[DesireCourse.Net] Udemy - The Complete Pandas Bootcamp 2020 Data Science with Python

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[DesireCourse.Net] Udemy - The Complete Pandas Bootcamp 2020 Data Science with Python

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收录时间：2021-04-10
最近下载：2025-07-24

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文件列表

  • 23. Python Basics/7. Data Types Lists (Part 2).mp4 140.9 MB
  • 11. Cleaning Data/17. Coding Exercise 11 (Solution).mp4 136.0 MB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/4. Olympic Medal Tables (Solution Part 2).mp4 135.0 MB
  • 23. 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
  • 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
  • 25. Statistical Concepts/1. Statistics - Overview, Terms and Vocabulary.mp4 97.9 MB
  • 10. Importing Data/1. Importing csv-files with pd.read_csv.mp4 95.4 MB
  • 11. Cleaning Data/5. Detection of missing Values.mp4 93.7 MB
  • 11. Cleaning Data/10. Handling Removing Duplicates.srt 93.0 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
  • 23. 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
  • 24. The Numpy Package/11. Visualization and (Linear) Regression.mp4 88.7 MB
  • 13. GroupBy Operations/16. 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/13. 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
  • 23. Python Basics/5. Data Types Strings.mp4 81.6 MB
  • 3. Pandas Basics (DataFrame Basics I)/16. Slicing Rows and Columns with loc (label-based indexing).mp4 81.3 MB
  • 4. Pandas Series and Index Objects/17. 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/3. Importing Data from Excel with pd.read_excel().mp4 77.5 MB
  • 24. 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
  • 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/4. Importing messy Data from Excel with pd.read_excel().mp4 76.0 MB
  • 20. Time Series Advanced Financial Time Series/3. 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
  • 7. DataFrame Basics III/2. Sorting DataFrames with sort_index() and sort_values() (Version 1.0 Update).mp4 72.2 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
  • 24. The Numpy Package/7. Generating Random Numbers.mp4 70.8 MB
  • 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 70.4 MB
  • 1. Getting Started/7. How to use Jupyter Notebooks.mp4 69.5 MB
  • 4. Pandas Series and Index Objects/7. 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
  • 3. Pandas Basics (DataFrame Basics I)/12. Selecting Rows with iloc (position-based indexing).mp4 68.2 MB
  • 24. The Numpy Package/2. Numpy Arrays Vectorization.mp4 67.9 MB
  • 23. 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
  • 23. Python Basics/6. Data Types Lists (Part 1).mp4 65.7 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
  • 23. Python Basics/10. Operators & Booleans.mp4 62.4 MB
  • 3. Pandas Basics (DataFrame Basics I)/1. Create your very first Pandas DataFrame (from csv).mp4 62.3 MB
  • 25. Statistical Concepts/26. Probabilities and Z-Values with scipy.stats.mp4 62.2 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
  • 23. 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 61.1 MB
  • 14. Reshaping and Pivoting DataFrames/5. pivot_table().mp4 60.9 MB
  • 10. Importing Data/5. 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 3 COMPREHENSIVE PROJECT CHALLENGE---/2. Olympic Medal Tables (Instruction & Hints).mp4 60.5 MB
  • 5. DataFrame Basics II/16. Coding Exercise 5 (Solution).mp4 60.5 MB
  • 7. DataFrame Basics III/5. Summary Statistics and Accumulations.mp4 60.3 MB
  • 23. 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
  • 15. Data Preparation and Feature Creation/10. Scaling Standardization.mp4 59.1 MB
  • 3. Pandas Basics (DataFrame Basics I)/3. First Data Inspection.mp4 58.7 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)/5. Make it easy TAB Completion and Tooltip.mp4 57.1 MB
  • 20. Time Series Advanced Financial Time Series/9. Financial Time Series - Return and Risk.mp4 56.2 MB
  • 24. 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
  • 23. Python Basics/17. User Defined Functions (Part 3).mp4 54.7 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
  • 24. The Numpy Package/8. Performance Issues.mp4 52.3 MB
  • 5. DataFrame Basics II/8. Removing Rows.mp4 52.0 MB
  • 23. 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
  • 25. Statistical Concepts/27. Confidence Intervals with scipy.stats.mp4 50.4 MB
  • 13. GroupBy Operations/4. split-apply-combine explained.mp4 49.4 MB
  • 25. Statistical Concepts/29. Cleaning and preparing the Data - Movies Database (Part 1).mp4 49.3 MB
  • 3. Pandas Basics (DataFrame Basics I)/4. Built-in Functions, Attributes and Methods with Pandas.mp4 49.2 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
  • 24. The Numpy Package/9. Case Study Numpy vs. Python Standard Library.mp4 47.8 MB
  • 11. Cleaning Data/14. Categorical Data.mp4 47.7 MB
  • 24. The Numpy Package/13. Numpy Quiz Solution.mp4 47.7 MB
  • 24. The Numpy Package/10. Summary Statistics.mp4 47.0 MB
  • 13. GroupBy Operations/10. 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
  • 24. The Numpy Package/6. Numpy Arrays Boolean Indexing.mp4 46.4 MB
  • 11. Cleaning Data/12. 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 46.1 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
  • 5. DataFrame Basics II/12. Creating DataFrames from Scratch with pd.DataFrame().mp4 45.4 MB
  • 4. Pandas Series and Index Objects/15. First Steps with Pandas Index Objects.mp4 45.2 MB
  • 4. Pandas Series and Index Objects/4. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 45.0 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/13. Removal of prior Version Deprecations.mp4 45.0 MB
  • 16. Advanced Visualization with Seaborn/5. Matrixplots Heatmaps.mp4 44.9 MB
  • 13. GroupBy Operations/11. 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
  • 3. Pandas Basics (DataFrame Basics I)/19. Summary, Best Practices and Outlook.mp4 44.0 MB
  • 23. 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/8. 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
  • 24. The Numpy Package/1. Introduction to Numpy Arrays.mp4 43.1 MB
  • 3. Pandas Basics (DataFrame Basics I)/2. Pandas Display Options and the methods head() & tail().mp4 42.4 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
  • 25. Statistical Concepts/34. A simple Linear Regression Model with numpy & Scipy.mp4 41.6 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)/18. Indexing and Slicing with reindex().mp4 40.8 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
  • 25. Statistical Concepts/24. The Standard Normal Distribution and Z-Values.mp4 40.5 MB
  • 4. Pandas Series and Index Objects/14. Coding Exercise 3 (Solution).mp4 40.5 MB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/3. Olympic Medal Tables (Solution Part 1).mp4 40.3 MB
  • 23. Python Basics/20. Python Basics Quiz Solution.mp4 40.1 MB
  • 23. Python Basics/14. Generating Random Numbers.mp4 40.0 MB
  • 4. Pandas Series and Index Objects/5. Creating Pandas Series (Part 1).mp4 39.9 MB
  • 4. Pandas Series and Index Objects/11. Manipulating Pandas Series.mp4 39.7 MB
  • 8. Visualization with Matplotlib/9. Coding Exercise 9 (Solution).mp4 38.6 MB
  • 23. Python Basics/13. Key words break, pass, continue.mp4 38.5 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/4. Important Recap Pandas Display Options (Changed in Version 0.25).mp4 38.3 MB
  • 25. Statistical Concepts/5. Relative and Cumulative Frequencies with plt.hist().mp4 38.2 MB
  • 8. Visualization with Matplotlib/7. Scatterplots.mp4 37.9 MB
  • 5. DataFrame Basics II/7. Removing Columns.mp4 37.8 MB
  • 20. Time Series Advanced Financial Time Series/6. The shift() method.mp4 37.5 MB
  • 25. Statistical Concepts/17. Probability Distributions - Overview.mp4 37.4 MB
  • 25. Statistical Concepts/3. Population vs. Sample.mp4 37.3 MB
  • 24. 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/9. 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
  • 23. Python Basics/2. First Steps.mp4 35.9 MB
  • 8. Visualization with Matplotlib/5. Histograms (Part 2).mp4 35.8 MB
  • 3. Pandas Basics (DataFrame Basics I)/23. Advanced Indexing and Slicing (optional).mp4 35.8 MB
  • 15. Data Preparation and Feature Creation/5. Conditional Transformation.mp4 35.0 MB
  • 13. GroupBy Operations/12. 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
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/10. The NEW StringDtype.mp4 33.7 MB
  • 12. Merging, Joining, and Concatenating Data/8. Outer Joins (without Intersection) with merge().mp4 33.0 MB
  • 23. Python Basics/3. Variables.mp4 33.0 MB
  • 1. Getting Started/3. Did you know that....mp4 32.8 MB
  • 3. Pandas Basics (DataFrame Basics I)/8. Explore your own Dataset Coding Exercise 1 (Solution).mp4 32.7 MB
  • 25. Statistical Concepts/30. Cleaning and preparing the Data - Movies Database (Part 2).mp4 32.6 MB
  • 5. DataFrame Basics II/4. Filtering DataFrames by many Conditions (OR).mp4 32.3 MB
  • 13. GroupBy Operations/7. Advanced aggregation with agg().mp4 31.7 MB
  • 11. Cleaning Data/13. 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/10. idxmin() and idxmax().mp4 30.1 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/6. NEW Extension dtypes (nullable dtypes) Why do we need them.mp4 29.7 MB
  • 25. Statistical Concepts/18. Discrete Uniform Distributions.mp4 29.6 MB
  • 3. Pandas Basics (DataFrame Basics I)/22. Coding Exercise 2 (Solution).mp4 29.4 MB
  • 4. Pandas Series and Index Objects/19. Renaming Index & Column Labels with rename().mp4 29.4 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/8. NEW pd.NA value for missing values.mp4 29.3 MB
  • 25. Statistical Concepts/9. Variability around the Central Tendency Dispersion (Theory).mp4 29.0 MB
  • 25. Statistical Concepts/28. Covariance and Correlation Coefficient (Theory).mp4 28.9 MB
  • 25. Statistical Concepts/14. How to calculate Skew and Kurtosis with scipy.stats.mp4 28.8 MB
  • 12. Merging, Joining, and Concatenating Data/12. Right Joins with merge().mp4 28.7 MB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/5. Olympic Medal Tables (Solution Part 3).mp4 28.3 MB
  • 25. Statistical Concepts/22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4 28.3 MB
  • 4. Pandas Series and Index Objects/6. Creating Pandas Series (Part 2).mp4 28.0 MB
  • 3. Pandas Basics (DataFrame Basics I)/9. Selecting Columns.mp4 27.9 MB
  • 3. Pandas Basics (DataFrame Basics I)/7. Explore your own Dataset Coding Exercise 1 (Intro).mp4 27.8 MB
  • 4. Pandas Series and Index Objects/22. Coding Exercise 4 (Solution).mp4 27.6 MB
  • 25. Statistical Concepts/36. Case Study (Part 1) The Market Model (Single Factor Model).mp4 27.6 MB
  • 5. DataFrame Basics II/3. Filtering DataFrames by many Conditions (AND).mp4 27.2 MB
  • 20. Time Series Advanced Financial Time Series/10. Financial Time Series - Covariance and Correlation.mp4 27.0 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/7. Creating the NEW extension dtypes with convert_dtypes().mp4 26.9 MB
  • 25. Statistical Concepts/15. How to generate Random Numbers with Numpy.mp4 26.4 MB
  • 11. Cleaning Data/7. Replacing missing values.mp4 25.8 MB
  • 8. Visualization with Matplotlib/4. Histograms (Part 1).mp4 25.8 MB
  • 3. Pandas Basics (DataFrame Basics I)/13. Slicing Rows and Columns with iloc (position-based indexing).mp4 25.5 MB
  • 25. Statistical Concepts/21. Creating a normally distributed Random Variable.mp4 25.3 MB
  • 12. Merging, Joining, and Concatenating Data/11. Left Joins with merge().mp4 25.3 MB
  • 25. Statistical Concepts/31. How to calculate Covariance and Correlation in Python.mp4 25.2 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/11. The NEW nullable BooleanDtype.mp4 24.3 MB
  • 7. DataFrame Basics III/6. The agg() method.mp4 23.9 MB
  • 25. Statistical Concepts/4. Visualizing Frequency Distributions with plt.hist().mp4 23.7 MB
  • 25. Statistical Concepts/7. Coding Measures of Central Tendency - Mean and Median.mp4 23.4 MB
  • 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.mp4 23.2 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. Getting Ready (Installing required package).mp4 22.8 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/12. Addition of the ignore_index parameter.mp4 22.8 MB
  • 23. Python Basics/9. Data Types Sets.mp4 22.5 MB
  • 3. Pandas Basics (DataFrame Basics I)/15. Selecting Rows with loc (label-based indexing).mp4 22.4 MB
  • 4. Pandas Series and Index Objects/18. Changing Column Labels.mp4 22.2 MB
  • 25. Statistical Concepts/6. Measures of Central Tendency (Theory).mp4 21.7 MB
  • 13. GroupBy Operations/8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).mp4 21.6 MB
  • 11. Cleaning Data/8. Intro Duplicates.mp4 21.2 MB
  • 25. Statistical Concepts/19. Continuous Uniform Distributions.mp4 21.1 MB
  • 25. Statistical Concepts/32. Correlation and Scatterplots – visual Interpretation.mp4 21.0 MB
  • 8. Visualization with Matplotlib/6. Barcharts and Piecharts.mp4 21.0 MB
  • 1. Getting Started/8. How to tackle Pandas Version 1.0.mp4 20.0 MB
  • 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.mp4 19.9 MB
  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/2. Download Part 1 Course Materials.mp4 19.6 MB
  • 11. Cleaning Data/15. Pandas Version 1.0 New dtypes and pd.NA.mp4 19.4 MB
  • 25. Statistical Concepts/20. The Normal Distribution (Theory).mp4 19.3 MB
  • 11. Cleaning Data/15. Pandas Version 1.0 New dtypes and pd.NA.srt 19.2 MB
  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/1. Intro to Tabular Data Pandas.mp4 19.0 MB
  • 25. Statistical Concepts/13. Skew and Kurtosis (Theory).mp4 18.9 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/9. The NEW nullable Int64Dtype.mp4 18.9 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
  • 25. Statistical Concepts/11. Percentiles with PythonNumpy.mp4 18.4 MB
  • 25. Statistical Concepts/16. Reproducibility with np.random.seed().mp4 18.1 MB
  • 5. DataFrame Basics II/13. Adding new Rows (hands-on approach).mp4 17.8 MB
  • 4. Pandas Series and Index Objects/9. nlargest() and nsmallest().mp4 17.6 MB
  • 25. Statistical Concepts/8. Coding Measures of Central Tendency - Geometric Mean.mp4 17.4 MB
  • 25. Statistical Concepts/12. Variance and Standard Deviation with PythonNumpy.mp4 17.1 MB
  • 12. Merging, Joining, and Concatenating Data/7. Inner Joins with merge().mp4 16.3 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/1. Intro and Overview.mp4 16.3 MB
  • 25. Statistical Concepts/23. Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4 16.1 MB
  • 12. Merging, Joining, and Concatenating Data/10. Right Joins (without Intersection) with merge().mp4 15.8 MB
  • 4. Pandas Series and Index Objects/16. Creating Index Objects from Scratch.mp4 15.8 MB
  • 25. Statistical Concepts/25. Properties of the Standard Normal Distribution (Theory).mp4 15.6 MB
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  • 25. Statistical Concepts/10. Minimum, Maximum and Range with PythonNumpy.mp4 12.9 MB
  • 25. Statistical Concepts/33. What is Linear Regression (Theory).mp4 12.2 MB
  • 25. Statistical Concepts/37. Case Study (Part 2) The Market Model (Single Factor Model).mp4 10.8 MB
  • 3. Pandas Basics (DataFrame Basics I)/11. Zero-based Indexing and Negative Indexing.mp4 10.7 MB
  • 13. GroupBy Operations/1. Intro.mp4 10.6 MB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/5. Info() method - new and extended output.mp4 10.3 MB
  • 3. Pandas Basics (DataFrame Basics I)/10. Selecting one Column with the dot notation.mp4 8.9 MB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/1.1 Course_Materials_Part3.zip 8.9 MB
  • 3. Pandas Basics (DataFrame Basics I)/21. Coding Exercise 2 (Intro).mp4 8.5 MB
  • 26. Download .py files/1.2 Course_Materials_Part2.zip 6.5 MB
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  • 11. Cleaning Data/11. The ignore_index parameter (NEW in Pandas 1.0).mp4 5.9 MB
  • 9. ----PART 2 FULL DATA WORKFLOW A-Z----/2.1 Course_Materials_Part2.zip 5.6 MB
  • 26. Download .py files/1.1 Course_Materials_Part1.zip 1.5 MB
  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/2.1 Course_Materials_Part1.zip 1.1 MB
  • 25. Statistical Concepts/1.1 Overview.pdf 1.0 MB
  • 18. ----PART 4 MANAGING TIME SERIES DATA WITH PANDAS----/2.1 Course_Materials_Part4.zip 851.4 kB
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  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/1.1 tabdata.pdf 483.5 kB
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  • 25. Statistical Concepts/25.1 standard_normal.pdf 403.4 kB
  • 25. Statistical Concepts/6.1 Central_tendency.pdf 306.4 kB
  • 25. Statistical Concepts/9.1 Dispersion.pdf 306.1 kB
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  • 3. Pandas Basics (DataFrame Basics I)/11.1 positions.pdf 198.8 kB
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  • 24. The Numpy Package/1.1 Numpy_basics.zip 108.3 kB
  • 3. Pandas Basics (DataFrame Basics I)/14.1 pandas-iloc.pdf 73.7 kB
  • 3. Pandas Basics (DataFrame Basics I)/17.1 Pandas-loc.pdf 69.4 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/3.1 Course_Materials_Version_1_0.zip 28.0 kB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/4. Olympic Medal Tables (Solution Part 2).srt 23.4 kB
  • 14. Reshaping and Pivoting DataFrames/6. pd.crosstab().srt 21.7 kB
  • 23. Python Basics/7. Data Types Lists (Part 2).srt 21.5 kB
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  • 11. Cleaning Data/5. Detection of missing Values.srt 17.6 kB
  • 16. Advanced Visualization with Seaborn/3. Categorical Plots.srt 17.4 kB
  • 1. Getting Started/7. How to use Jupyter Notebooks.srt 17.3 kB
  • 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().srt 17.2 kB
  • 23. Python Basics/18. Visualization with Matplotlib.srt 17.2 kB
  • 13. GroupBy Operations/13. stack() and unstack().srt 17.0 kB
  • 7. DataFrame Basics III/9. User-defined Functions with apply(), map() and applymap().srt 16.9 kB
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  • 19. Time Series Basics/7. Downsampling Time Series with resample() (Part 1).srt 16.7 kB
  • 12. Merging, Joining, and Concatenating Data/13. Joining on different Column Names Indexes.srt 16.7 kB
  • 15. Data Preparation and Feature Creation/8. Discretization and Binning with pd.qcut().srt 16.5 kB
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  • 23. Python Basics/11. Conditional Statements (if, elif, else, while).srt 15.9 kB
  • 13. GroupBy Operations/16. Coding Exercise 13 (Solution).srt 15.4 kB
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  • 25. Statistical Concepts/1. Statistics - Overview, Terms and Vocabulary.srt 15.3 kB
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  • 24. The Numpy Package/11. Visualization and (Linear) Regression.srt 14.7 kB
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  • 15. Data Preparation and Feature Creation/6. Discretization and Binning with pd.cut() (Part 1).srt 14.2 kB
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  • 14. Reshaping and Pivoting DataFrames/2. Transposing Rows and Columns.srt 13.3 kB
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  • 1. Getting Started/1. Overview Student FAQ.srt 12.3 kB
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  • 4. Pandas Series and Index Objects/7. Indexing and Slicing Pandas Series.srt 11.6 kB
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  • 23. Python Basics/12. For Loops.srt 11.5 kB
  • 23. Python Basics/10. Operators & Booleans.srt 11.4 kB
  • 19. Time Series Basics/2. Converting strings to datetime objects with pd.to_datetime().srt 11.4 kB
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  • 10. Importing Data/2. Importing messy csv-files with pd.read_csv.srt 11.1 kB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/2. Best Practice (How you should do it).srt 11.0 kB
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  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/3. Chained Indexing How you should NOT do it (Part 1).srt 11.0 kB
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  • 23. Python Basics/6. Data Types Lists (Part 1).srt 10.2 kB
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  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/2. Olympic Medal Tables (Instruction & Hints).srt 9.6 kB
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  • 25. Statistical Concepts/28. Covariance and Correlation Coefficient (Theory).srt 9.0 kB
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  • 25. Statistical Concepts/17. Probability Distributions - Overview.srt 8.1 kB
  • 25. Statistical Concepts/34. A simple Linear Regression Model with numpy & Scipy.srt 8.1 kB
  • 25. Statistical Concepts/9. Variability around the Central Tendency Dispersion (Theory).srt 8.0 kB
  • 23. Python Basics/14. Generating Random Numbers.srt 8.0 kB
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  • 23. Python Basics/8. Data Types Tuples.srt 7.9 kB
  • 20. Time Series Advanced Financial Time Series/5. Normalizing Time Series to a Base Value (100).srt 7.9 kB
  • 3. Pandas Basics (DataFrame Basics I)/19. Summary, Best Practices and Outlook.srt 7.8 kB
  • 3. Pandas Basics (DataFrame Basics I)/2. Pandas Display Options and the methods head() & tail().srt 7.8 kB
  • 25. Statistical Concepts/29. Cleaning and preparing the Data - Movies Database (Part 1).srt 7.8 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/13. Removal of prior Version Deprecations.srt 7.7 kB
  • 13. GroupBy Operations/12. Hierarchical Indexing with Groupby.srt 7.7 kB
  • 4. Pandas Series and Index Objects/14. Coding Exercise 3 (Solution).srt 7.6 kB
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  • 23. Python Basics/13. Key words break, pass, continue.srt 7.5 kB
  • 4. Pandas Series and Index Objects/5. Creating Pandas Series (Part 1).srt 7.4 kB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/9. Coding Exercise 6 (Solution).srt 7.4 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/8. NEW pd.NA value for missing values.srt 7.3 kB
  • 24. The Numpy Package/6. Numpy Arrays Boolean Indexing.srt 7.3 kB
  • 20. Time Series Advanced Financial Time Series/11. Helpful DatetimeIndex Attributes and Methods.srt 7.3 kB
  • 19. Time Series Basics/9. The PeriodIndex object.srt 7.3 kB
  • 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.srt 7.2 kB
  • 25. Statistical Concepts/30. Cleaning and preparing the Data - Movies Database (Part 2).srt 7.2 kB
  • 25. Statistical Concepts/18. Discrete Uniform Distributions.srt 7.2 kB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/5. Olympic Medal Tables (Solution Part 3).srt 7.1 kB
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/5. View vs. Copy.srt 7.1 kB
  • 24. The Numpy Package/8. Performance Issues.srt 7.1 kB
  • 24. The Numpy Package/4. Numpy Arrays Shape and Dimensions.srt 7.1 kB
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  • 25. Statistical Concepts/20. The Normal Distribution (Theory).srt 7.0 kB
  • 19. Time Series Basics/3. Initial Analysis Visualization of Time Series.srt 7.0 kB
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  • 1. Getting Started/2. Tips How to get the most out of this course.srt 6.7 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/4. Important Recap Pandas Display Options (Changed in Version 0.25).srt 6.7 kB
  • 4. Pandas Series and Index Objects/6. Creating Pandas Series (Part 2).srt 6.7 kB
  • 17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/3. Olympic Medal Tables (Solution Part 1).srt 6.7 kB
  • 3. Pandas Basics (DataFrame Basics I)/9. Selecting Columns.srt 6.7 kB
  • 25. Statistical Concepts/21. Creating a normally distributed Random Variable.srt 6.6 kB
  • 25. Statistical Concepts/6. Measures of Central Tendency (Theory).srt 6.6 kB
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  • 7. DataFrame Basics III/4. nunique() and nlargest() nsmallest() with DataFrames.srt 6.5 kB
  • 25. Statistical Concepts/31. How to calculate Covariance and Correlation in Python.srt 6.4 kB
  • 3. Pandas Basics (DataFrame Basics I)/18. Indexing and Slicing with reindex().srt 6.4 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/10. The NEW StringDtype.srt 6.3 kB
  • 3. Pandas Basics (DataFrame Basics I)/23. Advanced Indexing and Slicing (optional).srt 6.3 kB
  • 25. Statistical Concepts/32. Correlation and Scatterplots – visual Interpretation.srt 6.3 kB
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  • 5. DataFrame Basics II/7. Removing Columns.srt 6.2 kB
  • 4. Pandas Series and Index Objects/10. idxmin() and idxmax().srt 6.2 kB
  • 20. Time Series Advanced Financial Time Series/4. Initial Inspection and Visualization.srt 6.2 kB
  • 7. DataFrame Basics III/8. Coding Exercise 7 (Solution).srt 6.1 kB
  • 25. Statistical Concepts/5. Relative and Cumulative Frequencies with plt.hist().srt 6.1 kB
  • 5. DataFrame Basics II/4. Filtering DataFrames by many Conditions (OR).srt 6.0 kB
  • 25. Statistical Concepts/36. Case Study (Part 1) The Market Model (Single Factor Model).srt 5.9 kB
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  • 25. Statistical Concepts/15. How to generate Random Numbers with Numpy.srt 5.7 kB
  • 20. Time Series Advanced Financial Time Series/10. Financial Time Series - Covariance and Correlation.srt 5.6 kB
  • 12. Merging, Joining, and Concatenating Data/8. Outer Joins (without Intersection) with merge().srt 5.6 kB
  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/1. Intro to Tabular Data Pandas.srt 5.6 kB
  • 1. Getting Started/4. More FAQ Important Information.html 5.6 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/6. NEW Extension dtypes (nullable dtypes) Why do we need them.srt 5.6 kB
  • 13. GroupBy Operations/8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).srt 5.5 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/11. The NEW nullable BooleanDtype.srt 5.5 kB
  • 15. Data Preparation and Feature Creation/12. String Operations.srt 5.5 kB
  • 8. Visualization with Matplotlib/4. Histograms (Part 1).srt 5.4 kB
  • 25. Statistical Concepts/13. Skew and Kurtosis (Theory).srt 5.4 kB
  • 3. Pandas Basics (DataFrame Basics I)/13. Slicing Rows and Columns with iloc (position-based indexing).srt 5.4 kB
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  • 5. DataFrame Basics II/3. Filtering DataFrames by many Conditions (AND).srt 5.3 kB
  • 3. Pandas Basics (DataFrame Basics I)/8. Explore your own Dataset Coding Exercise 1 (Solution).srt 5.1 kB
  • 25. Statistical Concepts/8. Coding Measures of Central Tendency - Geometric Mean.srt 5.0 kB
  • 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.srt 4.9 kB
  • 4. Pandas Series and Index Objects/19. Renaming Index & Column Labels with rename().srt 4.9 kB
  • 25. Statistical Concepts/19. Continuous Uniform Distributions.srt 4.8 kB
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  • 8. Visualization with Matplotlib/6. Barcharts and Piecharts.srt 4.6 kB
  • 25. Statistical Concepts/4. Visualizing Frequency Distributions with plt.hist().srt 4.6 kB
  • 25. Statistical Concepts/22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.srt 4.6 kB
  • 25. Statistical Concepts/7. Coding Measures of Central Tendency - Mean and Median.srt 4.6 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/12. Addition of the ignore_index parameter.srt 4.5 kB
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  • 23. Python Basics/9. Data Types Sets.srt 4.2 kB
  • 25. Statistical Concepts/11. Percentiles with PythonNumpy.srt 4.2 kB
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/9. The NEW nullable Int64Dtype.srt 4.2 kB
  • 25. Statistical Concepts/12. Variance and Standard Deviation with PythonNumpy.srt 4.1 kB
  • 4. Pandas Series and Index Objects/18. Changing Column Labels.srt 4.0 kB
  • 12. Merging, Joining, and Concatenating Data/9. Left Joins (without Intersection) with merge().srt 3.9 kB
  • 5. DataFrame Basics II/9. Adding new Columns to a DataFrame.srt 3.9 kB
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  • 3. Pandas Basics (DataFrame Basics I)/11. Zero-based Indexing and Negative Indexing.srt 3.8 kB
  • 3. Pandas Basics (DataFrame Basics I)/15. Selecting Rows with loc (label-based indexing).srt 3.8 kB
  • 19. Time Series Basics/6. More on pd.date_range().srt 3.6 kB
  • 27. What´s next/1. Get your special BONUS here!.html 3.6 kB
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  • 1. Getting Started/8. How to tackle Pandas Version 1.0.srt 3.4 kB
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  • 3. Pandas Basics (DataFrame Basics I)/10. Selecting one Column with the dot notation.srt 3.0 kB
  • 2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/2. Download Part 1 Course Materials.srt 3.0 kB
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  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/1. Intro and Overview.srt 2.6 kB
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  • 3. Pandas Basics (DataFrame Basics I)/21. Coding Exercise 2 (Intro).srt 1.8 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/1. Intro.html 894 Bytes
  • 4. Pandas Series and Index Objects/1. Intro.html 827 Bytes
  • 9. ----PART 2 FULL DATA WORKFLOW A-Z----/1. Welcome to PART 2 Full Data Workflow A-Z.html 814 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/17. Label-based Indexing Cheat Sheets.html 786 Bytes
  • 16. Advanced Visualization with Seaborn/1. Intro.html 775 Bytes
  • 15. Data Preparation and Feature Creation/1. Intro.html 710 Bytes
  • 8. Visualization with Matplotlib/1. Intro.html 680 Bytes
  • 7. DataFrame Basics III/1. Intro.html 643 Bytes
  • 18. ----PART 4 MANAGING TIME SERIES DATA WITH PANDAS----/1. Welcome to PART 4 Time Series Data with Pandas.html 637 Bytes
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  • 16. Advanced Visualization with Seaborn/6. Coding Exercise 16.html 557 Bytes
  • 20. Time Series Advanced Financial Time Series/13. Coding Exercise 17.html 557 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/14. Position-based Indexing Cheat Sheets.html 495 Bytes
  • 22. ---APPENDIX PYTHON BASICS, NUMPY & STATISTICS---/1. Welcome to the Appendix.html 422 Bytes
  • 5. DataFrame Basics II/1. Intro.html 406 Bytes
  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/2. How to update Pandas to Version 1.0.html 313 Bytes
  • 11. Cleaning Data/16. Coding Exercise 11 (Intro).html 159 Bytes
  • 13. GroupBy Operations/15. Coding Exercise 13 (Intro).html 159 Bytes
  • 4. Pandas Series and Index Objects/13. Coding Exercise 3 (Intro).html 158 Bytes
  • 4. Pandas Series and Index Objects/21. Coding Exercise 4 (Intro).html 158 Bytes
  • 5. DataFrame Basics II/15. Coding Exercise 5 (Intro).html 158 Bytes
  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/8. Coding Exercise 6 (Intro).html 158 Bytes
  • 7. DataFrame Basics III/14. Coding Exercise 8 (Intro).html 158 Bytes
  • 7. DataFrame Basics III/7. Coding Exercise 7 (Intro).html 158 Bytes
  • 8. Visualization with Matplotlib/8. Coding Exercise 9 (Intro).html 158 Bytes
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  • 3. Pandas Basics (DataFrame Basics I)/4.2 Pandas Series Methods and Attributes.html 138 Bytes
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  • 9. ----PART 2 FULL DATA WORKFLOW A-Z----/2. Download Part 2 Course Materials.html 131 Bytes
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  • 13. GroupBy Operations/6. GroupBy 1.html 130 Bytes
  • 23. Python Basics/19. Python Basics.html 130 Bytes
  • 24. The Numpy Package/12. Numpy.html 130 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/20. Indexing and Slicing.html 130 Bytes
  • 3. Pandas Basics (DataFrame Basics I)/6. First Steps.html 130 Bytes
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  • 4. Pandas Series and Index Objects/20. Pandas Index objects.html 130 Bytes
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  • 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/7. Manipulating DataFrames Slices.html 130 Bytes
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  • 1. Getting Started/5.2 Installing on macOS.html 111 Bytes
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  • 21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/3. Downloads for this Section.html 84 Bytes
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  • 26. Download .py files/1. Parts 1 & 2 .py files.html 64 Bytes
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