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种子名称：
[GigaCourse.Com] Udemy - Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn
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视频
文件数目：
91个文件
文件大小：
1.95 GB
收录时间：
2022-4-9 02:49
已经下载：
3次
资源热度：
138
最近下载：
2024-5-27 12:39
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[GigaCourse.Com] Udemy - Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn.torrent
1. Introduction/1. Course Introduction.mp413.9MB
1. Introduction/2. How to Download Course Notebooks.mp438.09MB
1. Introduction/3. Overview of Course Curriculum.mp427.1MB
10. Module 10 Data Wrangling1 Hierarchical Indexing/1. Hierarchical Indexing.mp431.22MB
10. Module 10 Data Wrangling1 Hierarchical Indexing/2. Reordering and Sorting Index Levels.mp414.28MB
10. Module 10 Data Wrangling1 Hierarchical Indexing/3. Summary Statistics by Level.mp417.25MB
10. Module 10 Data Wrangling1 Hierarchical Indexing/4. Indexing with Columns in Dataframe.mp423.09MB
11. Module 11 Data Wrangling2 Combining and Merging Datasets/1. Merging Datasets on Keys (common columns).mp436.89MB
11. Module 11 Data Wrangling2 Combining and Merging Datasets/2. Merging Datasets on Index.mp415.02MB
11. Module 11 Data Wrangling2 Combining and Merging Datasets/3. Concatenating Along an Axis.mp430.11MB
12. Module 12 Data Wrangling3 Reshaping and Pivoting/1. Reshaping by Stacking and Unstacking.mp426.47MB
12. Module 12 Data Wrangling3 Reshaping and Pivoting/2. Reshaping by Melting (Wide to Long ).mp49.47MB
12. Module 12 Data Wrangling3 Reshaping and Pivoting/3. Reshaping by Pivoting (Long to Wide).mp428.92MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/1. Introducing Matplotlib Library.mp411.48MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/10. Bar Plots with Dataframes.mp420.59MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/11. Bar Plots with Seaborn.mp425.69MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/12. Histograms and Density Plots.mp427.78MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/13. Scatter Plots and Pair Plots.mp435.78MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/14. Factor Plots for Categorical Data.mp427.32MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/2. Creating Figures and Subplots.mp431.23MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/3. Changing Colors, Markers and Linestyle.mp421.94MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/4. Customizing Ticks and Labels.mp428.59MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/5. Adding Legends.mp424.61MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/6. Adding Texts and Arrows on a Plot.mp423.44MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/7. Adding Annotations and Drawings on a Plot.mp431.52MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/8. Saving Plots to a File.mp418.15MB
13. Module 13 Data Visualization with Matplotlib and Seaborn/9. Line Plots with Dataframe.mp426.72MB
14. Module 14 Time Series/1. Date and time Data types.mp420.25MB
14. Module 14 Time Series/2. Converting Between String and Datetime.mp425.86MB
14. Module 14 Time Series/3. Basics of Time Series.mp432.79MB
14. Module 14 Time Series/4. Generating Date Ranges.mp429.46MB
14. Module 14 Time Series/5. Shifting Data Through Time (Lagging and Leading).mp433.18MB
14. Module 14 Time Series/6. Handling Time Zone.mp433.46MB
14. Module 14 Time Series/7. Resampling and Frequency Conversion.mp423.09MB
14. Module 14 Time Series/8. Rolling and Moving Windows.mp429.77MB
15. Module 15 Real World Data Analysis Example/1. Housing Dataset Analysis -Part One.mp410.77MB
15. Module 15 Real World Data Analysis Example/2. Housing Dataset Analysis -Part Two.mp423.29MB
15. Module 15 Real World Data Analysis Example/3. Housing Dataset Analysis -Part Three.mp429.73MB
15. Module 15 Real World Data Analysis Example/4. Housing Dataset Analysis -Part Four.mp431.95MB
15. Module 15 Real World Data Analysis Example/5. Housing Dataset Analysis -Part Five.mp439.98MB
2. Module 2 Setting Python Environment/1. Decide Which Python Environment to Use.mp411.98MB
2. Module 2 Setting Python Environment/2. Local environment Installing Anaconda.mp410.44MB
2. Module 2 Setting Python Environment/3. Cloud Environment Google Colab Jupyter Notebooks.mp420.16MB
3. Module 3 Working with Jupyter Notebooks/1. Running Jupyter Notebook.mp428.76MB
3. Module 3 Working with Jupyter Notebooks/2. Tour In Basics of Jupyter Notebooks.mp426.87MB
3. Module 3 Working with Jupyter Notebooks/3. Cell Types in Jupyter Notebook.mp415.07MB
3. Module 3 Working with Jupyter Notebooks/4. Getting Help in Jupyter Notebook.mp415.56MB
3. Module 3 Working with Jupyter Notebooks/5. Magic Commands.mp423.38MB
4. Module 4 Data Structures And Sequences In Python/1. Tuple.mp419.83MB
4. Module 4 Data Structures And Sequences In Python/2. List.mp436.37MB
4. Module 4 Data Structures And Sequences In Python/3. Dictionary.mp414.79MB
4. Module 4 Data Structures And Sequences In Python/4. Set.mp44.45MB
5. Module 5 Functions in Python/1. Creating and Calling Functions.mp423.74MB
5. Module 5 Functions in Python/2. Returning Multiple Values.mp49.37MB
5. Module 5 Functions in Python/3. Lambda Functions.mp415.28MB
6. Module 6 NumPy Arrays/1. What Is NumPy Arrays (Ndarrays).mp411.54MB
6. Module 6 NumPy Arrays/10. Mathematical and Statistical Methods.mp435.39MB
6. Module 6 NumPy Arrays/11. Sorting Arrays.mp421.21MB
6. Module 6 NumPy Arrays/12. File Input and Output with Arrays.mp415.64MB
6. Module 6 NumPy Arrays/2. Creating Ndarrays.mp431.22MB
6. Module 6 NumPy Arrays/3. Data Types for Ndarrays.mp420.62MB
6. Module 6 NumPy Arrays/4. Arithmetic with NumPy Arrays.mp412.88MB
6. Module 6 NumPy Arrays/5. Indexing and Slicing-Part One.mp417.84MB
6. Module 6 NumPy Arrays/6. Indexing and Slicing-Part two.mp419.82MB
6. Module 6 NumPy Arrays/7. Boolean Indexing.mp428.16MB
6. Module 6 NumPy Arrays/8. Fancy Indexing.mp417.99MB
6. Module 6 NumPy Arrays/9. Transposing Arrays.mp48.93MB
7. Module 7 Pandas Dataframe/1. Series in Pandas.mp424.61MB
7. Module 7 Pandas Dataframe/10. Correlation and Covariance.mp418.75MB
7. Module 7 Pandas Dataframe/2. Dataframe in Pandas.mp433.96MB
7. Module 7 Pandas Dataframe/3. Index Objects.mp418.78MB
7. Module 7 Pandas Dataframe/4. Reindexing in Series and DataFrames.mp413.4MB
7. Module 7 Pandas Dataframe/5. Deleting Rows and Columns.mp45.4MB
7. Module 7 Pandas Dataframe/6. Indexing, Slicing and Filtering.mp425.33MB
7. Module 7 Pandas Dataframe/7. Arithmetic with Dataframe.mp422.14MB
7. Module 7 Pandas Dataframe/8. Sorting Series and Dataframe.mp420.27MB
7. Module 7 Pandas Dataframe/9. Descriptive Statistics with Dataframe.mp420.32MB
8. Module 8 Data Loading, Storage with Pandas/1. Reading Data in Text Format-Part1.mp422.34MB
8. Module 8 Data Loading, Storage with Pandas/2. Reading Data in Text Format-Part2.mp421.65MB
8. Module 8 Data Loading, Storage with Pandas/3. Writing Data in Text Format.mp421.88MB
8. Module 8 Data Loading, Storage with Pandas/4. Reading Microsoft Excel Files.mp412.18MB
9. Module 9 Data Cleaning and Preprocessing/1. Handling Missing Data.mp413.21MB
9. Module 9 Data Cleaning and Preprocessing/10. String Object Methods.mp420.68MB
9. Module 9 Data Cleaning and Preprocessing/2. Filtering out Missing Data.mp420.28MB
9. Module 9 Data Cleaning and Preprocessing/3. Filling in Missing Data.mp421.28MB
9. Module 9 Data Cleaning and Preprocessing/4. Removing Duplicate Entries.mp412.67MB
9. Module 9 Data Cleaning and Preprocessing/5. Replacing Values.mp413.52MB
9. Module 9 Data Cleaning and Preprocessing/6. Renaming columns and Index Labels.mp411.19MB
9. Module 9 Data Cleaning and Preprocessing/7. Filtering Outliers.mp422.44MB
9. Module 9 Data Cleaning and Preprocessing/8. Shuffling and Random Sampling.mp420.9MB
9. Module 9 Data Cleaning and Preprocessing/9. Dummy Variables.mp415.74MB
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