[Tutorialsplanet.NET] Udemy - Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn

磁力链接/BT种子名称

[Tutorialsplanet.NET] Udemy - Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn

磁力链接/BT种子简介

种子哈希：fa3d97dac66d1dc2d091d663d16cbf4a9ee9e614
文件大小： 1.95G
已经下载：1064次
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收录时间：2024-01-07
最近下载：2025-09-06

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文件列表

  • 15. Module 15 Real World Data Analysis Example/5. Housing Dataset Analysis -Part Five.mp4 41.9 MB
  • 1. Introduction/2. How to Download Course Notebooks.mp4 39.9 MB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/1. Merging Datasets on Keys (common columns).mp4 38.7 MB
  • 4. Module 4 Data Structures And Sequences In Python/2. List.mp4 38.1 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/13. Scatter Plots and Pair Plots.mp4 37.5 MB
  • 6. Module 6 NumPy Arrays/10. Mathematical and Statistical Methods.mp4 37.1 MB
  • 7. Module 7 Pandas Dataframe/2. Dataframe in Pandas.mp4 35.6 MB
  • 14. Module 14 Time Series/6. Handling Time Zone.mp4 35.1 MB
  • 14. Module 14 Time Series/5. Shifting Data Through Time (Lagging and Leading).mp4 34.8 MB
  • 14. Module 14 Time Series/3. Basics of Time Series.mp4 34.4 MB
  • 15. Module 15 Real World Data Analysis Example/4. Housing Dataset Analysis -Part Four.mp4 33.5 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/7. Adding Annotations and Drawings on a Plot.mp4 33.1 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/2. Creating Figures and Subplots.mp4 32.7 MB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/1. Hierarchical Indexing.mp4 32.7 MB
  • 6. Module 6 NumPy Arrays/2. Creating Ndarrays.mp4 32.7 MB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/3. Concatenating Along an Axis.mp4 31.6 MB
  • 14. Module 14 Time Series/8. Rolling and Moving Windows.mp4 31.2 MB
  • 15. Module 15 Real World Data Analysis Example/3. Housing Dataset Analysis -Part Three.mp4 31.2 MB
  • 14. Module 14 Time Series/4. Generating Date Ranges.mp4 30.9 MB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/3. Reshaping by Pivoting (Long to Wide).mp4 30.3 MB
  • 3. Module 3 Working with Jupyter Notebooks/1. Running Jupyter Notebook.mp4 30.2 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/4. Customizing Ticks and Labels.mp4 30.0 MB
  • 6. Module 6 NumPy Arrays/7. Boolean Indexing.mp4 29.5 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/12. Histograms and Density Plots.mp4 29.1 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/14. Factor Plots for Categorical Data.mp4 28.6 MB
  • 1. Introduction/3. Overview of Course Curriculum.mp4 28.4 MB
  • 3. Module 3 Working with Jupyter Notebooks/2. Tour In Basics of Jupyter Notebooks.mp4 28.2 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/9. Line Plots with Dataframe.mp4 28.0 MB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/1. Reshaping by Stacking and Unstacking.mp4 27.8 MB
  • 14. Module 14 Time Series/2. Converting Between String and Datetime.mp4 27.1 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/11. Bar Plots with Seaborn.mp4 26.9 MB
  • 7. Module 7 Pandas Dataframe/6. Indexing, Slicing and Filtering.mp4 26.6 MB
  • 7. Module 7 Pandas Dataframe/1. Series in Pandas.mp4 25.8 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/5. Adding Legends.mp4 25.8 MB
  • 5. Module 5 Functions in Python/1. Creating and Calling Functions.mp4 24.9 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/6. Adding Texts and Arrows on a Plot.mp4 24.6 MB
  • 3. Module 3 Working with Jupyter Notebooks/5. Magic Commands.mp4 24.5 MB
  • 15. Module 15 Real World Data Analysis Example/2. Housing Dataset Analysis -Part Two.mp4 24.4 MB
  • 14. Module 14 Time Series/7. Resampling and Frequency Conversion.mp4 24.2 MB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/4. Indexing with Columns in Dataframe.mp4 24.2 MB
  • 9. Module 9 Data Cleaning and Preprocessing/7. Filtering Outliers.mp4 23.5 MB
  • 8. Module 8 Data Loading, Storage with Pandas/1. Reading Data in Text Format-Part1.mp4 23.4 MB
  • 7. Module 7 Pandas Dataframe/7. Arithmetic with Dataframe.mp4 23.2 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/3. Changing Colors, Markers and Linestyle.mp4 23.0 MB
  • 8. Module 8 Data Loading, Storage with Pandas/3. Writing Data in Text Format.mp4 22.9 MB
  • 8. Module 8 Data Loading, Storage with Pandas/2. Reading Data in Text Format-Part2.mp4 22.7 MB
  • 9. Module 9 Data Cleaning and Preprocessing/3. Filling in Missing Data.mp4 22.3 MB
  • 6. Module 6 NumPy Arrays/11. Sorting Arrays.mp4 22.2 MB
  • 9. Module 9 Data Cleaning and Preprocessing/8. Shuffling and Random Sampling.mp4 21.9 MB
  • 9. Module 9 Data Cleaning and Preprocessing/10. String Object Methods.mp4 21.7 MB
  • 6. Module 6 NumPy Arrays/3. Data Types for Ndarrays.mp4 21.6 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/10. Bar Plots with Dataframes.mp4 21.6 MB
  • 7. Module 7 Pandas Dataframe/9. Descriptive Statistics with Dataframe.mp4 21.3 MB
  • 9. Module 9 Data Cleaning and Preprocessing/2. Filtering out Missing Data.mp4 21.3 MB
  • 7. Module 7 Pandas Dataframe/8. Sorting Series and Dataframe.mp4 21.3 MB
  • 14. Module 14 Time Series/1. Date and time Data types.mp4 21.2 MB
  • 2. Module 2 Setting Python Environment/3. Cloud Environment Google Colab Jupyter Notebooks.mp4 21.1 MB
  • 4. Module 4 Data Structures And Sequences In Python/1. Tuple.mp4 20.8 MB
  • 6. Module 6 NumPy Arrays/6. Indexing and Slicing-Part two.mp4 20.8 MB
  • 7. Module 7 Pandas Dataframe/3. Index Objects.mp4 19.7 MB
  • 7. Module 7 Pandas Dataframe/10. Correlation and Covariance.mp4 19.7 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/8. Saving Plots to a File.mp4 19.0 MB
  • 6. Module 6 NumPy Arrays/8. Fancy Indexing.mp4 18.9 MB
  • 6. Module 6 NumPy Arrays/5. Indexing and Slicing-Part One.mp4 18.7 MB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/3. Summary Statistics by Level.mp4 18.1 MB
  • 9. Module 9 Data Cleaning and Preprocessing/9. Dummy Variables.mp4 16.5 MB
  • 6. Module 6 NumPy Arrays/12. File Input and Output with Arrays.mp4 16.4 MB
  • 3. Module 3 Working with Jupyter Notebooks/4. Getting Help in Jupyter Notebook.mp4 16.3 MB
  • 5. Module 5 Functions in Python/3. Lambda Functions.mp4 16.0 MB
  • 3. Module 3 Working with Jupyter Notebooks/3. Cell Types in Jupyter Notebook.mp4 15.8 MB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/2. Merging Datasets on Index.mp4 15.7 MB
  • 4. Module 4 Data Structures And Sequences In Python/3. Dictionary.mp4 15.5 MB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/2. Reordering and Sorting Index Levels.mp4 15.0 MB
  • 1. Introduction/1. Course Introduction.mp4 14.6 MB
  • 9. Module 9 Data Cleaning and Preprocessing/5. Replacing Values.mp4 14.2 MB
  • 7. Module 7 Pandas Dataframe/4. Reindexing in Series and DataFrames.mp4 14.1 MB
  • 9. Module 9 Data Cleaning and Preprocessing/1. Handling Missing Data.mp4 13.9 MB
  • 6. Module 6 NumPy Arrays/4. Arithmetic with NumPy Arrays.mp4 13.5 MB
  • 9. Module 9 Data Cleaning and Preprocessing/4. Removing Duplicate Entries.mp4 13.3 MB
  • 8. Module 8 Data Loading, Storage with Pandas/4. Reading Microsoft Excel Files.mp4 12.8 MB
  • 2. Module 2 Setting Python Environment/1. Decide Which Python Environment to Use.mp4 12.6 MB
  • 6. Module 6 NumPy Arrays/1. What Is NumPy Arrays (Ndarrays).mp4 12.1 MB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/1. Introducing Matplotlib Library.mp4 12.0 MB
  • 9. Module 9 Data Cleaning and Preprocessing/6. Renaming columns and Index Labels.mp4 11.7 MB
  • 15. Module 15 Real World Data Analysis Example/1. Housing Dataset Analysis -Part One.mp4 11.3 MB
  • 2. Module 2 Setting Python Environment/2. Local environment Installing Anaconda.mp4 11.0 MB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/2. Reshaping by Melting (Wide to Long ).mp4 9.9 MB
  • 5. Module 5 Functions in Python/2. Returning Multiple Values.mp4 9.8 MB
  • 6. Module 6 NumPy Arrays/9. Transposing Arrays.mp4 9.4 MB
  • 7. Module 7 Pandas Dataframe/5. Deleting Rows and Columns.mp4 5.7 MB
  • 4. Module 4 Data Structures And Sequences In Python/4. Set.mp4 4.7 MB
  • 1. Introduction/2.1 How to download course notebooks.pdf 143.5 kB
  • 4. Module 4 Data Structures And Sequences In Python/2. List.srt 9.4 kB
  • 15. Module 15 Real World Data Analysis Example/5. Housing Dataset Analysis -Part Five.srt 8.9 kB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/1. Merging Datasets on Keys (common columns).srt 8.4 kB
  • 7. Module 7 Pandas Dataframe/2. Dataframe in Pandas.srt 7.9 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/7. Adding Annotations and Drawings on a Plot.srt 7.8 kB
  • 6. Module 6 NumPy Arrays/2. Creating Ndarrays.srt 7.6 kB
  • 14. Module 14 Time Series/3. Basics of Time Series.srt 7.6 kB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/3. Concatenating Along an Axis.srt 7.4 kB
  • 3. Module 3 Working with Jupyter Notebooks/2. Tour In Basics of Jupyter Notebooks.srt 7.2 kB
  • 14. Module 14 Time Series/8. Rolling and Moving Windows.srt 6.9 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/2. Creating Figures and Subplots.srt 6.9 kB
  • 6. Module 6 NumPy Arrays/10. Mathematical and Statistical Methods.srt 6.8 kB
  • 14. Module 14 Time Series/5. Shifting Data Through Time (Lagging and Leading).srt 6.8 kB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/1. Hierarchical Indexing.srt 6.6 kB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/3. Reshaping by Pivoting (Long to Wide).srt 6.6 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/14. Factor Plots for Categorical Data.srt 6.5 kB
  • 15. Module 15 Real World Data Analysis Example/4. Housing Dataset Analysis -Part Four.srt 6.4 kB
  • 1. Introduction/2. How to Download Course Notebooks.srt 6.4 kB
  • 5. Module 5 Functions in Python/1. Creating and Calling Functions.srt 6.4 kB
  • 7. Module 7 Pandas Dataframe/6. Indexing, Slicing and Filtering.srt 6.3 kB
  • 6. Module 6 NumPy Arrays/7. Boolean Indexing.srt 6.2 kB
  • 3. Module 3 Working with Jupyter Notebooks/1. Running Jupyter Notebook.srt 6.0 kB
  • 1. Introduction/3. Overview of Course Curriculum.srt 6.0 kB
  • 7. Module 7 Pandas Dataframe/1. Series in Pandas.srt 6.0 kB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/2. Reshaping by Melting (Wide to Long ).srt 6.0 kB
  • 8. Module 8 Data Loading, Storage with Pandas/1. Reading Data in Text Format-Part1.srt 5.9 kB
  • 14. Module 14 Time Series/6. Handling Time Zone.srt 5.8 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/11. Bar Plots with Seaborn.srt 5.7 kB
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/1. Reshaping by Stacking and Unstacking.srt 5.7 kB
  • 14. Module 14 Time Series/7. Resampling and Frequency Conversion.srt 5.6 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/13. Scatter Plots and Pair Plots.srt 5.6 kB
  • 14. Module 14 Time Series/2. Converting Between String and Datetime.srt 5.5 kB
  • 2. Module 2 Setting Python Environment/3. Cloud Environment Google Colab Jupyter Notebooks.srt 5.4 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/12. Histograms and Density Plots.srt 5.3 kB
  • 7. Module 7 Pandas Dataframe/7. Arithmetic with Dataframe.srt 5.1 kB
  • 4. Module 4 Data Structures And Sequences In Python/1. Tuple.srt 5.1 kB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/4. Indexing with Columns in Dataframe.srt 5.1 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/6. Adding Texts and Arrows on a Plot.srt 5.1 kB
  • 6. Module 6 NumPy Arrays/3. Data Types for Ndarrays.srt 5.0 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/4. Customizing Ticks and Labels.srt 5.0 kB
  • 9. Module 9 Data Cleaning and Preprocessing/7. Filtering Outliers.srt 5.0 kB
  • 9. Module 9 Data Cleaning and Preprocessing/10. String Object Methods.srt 5.0 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/9. Line Plots with Dataframe.srt 4.9 kB
  • 6. Module 6 NumPy Arrays/6. Indexing and Slicing-Part two.srt 4.8 kB
  • 7. Module 7 Pandas Dataframe/9. Descriptive Statistics with Dataframe.srt 4.8 kB
  • 14. Module 14 Time Series/4. Generating Date Ranges.srt 4.7 kB
  • 1. Introduction/1. Course Introduction.srt 4.6 kB
  • 15. Module 15 Real World Data Analysis Example/3. Housing Dataset Analysis -Part Three.srt 4.6 kB
  • 3. Module 3 Working with Jupyter Notebooks/4. Getting Help in Jupyter Notebook.srt 4.6 kB
  • 9. Module 9 Data Cleaning and Preprocessing/3. Filling in Missing Data.srt 4.6 kB
  • 14. Module 14 Time Series/1. Date and time Data types.srt 4.6 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/5. Adding Legends.srt 4.5 kB
  • 7. Module 7 Pandas Dataframe/8. Sorting Series and Dataframe.srt 4.5 kB
  • 9. Module 9 Data Cleaning and Preprocessing/2. Filtering out Missing Data.srt 4.4 kB
  • 8. Module 8 Data Loading, Storage with Pandas/2. Reading Data in Text Format-Part2.srt 4.4 kB
  • 6. Module 6 NumPy Arrays/8. Fancy Indexing.srt 4.4 kB
  • 8. Module 8 Data Loading, Storage with Pandas/3. Writing Data in Text Format.srt 4.3 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/10. Bar Plots with Dataframes.srt 4.3 kB
  • 15. Module 15 Real World Data Analysis Example/1. Housing Dataset Analysis -Part One.srt 4.3 kB
  • 15. Module 15 Real World Data Analysis Example/2. Housing Dataset Analysis -Part Two.srt 4.3 kB
  • 2. Module 2 Setting Python Environment/1. Decide Which Python Environment to Use.srt 4.3 kB
  • 2. Module 2 Setting Python Environment/2. Local environment Installing Anaconda.srt 4.3 kB
  • 3. Module 3 Working with Jupyter Notebooks/5. Magic Commands.srt 4.3 kB
  • 6. Module 6 NumPy Arrays/5. Indexing and Slicing-Part One.srt 4.3 kB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/3. Summary Statistics by Level.srt 4.2 kB
  • 9. Module 9 Data Cleaning and Preprocessing/8. Shuffling and Random Sampling.srt 4.2 kB
  • 7. Module 7 Pandas Dataframe/10. Correlation and Covariance.srt 4.2 kB
  • 3. Module 3 Working with Jupyter Notebooks/3. Cell Types in Jupyter Notebook.srt 4.2 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/3. Changing Colors, Markers and Linestyle.srt 4.1 kB
  • 7. Module 7 Pandas Dataframe/3. Index Objects.srt 4.1 kB
  • 9. Module 9 Data Cleaning and Preprocessing/9. Dummy Variables.srt 4.0 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/8. Saving Plots to a File.srt 4.0 kB
  • 5. Module 5 Functions in Python/3. Lambda Functions.srt 3.9 kB
  • 6. Module 6 NumPy Arrays/11. Sorting Arrays.srt 3.6 kB
  • 9. Module 9 Data Cleaning and Preprocessing/5. Replacing Values.srt 3.6 kB
  • 9. Module 9 Data Cleaning and Preprocessing/1. Handling Missing Data.srt 3.5 kB
  • 4. Module 4 Data Structures And Sequences In Python/3. Dictionary.srt 3.4 kB
  • 7. Module 7 Pandas Dataframe/5. Deleting Rows and Columns.srt 3.3 kB
  • 6. Module 6 NumPy Arrays/12. File Input and Output with Arrays.srt 3.3 kB
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/1. Introducing Matplotlib Library.srt 3.2 kB
  • 6. Module 6 NumPy Arrays/4. Arithmetic with NumPy Arrays.srt 3.2 kB
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/2. Merging Datasets on Index.srt 3.1 kB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/2. Reordering and Sorting Index Levels.srt 3.1 kB
  • 7. Module 7 Pandas Dataframe/4. Reindexing in Series and DataFrames.srt 3.0 kB
  • 6. Module 6 NumPy Arrays/1. What Is NumPy Arrays (Ndarrays).srt 2.9 kB
  • 9. Module 9 Data Cleaning and Preprocessing/6. Renaming columns and Index Labels.srt 2.8 kB
  • 9. Module 9 Data Cleaning and Preprocessing/4. Removing Duplicate Entries.srt 2.7 kB
  • 8. Module 8 Data Loading, Storage with Pandas/4. Reading Microsoft Excel Files.srt 2.5 kB
  • 4. Module 4 Data Structures And Sequences In Python/4. Set.srt 2.4 kB
  • 5. Module 5 Functions in Python/2. Returning Multiple Values.srt 2.3 kB
  • 6. Module 6 NumPy Arrays/9. Transposing Arrays.srt 2.0 kB
  • 10. Module 10 Data Wrangling1 Hierarchical Indexing/5. Short Quiz.html 213 Bytes
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/4. Short Quiz.html 213 Bytes
  • 12. Module 12 Data Wrangling3 Reshaping and Pivoting/4. Short Quiz.html 213 Bytes
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/15. Short Quiz.html 213 Bytes
  • 14. Module 14 Time Series/9. Short Quiz.html 213 Bytes
  • 4. Module 4 Data Structures And Sequences In Python/5. Short Quiz.html 213 Bytes
  • 5. Module 5 Functions in Python/4. Short Quiz.html 213 Bytes
  • 6. Module 6 NumPy Arrays/13. Short Quiz.html 213 Bytes
  • 7. Module 7 Pandas Dataframe/11. Short Quiz.html 213 Bytes
  • 8. Module 8 Data Loading, Storage with Pandas/5. Short Quiz.html 213 Bytes
  • 9. Module 9 Data Cleaning and Preprocessing/11. Short Quiz.html 213 Bytes
  • 0. Websites you may like/[Tutorialsplanet.NET].url 128 Bytes
  • 11. Module 11 Data Wrangling2 Combining and Merging Datasets/[Tutorialsplanet.NET].url 128 Bytes
  • 13. Module 13 Data Visualization with Matplotlib and Seaborn/[Tutorialsplanet.NET].url 128 Bytes
  • 15. Module 15 Real World Data Analysis Example/[Tutorialsplanet.NET].url 128 Bytes
  • 6. Module 6 NumPy Arrays/[Tutorialsplanet.NET].url 128 Bytes
  • 8. Module 8 Data Loading, Storage with Pandas/[Tutorialsplanet.NET].url 128 Bytes
  • [Tutorialsplanet.NET].url 128 Bytes

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本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！