[DesireCourse.Net] Udemy - The Complete Pandas Bootcamp Master your Data in Python

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[DesireCourse.Net] Udemy - The Complete Pandas Bootcamp Master your Data in Python

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收录时间：2020-03-23
最近下载：2025-03-26

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文件列表

  • 22. Python Basics/7. Data Types Lists (Part 2).mp4 140.9 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/4. Olympic Medal Tables (Solution Part 2).mp4 135.0 MB
  • 22. Python Basics/18. Visualization with Matplotlib.mp4 130.3 MB
  • 19. Time Series Basics/5. Creating a customized DatetimeIndex with pd.date_range().mp4 120.2 MB
  • 3. Pandas Basics (DataFrame Basics I)/5. Coding Exercise 0 Coding the Video Lectures.mp4 114.6 MB
  • 8. Visualization with Matplotlib/3. Customization of Plots.mp4 108.0 MB
  • 14. Reshaping and Pivoting DataFrames/6. pd.crosstab().mp4 104.3 MB
  • 12. Merging, Joining, and Concatenating Data/13. Joining on different Column Names Indexes.mp4 100.0 MB
  • 3. Pandas Basics (DataFrame Basics I)/17. Slicing Rows and Columns with loc (label-based indexing).mp4 95.8 MB
  • 10. Importing Data/1. Importing csv-files with pd.read_csv.mp4 95.3 MB
  • 11. Cleaning Data/5. Detection of missing Values.mp4 93.7 MB
  • 11. Cleaning Data/10. Handling Removing Duplicates.mp4 93.0 MB
  • 12. Merging, Joining, and Concatenating Data/2. Adding Rows with append() and pd.concat() (Part 1).mp4 92.3 MB
  • 1. Getting Started/5. Installation of Anaconda.mp4 90.5 MB
  • 22. Python Basics/11. Conditional Statements (if, elif, else, while).mp4 90.2 MB
  • 19. Time Series Basics/7. Downsampling Time Series with resample() (Part 1).mp4 89.7 MB
  • 11. Cleaning Data/6. Removing missing values.mp4 89.6 MB
  • 15. Data Preparation and Feature Creation/8. Discretization and Binning with pd.qcut().mp4 89.5 MB
  • 16. Advanced Visualization with Seaborn/3. Categorical Plots.mp4 89.3 MB
  • 23. The Numpy Package/11. Visualization and (Linear) Regression.mp4 88.7 MB
  • 13. GroupBy Operations/15. Coding Exercise 13 (Solution).mp4 85.5 MB
  • 11. Cleaning Data/2. String Operations.mp4 84.8 MB
  • 12. Merging, Joining, and Concatenating Data/6. Outer Joins with merge().mp4 84.0 MB
  • 16. Advanced Visualization with Seaborn/4. Joint Plots Regression Plots.mp4 83.5 MB
  • 11. Cleaning Data/9. Detection of Duplicates.mp4 83.1 MB
  • 13. GroupBy Operations/12. stack() and unstack().mp4 82.6 MB
  • 20. Time Series Advanced Financial Time Series/12. Filling NA Values with bfill, ffill and interpolation.mp4 82.3 MB
  • 22. Python Basics/5. Data Types Strings.mp4 81.6 MB
  • 4. Pandas Series and Index Objects/5. EXCURSUS Updating Pandas Anaconda.mp4 80.9 MB
  • 4. Pandas Series and Index Objects/19. Changing Row Index with set_index() and reset_index().mp4 78.7 MB
  • 7. DataFrame Basics III/9. User-defined Functions with apply(), map() and applymap().mp4 77.9 MB
  • 10. Importing Data/4. NEW Importing Data from Excel with pd.read_excel().mp4 77.5 MB
  • 23. The Numpy Package/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4 77.2 MB
  • 15. Data Preparation and Feature Creation/6. Discretization and Binning with pd.cut() (Part 1).mp4 76.6 MB
  • 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 76.3 MB
  • 7. DataFrame Basics III/11. Hierarchical Indexing (Part 2).mp4 76.1 MB
  • 7. DataFrame Basics III/10. Hierarchical Indexing (Part 1).mp4 76.1 MB
  • 10. Importing Data/5. Importing messy Data from Excel with pd.read_excel().mp4 76.0 MB
  • 20. Time Series Advanced Financial Time Series/3. NEW Importing Stock Price Data from Yahoo Finance (it still works!).mp4 75.4 MB
  • 13. GroupBy Operations/5. split-apply-combine applied.mp4 74.1 MB
  • 8. Visualization with Matplotlib/2. The plot() method.mp4 73.7 MB
  • 14. Reshaping and Pivoting DataFrames/2. Transposing Rows and Columns.mp4 71.8 MB
  • 11. Cleaning Data/1. First Inspection & Handling of inconsistent Data.mp4 71.6 MB
  • 23. The Numpy Package/7. Generating Random Numbers.mp4 70.8 MB
  • 1. Getting Started/7. How to use Jupyter Notebooks.mp4 69.5 MB
  • 4. Pandas Series and Index Objects/9. Indexing and Slicing Pandas Series.mp4 69.4 MB
  • 5. DataFrame Basics II/5. Advanced Filtering with between(), isin() and ~.mp4 68.9 MB
  • 1. Getting Started/6. Opening a Jupyter Notebook.mp4 68.2 MB
  • 23. The Numpy Package/2. Numpy Arrays Vectorization.mp4 67.9 MB
  • 22. Python Basics/15. User Defined Functions (Part 1).mp4 67.5 MB
  • 15. Data Preparation and Feature Creation/2. Arithmetic Operations (Part 1).mp4 66.6 MB
  • 10. Importing Data/2. Importing messy csv-files with pd.read_csv.mp4 66.3 MB
  • 3. Pandas Basics (DataFrame Basics I)/9. Explore your own Dataset Coding Exercise 1 (Intro).mp4 66.2 MB
  • 22. Python Basics/6. Data Types Lists (Part 1).mp4 65.7 MB
  • 3. Pandas Basics (DataFrame Basics I)/19. Summary and Outlook.mp4 65.2 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/3. Chained Indexing How you should NOT do it (Part 1).mp4 63.0 MB
  • 22. Python Basics/10. Operators & Booleans.mp4 62.4 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/4. Chained Indexing How you should NOT do it (Part 2).mp4 61.7 MB
  • 15. Data Preparation and Feature Creation/3. Arithmetic Operations (Part 2).mp4 61.3 MB
  • 22. Python Basics/12. For Loops.mp4 61.3 MB
  • 14. Reshaping and Pivoting DataFrames/4. Limits of pivot().mp4 61.1 MB
  • 7. DataFrame Basics III/15. Coding Exercise 8 (Solution).mp4 61.0 MB
  • 14. Reshaping and Pivoting DataFrames/5. pivot_table().mp4 60.9 MB
  • 10. Importing Data/6. Importing Data from the Web with pd.read_html().mp4 60.8 MB
  • 19. Time Series Basics/2. Converting strings to datetime objects with pd.to_datetime().mp4 60.8 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/2. Olympic Medal Tables (Instruction & Hints).mp4 60.5 MB
  • 5. DataFrame Basics II/15. Coding Exercise 5 (Solution).mp4 60.5 MB
  • 7. DataFrame Basics III/5. Summary Statistics and Accumulations.mp4 60.3 MB
  • 22. Python Basics/16. User Defined Functions (Part 2).mp4 60.2 MB
  • 12. Merging, Joining, and Concatenating Data/3. Adding Rows with pd.concat() (Part 2).mp4 59.7 MB
  • 3. Pandas Basics (DataFrame Basics I)/4. First Steps (Inspection of Data, Part 2).mp4 59.5 MB
  • 15. Data Preparation and Feature Creation/10. Scaling Standardization.mp4 59.1 MB
  • 14. Reshaping and Pivoting DataFrames/3. Pivoting DataFrames with pivot().mp4 58.6 MB
  • 15. Data Preparation and Feature Creation/11. Creating Dummy Variables.mp4 57.9 MB
  • 7. DataFrame Basics III/13. String Operations (Part 2).mp4 57.9 MB
  • 3. Pandas Basics (DataFrame Basics I)/7. Make it easy TAB Completion and Tooltip.mp4 57.1 MB
  • 7. DataFrame Basics III/2. Sorting DataFrames with sort_index() and sort_values().mp4 57.0 MB
  • 3. Pandas Basics (DataFrame Basics I)/13. Selecting Rows with iloc (position-based indexing).mp4 56.6 MB
  • 20. Time Series Advanced Financial Time Series/9. Financial Time Series - Return and Risk.mp4 56.2 MB
  • 23. The Numpy Package/3. Numpy Arrays Indexing and Slicing.mp4 56.0 MB
  • 5. DataFrame Basics II/2. Filtering DataFrames by one Condition.mp4 55.5 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/2. Best Practice (How you should do it).mp4 55.2 MB
  • 22. Python Basics/17. User Defined Functions (Part 3).mp4 54.7 MB
  • 10. Importing Data/3. OLD Importing Data from Excel with pd.read_excel().mp4 54.4 MB
  • 3. Pandas Basics (DataFrame Basics I)/3. First Steps (Inspection of Data, Part 1).mp4 54.0 MB
  • 3. Pandas Basics (DataFrame Basics I)/6. Built-in Functions, Attributes and Methods with Pandas.mp4 53.1 MB
  • 19. Time Series Basics/10. Advanced Indexing with reindex().mp4 53.0 MB
  • 13. GroupBy Operations/3. Splitting with many Keys.mp4 52.3 MB
  • 23. The Numpy Package/8. Performance Issues.mp4 52.3 MB
  • 5. DataFrame Basics II/8. Removing Rows.mp4 52.0 MB
  • 22. Python Basics/4. Data Types Integers and Floats.mp4 51.9 MB
  • 14. Reshaping and Pivoting DataFrames/7. melting DataFrames with melt().mp4 51.9 MB
  • 19. Time Series Basics/8. Downsampling Time Series with resample (Part 2).mp4 51.5 MB
  • 1. Getting Started/1. Overview Student FAQ.mp4 50.8 MB
  • 19. Time Series Basics/4. Indexing and Slicing Time Series.mp4 50.5 MB
  • 13. GroupBy Operations/4. split-apply-combine explained.mp4 49.4 MB
  • 13. GroupBy Operations/2. Understanding the GroupBy Object.mp4 48.5 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/6. Simple Rules what to do when....mp4 48.1 MB
  • 11. Cleaning Data/4. Intro NA values missing values.mp4 47.9 MB
  • 23. The Numpy Package/9. Case Study Numpy vs. Python Standard Library.mp4 47.8 MB
  • 11. Cleaning Data/13. Categorical Data.mp4 47.7 MB
  • 23. The Numpy Package/13. Numpy Quiz Solution.mp4 47.7 MB
  • 23. The Numpy Package/10. Summary Statistics.mp4 47.0 MB
  • 13. GroupBy Operations/9. Replacing NA Values by group-specific Values.mp4 46.9 MB
  • 20. Time Series Advanced Financial Time Series/11. Helpful DatetimeIndex Attributes and Methods.mp4 46.5 MB
  • 20. Time Series Advanced Financial Time Series/5. Normalizing Time Series to a Base Value (100).mp4 46.4 MB
  • 23. The Numpy Package/6. Numpy Arrays Boolean Indexing.mp4 46.4 MB
  • 11. Cleaning Data/11. Detection of Outliers.mp4 46.2 MB
  • 20. Time Series Advanced Financial Time Series/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 46.0 MB
  • 1. Getting Started/2. Tips How to get the most out of this course.mp4 45.7 MB
  • 7. DataFrame Basics III/3. Ranking DataFrames with rank().mp4 45.6 MB
  • 4. Pandas Series and Index Objects/17. First Steps with Pandas Index Objects.mp4 45.2 MB
  • 4. Pandas Series and Index Objects/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 45.0 MB
  • 16. Advanced Visualization with Seaborn/5. Matrixplots Heatmaps.mp4 44.9 MB
  • 13. GroupBy Operations/10. Generalizing split-apply-combine with apply().mp4 44.9 MB
  • 15. Data Preparation and Feature Creation/4. TransformationMapping with map().mp4 44.8 MB
  • 20. Time Series Advanced Financial Time Series/4. Initial Inspection and Visualization.mp4 44.4 MB
  • 22. Python Basics/8. Data Types Tuples.mp4 43.8 MB
  • 19. Time Series Basics/1. Importing Time Series Data from csv-files.mp4 43.8 MB
  • 4. Pandas Series and Index Objects/10. Sorting of Series and Introduction to the inplace - parameter.mp4 43.4 MB
  • 7. DataFrame Basics III/12. String Operations (Part 1).mp4 43.2 MB
  • 23. The Numpy Package/1. Introduction to Numpy Arrays.mp4 43.1 MB
  • 20. Time Series Advanced Financial Time Series/7. The methods diff() and pct_change().mp4 42.2 MB
  • 7. DataFrame Basics III/8. Coding Exercise 7 (Solution).mp4 41.7 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/9. Coding Exercise 6 (Solution).mp4 41.3 MB
  • 15. Data Preparation and Feature Creation/9. Floors and Caps.mp4 41.2 MB
  • 3. Pandas Basics (DataFrame Basics I)/22. Coding Exercise 2 (Solution).mp4 41.0 MB
  • 12. Merging, Joining, and Concatenating Data/4. Arithmetic with Pandas Objects Data Alignment.mp4 40.8 MB
  • 11. Cleaning Data/3. Changing Datatype of Columns with astype().mp4 40.7 MB
  • 19. Time Series Basics/9. The PeriodIndex object.mp4 40.7 MB
  • 12. Merging, Joining, and Concatenating Data/14. Joining on more than one Column.mp4 40.6 MB
  • 4. Pandas Series and Index Objects/16. Coding Exercise 3 (Solution).mp4 40.5 MB
  • 3. Pandas Basics (DataFrame Basics I)/11. Selecting Columns.mp4 40.4 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/3. Olympic Medal Tables (Solution Part 1).mp4 40.3 MB
  • 22. Python Basics/20. Python Basics Quiz Solution.mp4 40.1 MB
  • 22. Python Basics/14. Generating Random Numbers.mp4 40.0 MB
  • 4. Pandas Series and Index Objects/7. Creating Pandas Series (Part 1).mp4 39.9 MB
  • 4. Pandas Series and Index Objects/13. Manipulating Pandas Series.mp4 39.7 MB
  • 8. Visualization with Matplotlib/9. Coding Exercise 9 (Solution).mp4 38.6 MB
  • 22. Python Basics/13. Key words break, pass, continue.mp4 38.5 MB
  • 8. Visualization with Matplotlib/7. Scatterplots.mp4 37.9 MB
  • 5. DataFrame Basics II/7. Removing Columns.mp4 37.8 MB
  • 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.mp4 37.7 MB
  • 20. Time Series Advanced Financial Time Series/6. The shift() method.mp4 37.5 MB
  • 23. The Numpy Package/4. Numpy Arrays Shape and Dimensions.mp4 37.2 MB
  • 12. Merging, Joining, and Concatenating Data/15. pd.merge() and join().mp4 37.2 MB
  • 13. GroupBy Operations/8. Transformation with transform().mp4 37.1 MB
  • 19. Time Series Basics/3. Initial Analysis Visualization of Time Series.mp4 36.7 MB
  • 5. DataFrame Basics II/10. Creating Columns based on other Columns.mp4 36.2 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/5. View vs. Copy.mp4 36.2 MB
  • 22. Python Basics/2. First Steps.mp4 35.9 MB
  • 8. Visualization with Matplotlib/5. Histograms (Part 2).mp4 35.8 MB
  • 4. Pandas Series and Index Objects/21. Renaming Index & Column Labels with rename().mp4 35.2 MB
  • 15. Data Preparation and Feature Creation/5. Conditional Transformation.mp4 35.0 MB
  • 13. GroupBy Operations/11. Hierarchical Indexing with Groupby.mp4 34.5 MB
  • 15. Data Preparation and Feature Creation/7. Discretization and Binning with pd.cut() (Part 2).mp4 34.3 MB
  • 7. DataFrame Basics III/4. nunique() and nlargest() nsmallest() with DataFrames.mp4 34.2 MB
  • 12. Merging, Joining, and Concatenating Data/8. Outer Joins (without Intersection) with merge().mp4 33.0 MB
  • 22. Python Basics/3. Variables.mp4 33.0 MB
  • 1. Getting Started/3. Did you know that....mp4 32.8 MB
  • 5. DataFrame Basics II/4. Filtering DataFrames by many Conditions (OR).mp4 32.3 MB
  • 3. Pandas Basics (DataFrame Basics I)/16. Selecting Rows with loc (label-based indexing).mp4 31.8 MB
  • 13. GroupBy Operations/7. Advanced aggregation with agg().mp4 31.7 MB
  • 3. Pandas Basics (DataFrame Basics I)/10. Explore your own Dataset Coding Exercise 1 (Solution).mp4 31.3 MB
  • 11. Cleaning Data/12. Handling Removing Outliers.mp4 31.1 MB
  • 15. Data Preparation and Feature Creation/12. String Operations.mp4 31.1 MB
  • 4. Pandas Series and Index Objects/12. idxmin() and idxmax().mp4 30.1 MB
  • 12. Merging, Joining, and Concatenating Data/12. Right Joins with merge().mp4 28.7 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/5. Olympic Medal Tables (Solution Part 3).mp4 28.3 MB
  • 4. Pandas Series and Index Objects/8. Creating Pandas Series (Part 2).mp4 28.0 MB
  • 4. Pandas Series and Index Objects/24. Coding Exercise 4 (Solution).mp4 27.6 MB
  • 3. Pandas Basics (DataFrame Basics I)/14. Slicing Rows and Columns with iloc (position-based indexing).mp4 27.2 MB
  • 5. DataFrame Basics II/3. Filtering DataFrames by many Conditions (AND).mp4 27.2 MB
  • 3. Pandas Basics (DataFrame Basics I)/1. Intro to Tabular Data Pandas.mp4 27.1 MB
  • 20. Time Series Advanced Financial Time Series/10. Financial Time Series - Covariance and Correlation.mp4 27.0 MB
  • 11. Cleaning Data/7. Replacing missing values.mp4 25.8 MB
  • 8. Visualization with Matplotlib/4. Histograms (Part 1).mp4 25.8 MB
  • 12. Merging, Joining, and Concatenating Data/11. Left Joins with merge().mp4 25.2 MB
  • 7. DataFrame Basics III/6. The agg() method.mp4 23.9 MB
  • 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.mp4 23.2 MB
  • 3. Pandas Basics (DataFrame Basics I)/12. Selecting Rows with Square Brackets (not advisable).mp4 23.1 MB
  • 12. Merging, Joining, and Concatenating Data/9. Left Joins (without Intersection) with merge().mp4 22.9 MB
  • 20. Time Series Advanced Financial Time Series/2. NEW Getting Ready (Installing required package).mp4 22.8 MB
  • 22. Python Basics/9. Data Types Sets.mp4 22.5 MB
  • 4. Pandas Series and Index Objects/20. Changing Column Labels.mp4 22.2 MB
  • 11. Cleaning Data/8. Intro Duplicates.mp4 21.2 MB
  • 8. Visualization with Matplotlib/6. Barcharts and Piecharts.mp4 21.0 MB
  • 5. DataFrame Basics II/9. Adding new Columns to a DataFrame.mp4 18.7 MB
  • 5. DataFrame Basics II/6. any() and all().mp4 18.4 MB
  • 4. Pandas Series and Index Objects/11. nlargest() and nsmallest().mp4 17.6 MB
  • 12. Merging, Joining, and Concatenating Data/7. Inner Joins with merge().mp4 16.3 MB
  • 12. Merging, Joining, and Concatenating Data/10. Right Joins (without Intersection) with merge().mp4 15.8 MB
  • 15. Data Preparation and Feature Creation/13. Coding Exercise 15 (Intro).mp4 15.8 MB
  • 4. Pandas Series and Index Objects/18. Creating Index Objects from Scratch.mp4 15.8 MB
  • 3. Pandas Basics (DataFrame Basics I)/9.1 Pandas-Bootcamp-exc.zip.zip 15.7 MB
  • 4. Pandas Series and Index Objects/15. Coding Exercise 3 (Intro).mp4 14.8 MB
  • 5. DataFrame Basics II/11. Adding Columns with insert().mp4 13.7 MB
  • 10. Importing Data/7. Coding Exercise 10 (Intro).mp4 13.0 MB
  • 19. Time Series Basics/6. More on pd.date_range().mp4 13.0 MB
  • 13. GroupBy Operations/14. Coding Exercise 13 (Intro).mp4 12.4 MB
  • 11. Cleaning Data/14. Coding Exercise 11 (Intro).mp4 11.4 MB
  • 20. Time Series Advanced Financial Time Series/13. Coding Exercise 17 (Intro).mp4 11.3 MB
  • 5. DataFrame Basics II/14. Coding Exercise 5 (Intro).mp4 11.3 MB
  • 13. GroupBy Operations/1. Intro.mp4 10.6 MB
  • 7. DataFrame Basics III/7. Coding Exercise 7 (Intro).mp4 10.5 MB
  • 8. Visualization with Matplotlib/8. Coding Exercise 9 (Intro).mp4 10.1 MB
  • 4. Pandas Series and Index Objects/23. Coding Exercise 4 (Intro).mp4 9.4 MB
  • 16. Advanced Visualization with Seaborn/6. Coding Exercise 16 (Intro).mp4 9.4 MB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/8. Coding Exercise 6 (Intro).mp4 9.2 MB
  • 3. Pandas Basics (DataFrame Basics I)/21. Coding Exercise 2 (Intro).mp4 9.0 MB
  • 12. Merging, Joining, and Concatenating Data/16. Coding Exercise 12 (Intro).mp4 9.0 MB
  • 7. DataFrame Basics III/14. Coding Exercise 8 (Intro).mp4 8.6 MB
  • 14. Reshaping and Pivoting DataFrames/8. Coding Exercsie 14 (Intro).mp4 7.1 MB
  • 22. Python Basics/1. Intro.mp4 6.2 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/1. Olympic Medal Tables (Intro).mp4 4.7 MB
  • 3. Pandas Basics (DataFrame Basics I)/5.1 Video_Lecture_NBs.zip.zip 3.6 MB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/4. Olympic Medal Tables (Solution Part 2).vtt 20.4 kB
  • 14. Reshaping and Pivoting DataFrames/6. pd.crosstab().vtt 19.1 kB
  • 22. Python Basics/7. Data Types Lists (Part 2).vtt 18.5 kB
  • 3. Pandas Basics (DataFrame Basics I)/5. Coding Exercise 0 Coding the Video Lectures.vtt 16.7 kB
  • 11. Cleaning Data/6. Removing missing values.vtt 16.5 kB
  • 19. Time Series Basics/5. Creating a customized DatetimeIndex with pd.date_range().vtt 16.1 kB
  • 11. Cleaning Data/5. Detection of missing Values.vtt 15.5 kB
  • 16. Advanced Visualization with Seaborn/3. Categorical Plots.vtt 15.2 kB
  • 1. Getting Started/7. How to use Jupyter Notebooks.vtt 15.2 kB
  • 22. Python Basics/18. Visualization with Matplotlib.vtt 14.8 kB
  • 13. GroupBy Operations/12. stack() and unstack().vtt 14.8 kB
  • 7. DataFrame Basics III/9. User-defined Functions with apply(), map() and applymap().vtt 14.8 kB
  • 12. Merging, Joining, and Concatenating Data/13. Joining on different Column Names Indexes.vtt 14.7 kB
  • 19. Time Series Basics/7. Downsampling Time Series with resample() (Part 1).vtt 14.7 kB
  • 23. The Numpy Package/13. Numpy Quiz Solution.vtt 14.7 kB
  • 15. Data Preparation and Feature Creation/8. Discretization and Binning with pd.qcut().vtt 14.5 kB
  • 12. Merging, Joining, and Concatenating Data/6. Outer Joins with merge().vtt 14.1 kB
  • 14. Reshaping and Pivoting DataFrames/5. pivot_table().vtt 14.1 kB
  • 12. Merging, Joining, and Concatenating Data/2. Adding Rows with append() and pd.concat() (Part 1).vtt 14.0 kB
  • 11. Cleaning Data/10. Handling Removing Duplicates.vtt 13.9 kB
  • 22. Python Basics/11. Conditional Statements (if, elif, else, while).vtt 13.7 kB
  • 13. GroupBy Operations/15. Coding Exercise 13 (Solution).vtt 13.6 kB
  • 11. Cleaning Data/9. Detection of Duplicates.vtt 13.5 kB
  • 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().vtt 13.2 kB
  • 11. Cleaning Data/2. String Operations.vtt 13.2 kB
  • 15. Data Preparation and Feature Creation/2. Arithmetic Operations (Part 1).vtt 13.2 kB
  • 7. DataFrame Basics III/11. Hierarchical Indexing (Part 2).vtt 13.1 kB
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  • 10. Importing Data/4. NEW Importing Data from Excel with pd.read_excel().vtt 12.9 kB
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  • 22. Python Basics/10. Operators & Booleans.vtt 9.9 kB
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  • 23. The Numpy Package/7. Generating Random Numbers.vtt 9.0 kB
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  • 23. The Numpy Package/2. Numpy Arrays Vectorization.vtt 8.9 kB
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  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/6. Simple Rules what to do when....vtt 8.8 kB
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  • 22. Python Basics/6. Data Types Lists (Part 1).vtt 8.7 kB
  • 19. Time Series Basics/1. Importing Time Series Data from csv-files.vtt 8.7 kB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/2. Olympic Medal Tables (Instruction & Hints).vtt 8.5 kB
  • 4. Pandas Series and Index Objects/13. Manipulating Pandas Series.vtt 8.4 kB
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  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/4. Chained Indexing How you should NOT do it (Part 2).vtt 8.4 kB
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  • 5. DataFrame Basics II/5. Advanced Filtering with between(), isin() and ~.vtt 8.1 kB
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  • 23. The Numpy Package/10. Summary Statistics.vtt 7.6 kB
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  • 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.vtt 7.2 kB
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  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/9. Coding Exercise 6 (Solution).vtt 6.5 kB
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  • 22. Python Basics/13. Key words break, pass, continue.vtt 6.5 kB
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  • 20. Time Series Advanced Financial Time Series/11. Helpful DatetimeIndex Attributes and Methods.vtt 6.4 kB
  • 4. Pandas Series and Index Objects/5. EXCURSUS Updating Pandas Anaconda.vtt 6.4 kB
  • 19. Time Series Basics/9. The PeriodIndex object.vtt 6.4 kB
  • 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.vtt 6.3 kB
  • 23. The Numpy Package/6. Numpy Arrays Boolean Indexing.vtt 6.3 kB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/5. View vs. Copy.vtt 6.3 kB
  • 13. GroupBy Operations/7. Advanced aggregation with agg().vtt 6.2 kB
  • 12. Merging, Joining, and Concatenating Data/15. pd.merge() and join().vtt 6.2 kB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/5. Olympic Medal Tables (Solution Part 3).vtt 6.2 kB
  • 23. The Numpy Package/4. Numpy Arrays Shape and Dimensions.vtt 6.2 kB
  • 23. The Numpy Package/8. Performance Issues.vtt 6.2 kB
  • 11. Cleaning Data/12. Handling Removing Outliers.vtt 6.2 kB
  • 19. Time Series Basics/3. Initial Analysis Visualization of Time Series.vtt 6.1 kB
  • 3. Pandas Basics (DataFrame Basics I)/3. First Steps (Inspection of Data, Part 1).vtt 6.0 kB
  • 4. Pandas Series and Index Objects/17. First Steps with Pandas Index Objects.vtt 6.0 kB
  • 1. Getting Started/2. Tips How to get the most out of this course.vtt 6.0 kB
  • 4. Pandas Series and Index Objects/8. Creating Pandas Series (Part 2).vtt 5.9 kB
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/3. Olympic Medal Tables (Solution Part 1).vtt 5.9 kB
  • 3. Pandas Basics (DataFrame Basics I)/16. Selecting Rows with loc (label-based indexing).vtt 5.7 kB
  • 11. Cleaning Data/8. Intro Duplicates.vtt 5.7 kB
  • 7. DataFrame Basics III/4. nunique() and nlargest() nsmallest() with DataFrames.vtt 5.7 kB
  • 1. Getting Started/4. More FAQ Important Information.html 5.6 kB
  • 15. Data Preparation and Feature Creation/7. Discretization and Binning with pd.cut() (Part 2).vtt 5.5 kB
  • 4. Pandas Series and Index Objects/12. idxmin() and idxmax().vtt 5.5 kB
  • 3. Pandas Basics (DataFrame Basics I)/14. Slicing Rows and Columns with iloc (position-based indexing).vtt 5.5 kB
  • 5. DataFrame Basics II/7. Removing Columns.vtt 5.5 kB
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  • 5. DataFrame Basics II/9. Adding new Columns to a DataFrame.vtt 3.5 kB
  • 12. Merging, Joining, and Concatenating Data/9. Left Joins (without Intersection) with merge().vtt 3.5 kB
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  • 22. Python Basics/1. Intro.vtt 2.6 kB
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  • 24. Bonus/1. Bonus.html 1.5 kB
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  • 7. DataFrame Basics III/7. Coding Exercise 7 (Intro).vtt 1.3 kB
  • 12. Merging, Joining, and Concatenating Data/16. Coding Exercise 12 (Intro).vtt 1.3 kB
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  • 7. DataFrame Basics III/14. Coding Exercise 8 (Intro).vtt 1.1 kB
  • 16. Advanced Visualization with Seaborn/6. Coding Exercise 16 (Intro).vtt 1.1 kB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/1. Intro.html 1.0 kB
  • 20. Time Series Advanced Financial Time Series/1. Intro.html 976 Bytes
  • 14. Reshaping and Pivoting DataFrames/8. Coding Exercsie 14 (Intro).vtt 968 Bytes
  • 14. Reshaping and Pivoting DataFrames/1. Intro.html 894 Bytes
  • 4. Pandas Series and Index Objects/1. Intro.html 838 Bytes
  • 9. -----PART II FULL DATA WORKFLOW A-Z------/1. Welcome to PART II Full Data Analysis Workflow.html 818 Bytes
  • 16. Advanced Visualization with Seaborn/1. Intro.html 775 Bytes
  • 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/1. Olympic Medal Tables (Intro).vtt 748 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/18. Label-based Indexing Cheat Sheets.html 711 Bytes
  • 15. Data Preparation and Feature Creation/1. Intro.html 710 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/15. Position-based Indexing Cheat Sheets.html 700 Bytes
  • 8. Visualization with Matplotlib/1. Intro.html 680 Bytes
  • 18. --------PART IV MANAGING TIME SERIES DATA WITH PANDAS----------/1. Welcome to Part III Time Series Data.html 660 Bytes
  • 7. DataFrame Basics III/1. Intro.html 643 Bytes
  • 2. --------PART I BUILDING BLOCKS--------/1. Welcome to PART I - Pandas Building Blocks.html 606 Bytes
  • 12. Merging, Joining, and Concatenating Data/1. Intro.html 585 Bytes
  • 21. ------APPENDIX PYTHON BASICS AND NUMPY--------/1. Welcome to the Appendix.html 429 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/2. Tabular Data Cheat Sheets.html 421 Bytes
  • 10. Importing Data/8. Coding Exercise 10 (Solution).html 406 Bytes
  • 5. DataFrame Basics II/1. Intro.html 406 Bytes
  • 11. Cleaning Data/15. Coding Exercise 11 (Solution).html 398 Bytes
  • 12. Merging, Joining, and Concatenating Data/17. Coding Exercise 12 (Solution).html 398 Bytes
  • 14. Reshaping and Pivoting DataFrames/9. Coding Exercise 14 (Solution).html 398 Bytes
  • 15. Data Preparation and Feature Creation/14. Coding Exercise 15 (Solution).html 398 Bytes
  • 16. Advanced Visualization with Seaborn/7. Coding Exercise 16 (Solution).html 398 Bytes
  • 20. Time Series Advanced Financial Time Series/14. Coding Exercise 17 (Solution).html 398 Bytes
  • 4. Pandas Series and Index Objects/4. UPDATE Pandas Version 0.24.0 (Jan 2019).html 369 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/6.1 DataFrame Methods and Attributes.html 141 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/6.2 Pandas Series Methods and Attributes.html 138 Bytes
  • 13. GroupBy Operations/13. GroupBy 2.html 123 Bytes
  • 13. GroupBy Operations/6. GroupBy 1.html 123 Bytes
  • 22. Python Basics/19. Python Basics.html 123 Bytes
  • 23. The Numpy Package/12. Numpy.html 123 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/20. Indexing and Slicing.html 123 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/8. First Steps.html 123 Bytes
  • 4. Pandas Series and Index Objects/14. Pandas Series.html 123 Bytes
  • 4. Pandas Series and Index Objects/22. Pandas Index objects.html 123 Bytes
  • 5. DataFrame Basics II/13. DataFrame Basics II.html 123 Bytes
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/7. Manipulating DataFrames Slices.html 123 Bytes
  • 4. Pandas Series and Index Objects/5.1 Updating Anaconda (Link).html 119 Bytes
  • 1. Getting Started/5.1 Installing on Windows.html 112 Bytes
  • 1. Getting Started/5.2 Installing on macOS.html 111 Bytes
  • 1. Getting Started/5.3 Installing on Linux.html 110 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • [CourseClub.Me].url 48 Bytes

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