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| 7. The methods diff() and pct_change().mp4 |
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| 7. The methods diff() and pct_change().srt |
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| 8. Coding Exercise 14.html |
557б |
| 8. Coding Exercise 6 (Intro).html |
158б |
| 8. Coding Exercise 7 (Solution).mp4 |
39.82Мб |
| 8. Coding Exercise 7 (Solution).srt |
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| 8. Coding Exercise 9 (Intro).html |
158б |
| 8. Coding Measures of Central Tendency - Geometric Mean.mp4 |
16.56Мб |
| 8. Coding Measures of Central Tendency - Geometric Mean.srt |
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| 8. Data Types Tuples.mp4 |
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| 8. Data Types Tuples.srt |
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| 8. Discretization and Binning with pd.qcut().mp4 |
85.39Мб |
| 8. Discretization and Binning with pd.qcut().srt |
16.13Кб |
| 8. Downsampling Time Series with resample (Part 2).mp4 |
49.11Мб |
| 8. Downsampling Time Series with resample (Part 2).srt |
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| 8. Explore your own Dataset Coding Exercise 1 (Solution).mp4 |
31.20Мб |
| 8. Explore your own Dataset Coding Exercise 1 (Solution).srt |
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| 8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).mp4 |
20.62Мб |
| 8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).srt |
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| 8. How to tackle Pandas Version 1.0.mp4 |
19.03Мб |
| 8. How to tackle Pandas Version 1.0.srt |
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| 8. Intro Duplicates.mp4 |
20.26Мб |
| 8. Intro Duplicates.srt |
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| 8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 |
43.93Мб |
| 8. Measuring Stock Performance with MEAN Returns and STD of Returns.srt |
10.55Кб |
| 8. NEW pd.NA value for missing values.mp4 |
27.91Мб |
| 8. NEW pd.NA value for missing values.srt |
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| 8. Outer Joins (without Intersection) with merge().mp4 |
31.49Мб |
| 8. Outer Joins (without Intersection) with merge().srt |
5.46Кб |
| 8. Performance Issues.mp4 |
49.88Мб |
| 8. Performance Issues.srt |
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| 8. Removing Rows.mp4 |
49.62Мб |
| 8. Removing Rows.srt |
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| 8. Sorting of Series and Introduction to the inplace - parameter.mp4 |
41.40Мб |
| 8. Sorting of Series and Introduction to the inplace - parameter.srt |
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| 9.1 Dispersion.pdf |
298.92Кб |
| 9. Adding new Columns to a DataFrame.mp4 |
17.88Мб |
| 9. Adding new Columns to a DataFrame.srt |
3.85Кб |
| 9. Case Study Numpy vs. Python Standard Library.mp4 |
45.61Мб |
| 9. Case Study Numpy vs. Python Standard Library.srt |
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| 9. Coding Exercise 6 (Solution).mp4 |
39.40Мб |
| 9. Coding Exercise 6 (Solution).srt |
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| 9. Coding Exercise 9 (Solution).mp4 |
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| 9. Coding Exercise 9 (Solution).srt |
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| 9. Data Types Sets.mp4 |
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| 9. Data Types Sets.srt |
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| 9. Detection of Duplicates.mp4 |
79.21Мб |
| 9. Detection of Duplicates.srt |
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| 9. Financial Time Series - Return and Risk.mp4 |
53.62Мб |
| 9. Financial Time Series - Return and Risk.srt |
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| 9. Floors and Caps.mp4 |
39.25Мб |
| 9. Floors and Caps.srt |
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| 9. Left Joins (without Intersection) with merge().mp4 |
21.85Мб |
| 9. Left Joins (without Intersection) with merge().srt |
3.85Кб |
| 9. nlargest() and nsmallest().mp4 |
16.77Мб |
| 9. nlargest() and nsmallest().srt |
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| 9. Selecting Columns.mp4 |
26.63Мб |
| 9. Selecting Columns.srt |
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| 9. The NEW nullable Int64Dtype.mp4 |
18.00Мб |
| 9. The NEW nullable Int64Dtype.srt |
4.06Кб |
| 9. The PeriodIndex object.mp4 |
38.78Мб |
| 9. The PeriodIndex object.srt |
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| 9. Transformation with transform().mp4 |
35.41Мб |
| 9. Transformation with transform().srt |
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| 9. User-defined Functions with apply(), map() and applymap().mp4 |
74.33Мб |
| 9. User-defined Functions with apply(), map() and applymap().srt |
16.48Кб |
| 9. Variability around the Central Tendency Dispersion (Theory).mp4 |
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| 9. Variability around the Central Tendency Dispersion (Theory).srt |
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