种子简介

种子名称： [FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass
文件类型： 视频
文件数目： 221个文件
文件大小： 9.78 GB
收录时间： 2021-3-4 01:07
已经下载： 3次
资源热度： 342
最近下载： 2024-12-28 05:35

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:2c675254c71f5b18cfc4579767100a16e7188c88&dn=[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass.torrent

1. Getting Started/1. Course Overview and how to maximize your learning success.mp470.95MB

1. Getting Started/2. Tips How to get the most out of this Course.mp443.64MB

1. Getting Started/3. Did you know that....mp426.85MB

1. Getting Started/5. Installation of Anaconda.mp486.21MB

1. Getting Started/6. Opening a Jupyter Notebook.mp465.09MB

1. Getting Started/7. How to use Jupyter Notebooks.mp466.29MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.mp432.15MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).mp456.32MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).mp460.35MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.mp432.94MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.mp441.9MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).mp423.78MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.mp425.12MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.mp432.24MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.mp433.02MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).mp430.69MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.mp480.67MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).mp420.62MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).mp496.57MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().mp440.98MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.mp433.01MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.mp454.06MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.mp451MB

10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.mp432.65MB

11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.mp464.35MB

11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.mp442.75MB

11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).mp449.8MB

11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).mp444.26MB

11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.mp432.48MB

11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.mp439.53MB

11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).mp411.36MB

11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).mp469.87MB

11. Create and Analyze Financial Indexes/3. Getting the Data.mp428.05MB

11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.mp434.95MB

11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.mp450.23MB

11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.mp425.39MB

11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.mp445.48MB

12. Create, Analyze and Optimize Financial Portfolios/1. Intro.mp422.09MB

12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).mp422.5MB

12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).mp488.5MB

12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.mp412.25MB

12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.mp454.3MB

12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.mp472.47MB

12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.mp416.88MB

12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.mp444.85MB

12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.mp447.74MB

12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.mp423.23MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.mp410MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.mp445.82MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp440.55MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).mp418.78MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).mp468.45MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.mp415.81MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.mp486.5MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.mp473.1MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).mp448.36MB

13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.mp442.67MB

14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.mp420.47MB

14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).mp461.73MB

14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).mp450.48MB

14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.mp442.91MB

14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).mp460.07MB

15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.mp416.54MB

15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).mp418.82MB

15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.mp455.39MB

15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.mp438.69MB

15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.mp446.88MB

15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.mp430.59MB

15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.mp426.5MB

15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.mp442.6MB

15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).mp411.12MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).mp49.97MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).mp431.59MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).mp418.28MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).mp456.51MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).mp447.71MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).mp438.8MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).mp435.47MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).mp452.32MB

16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).mp458.54MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.mp444.28MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.mp442.81MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.mp478.47MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().mp446.64MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().mp48.79MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().mp449.64MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).mp429.3MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).mp436.92MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().mp431.37MB

17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.mp426.61MB

19. Appendix 1 Python Crash Course (optional)/1. Intro.mp45.95MB

19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).mp486.02MB

19. Appendix 1 Python Crash Course (optional)/11. For Loops.mp458.37MB

19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.mp436.73MB

19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.mp438.12MB

19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).mp464.38MB

19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).mp457.43MB

19. Appendix 1 Python Crash Course (optional)/16. User Defined Functions (Part 3).mp452.16MB

19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.mp4124.27MB

19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.mp438.25MB

19. Appendix 1 Python Crash Course (optional)/2. First Steps.mp434.23MB

19. Appendix 1 Python Crash Course (optional)/3. Variables.mp431.45MB

19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.mp449.51MB

19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.mp477.74MB

19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).mp462.73MB

19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).mp4134.38MB

19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.mp441.81MB

19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.mp459.49MB

20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.mp441.11MB

20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.mp444.82MB

20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.mp484.47MB

20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.mp445.45MB

20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.mp464.73MB

20. Appendix 2 Numpy Crash Course (optional)/3. Numpy Arrays Indexing and Slicing.mp453.46MB

20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.mp435.52MB

20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp473.61MB

20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.mp444.19MB

20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.mp467.51MB

20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.mp449.87MB

20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.mp445.62MB

3. Pandas Basics/1. Intro to Tabular Data Pandas.mp427.55MB

3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).mp439.47MB

3. Pandas Basics/11. Selecting Columns.mp438.56MB

3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).mp422.05MB

3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).mp453.96MB

3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).mp425.92MB

3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).mp430.36MB

3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).mp491.41MB

3. Pandas Basics/19. Summary and Outlook.mp462.13MB

3. Pandas Basics/21. Coding Exercise 2 (Intro).mp48.64MB

3. Pandas Basics/22. Coding Exercise 2 (Solution).mp450.56MB

3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).mp445.2MB

3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).mp456.78MB

3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.mp4113.37MB

3. Pandas Basics/6. Built-in Functions, Attributes and Methods.mp450.67MB

3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.mp454.2MB

3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).mp460.54MB

4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).mp410.52MB

4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).mp435.9MB

4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.mp443.04MB

4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().mp475.07MB

4. Pandas Intermediate Topics/14. Changing Column Labels.mp421.18MB

4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().mp433.54MB

4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).mp47.67MB

4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).mp427.34MB

4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().mp454.38MB

4. Pandas Intermediate Topics/2. First Steps with Pandas Series.mp435.96MB

4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.mp432.62MB

4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).mp452.91MB

4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).mp425.9MB

4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).mp430.79MB

4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.mp465.45MB

4. Pandas Intermediate Topics/25. any() and all().mp417.51MB

4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).mp411MB

4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).mp471.87MB

4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.mp445.65MB

4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp472.67MB

4. Pandas Intermediate Topics/30. Handling NA Values missing Values.mp468.61MB

4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.mp413.25MB

4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.mp457.58MB

4. Pandas Intermediate Topics/33. The agg() method.mp422.81MB

4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).mp415.33MB

4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).mp483.91MB

4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.mp477.1MB

4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp442.89MB

4. Pandas Intermediate Topics/7. The copy() method.mp424.78MB

4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.mp441.42MB

5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.mp442.75MB

5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).mp410.69MB

5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).mp462.15MB

5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).mp470.28MB

5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.mp4103.1MB

5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).mp424.6MB

5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).mp434.14MB

5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.mp436.12MB

5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.mp422.1MB

5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.mp485.2MB

5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.mp479.41MB

6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).mp49.04MB

6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).mp454.6MB

6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.mp410.06MB

6. Pandas Advanced Topics/13. Understanding the GroupBy Object.mp446.25MB

6. Pandas Advanced Topics/14. Splitting with many Keys.mp449.71MB

6. Pandas Advanced Topics/15. split-apply-combine.mp447.06MB

6. Pandas Advanced Topics/16. split-apply-combine applied.mp470.71MB

6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.mp432.86MB

6. Pandas Advanced Topics/18. stack() and unstack().mp478.77MB

6. Pandas Advanced Topics/2. Removing Columns.mp436.06MB

6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).mp47.84MB

6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).mp444.46MB

6. Pandas Advanced Topics/3. Removing Rows.mp449.66MB

6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.mp417.89MB

6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).mp463.51MB

6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).mp458.44MB

6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.mp488.04MB

6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.mp431.28MB

8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.mp441.75MB

8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).mp449.13MB

8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.mp438.78MB

8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().mp450.48MB

8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).mp48.76MB

8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).mp444.08MB

8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().mp457.97MB

8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.mp435.02MB

8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.mp448.16MB

8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().mp4114.71MB

8. Time Series Data in Pandas Introduction/6. More on pd.date_range().mp412.36MB

8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).mp49.94MB

8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).mp444.46MB

8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).mp485.52MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.mp425.73MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).mp417.53MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).mp455.95MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).mp421.77MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).mp471.86MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.mp442.33MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).mp444.25MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.mp435.76MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().mp440.26MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp443.93MB

9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.mp453.66MB