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[] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass

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文件列表

  1. 19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).mp4 134MB
  2. 19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.mp4 124MB
  3. 8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().mp4 115MB
  4. 3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.mp4 113MB
  5. 5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.mp4 103MB
  6. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).mp4 97MB
  7. 3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).mp4 91MB
  8. 12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).mp4 88MB
  9. 6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.mp4 88MB
  10. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.mp4 87MB
  11. 1. Getting Started/5. Installation of Anaconda.mp4 86MB
  12. 19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).mp4 86MB
  13. 8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).mp4 86MB
  14. 5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.mp4 85MB
  15. 20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.mp4 84MB
  16. 4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).mp4 84MB
  17. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.mp4 81MB
  18. 5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.mp4 79MB
  19. 6. Pandas Advanced Topics/18. stack() and unstack().mp4 79MB
  20. 17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.mp4 78MB
  21. 19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.mp4 78MB
  22. 4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.mp4 77MB
  23. 4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().mp4 75MB
  24. 20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4 74MB
  25. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.mp4 73MB
  26. 4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 73MB
  27. 12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.mp4 72MB
  28. 4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).mp4 72MB
  29. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).mp4 72MB
  30. 1. Getting Started/1. Course Overview and how to maximize your learning success.mp4 71MB
  31. 6. Pandas Advanced Topics/16. split-apply-combine applied.mp4 71MB
  32. 5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).mp4 70MB
  33. 11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).mp4 70MB
  34. 4. Pandas Intermediate Topics/30. Handling NA Values missing Values.mp4 69MB
  35. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).mp4 68MB
  36. 20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.mp4 68MB
  37. 1. Getting Started/7. How to use Jupyter Notebooks.mp4 66MB
  38. 4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.mp4 65MB
  39. 1. Getting Started/6. Opening a Jupyter Notebook.mp4 65MB
  40. 20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.mp4 65MB
  41. 19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).mp4 64MB
  42. 11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.mp4 64MB
  43. 6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).mp4 64MB
  44. 19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).mp4 63MB
  45. 5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).mp4 62MB
  46. 3. Pandas Basics/19. Summary and Outlook.mp4 62MB
  47. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).mp4 62MB
  48. 3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).mp4 61MB
  49. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).mp4 60MB
  50. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).mp4 60MB
  51. 19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.mp4 59MB
  52. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).mp4 59MB
  53. 6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).mp4 58MB
  54. 19. Appendix 1 Python Crash Course (optional)/11. For Loops.mp4 58MB
  55. 8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().mp4 58MB
  56. 4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.mp4 58MB
  57. 19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).mp4 57MB
  58. 3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).mp4 57MB
  59. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).mp4 57MB
  60. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).mp4 56MB
  61. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).mp4 56MB
  62. 15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.mp4 55MB
  63. 6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).mp4 55MB
  64. 4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().mp4 54MB
  65. 12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.mp4 54MB
  66. 3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.mp4 54MB
  67. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.mp4 54MB
  68. 3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).mp4 54MB
  69. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.mp4 54MB
  70. 20. Appendix 2 Numpy Crash Course (optional)/3. Numpy Arrays Indexing and Slicing.mp4 53MB
  71. 4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).mp4 53MB
  72. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).mp4 52MB
  73. 19. Appendix 1 Python Crash Course (optional)/16. User Defined Functions (Part 3).mp4 52MB
  74. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.mp4 51MB
  75. 3. Pandas Basics/6. Built-in Functions, Attributes and Methods.mp4 51MB
  76. 3. Pandas Basics/22. Coding Exercise 2 (Solution).mp4 51MB
  77. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).mp4 50MB
  78. 8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().mp4 50MB
  79. 11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.mp4 50MB
  80. 20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.mp4 50MB
  81. 11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).mp4 50MB
  82. 6. Pandas Advanced Topics/14. Splitting with many Keys.mp4 50MB
  83. 6. Pandas Advanced Topics/3. Removing Rows.mp4 50MB
  84. 17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().mp4 50MB
  85. 19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.mp4 50MB
  86. 8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).mp4 49MB
  87. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).mp4 48MB
  88. 8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.mp4 48MB
  89. 12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.mp4 48MB
  90. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).mp4 48MB
  91. 6. Pandas Advanced Topics/15. split-apply-combine.mp4 47MB
  92. 15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.mp4 47MB
  93. 17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().mp4 47MB
  94. 6. Pandas Advanced Topics/13. Understanding the GroupBy Object.mp4 46MB
  95. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.mp4 46MB
  96. 4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.mp4 46MB
  97. 20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.mp4 46MB
  98. 11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.mp4 45MB
  99. 20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.mp4 45MB
  100. 3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).mp4 45MB
  101. 12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.mp4 45MB
  102. 20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.mp4 45MB
  103. 8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).mp4 44MB
  104. 6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).mp4 44MB
  105. 17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.mp4 44MB
  106. 11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).mp4 44MB
  107. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).mp4 44MB
  108. 20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.mp4 44MB
  109. 8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).mp4 44MB
  110. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 44MB
  111. 1. Getting Started/2. Tips How to get the most out of this Course.mp4 44MB
  112. 4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.mp4 43MB
  113. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.mp4 43MB
  114. 4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 43MB
  115. 17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.mp4 43MB
  116. 11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.mp4 43MB
  117. 5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.mp4 43MB
  118. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.mp4 43MB
  119. 15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.mp4 43MB
  120. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.mp4 42MB
  121. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.mp4 42MB
  122. 19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.mp4 42MB
  123. 8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.mp4 42MB
  124. 4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.mp4 41MB
  125. 20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.mp4 41MB
  126. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().mp4 41MB
  127. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4 41MB
  128. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().mp4 40MB
  129. 11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.mp4 40MB
  130. 3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).mp4 39MB
  131. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).mp4 39MB
  132. 8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.mp4 39MB
  133. 15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.mp4 39MB
  134. 3. Pandas Basics/11. Selecting Columns.mp4 39MB
  135. 19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.mp4 38MB
  136. 19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.mp4 38MB
  137. 17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).mp4 37MB
  138. 19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.mp4 37MB
  139. 5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.mp4 36MB
  140. 6. Pandas Advanced Topics/2. Removing Columns.mp4 36MB
  141. 4. Pandas Intermediate Topics/2. First Steps with Pandas Series.mp4 36MB
  142. 4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).mp4 36MB
  143. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.mp4 36MB
  144. 20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.mp4 36MB
  145. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).mp4 35MB
  146. 8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.mp4 35MB
  147. 11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.mp4 35MB
  148. 19. Appendix 1 Python Crash Course (optional)/2. First Steps.mp4 34MB
  149. 5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).mp4 34MB
  150. 4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().mp4 34MB
  151. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.mp4 33MB
  152. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.mp4 33MB
  153. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.mp4 33MB
  154. 6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.mp4 33MB
  155. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.mp4 33MB
  156. 4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.mp4 33MB
  157. 11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.mp4 32MB
  158. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.mp4 32MB
  159. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.mp4 32MB
  160. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).mp4 32MB
  161. 19. Appendix 1 Python Crash Course (optional)/3. Variables.mp4 31MB
  162. 17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().mp4 31MB
  163. 6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.mp4 31MB
  164. 4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).mp4 31MB
  165. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).mp4 31MB
  166. 15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.mp4 31MB
  167. 3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).mp4 30MB
  168. 17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).mp4 29MB
  169. 11. Create and Analyze Financial Indexes/3. Getting the Data.mp4 28MB
  170. 3. Pandas Basics/1. Intro to Tabular Data Pandas.mp4 28MB
  171. 4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).mp4 27MB
  172. 1. Getting Started/3. Did you know that....mp4 27MB
  173. 17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.mp4 27MB
  174. 15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.mp4 26MB
  175. 3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).mp4 26MB
  176. 4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).mp4 26MB
  177. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.mp4 26MB
  178. 11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.mp4 25MB
  179. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.mp4 25MB
  180. 4. Pandas Intermediate Topics/7. The copy() method.mp4 25MB
  181. 5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).mp4 25MB
  182. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).mp4 24MB
  183. 12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.mp4 23MB
  184. 4. Pandas Intermediate Topics/33. The agg() method.mp4 23MB
  185. 12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).mp4 23MB
  186. 5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.mp4 22MB
  187. 12. Create, Analyze and Optimize Financial Portfolios/1. Intro.mp4 22MB
  188. 3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).mp4 22MB
  189. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).mp4 22MB
  190. 4. Pandas Intermediate Topics/14. Changing Column Labels.mp4 21MB
  191. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).mp4 21MB
  192. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.mp4 20MB
  193. 15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).mp4 19MB
  194. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).mp4 19MB
  195. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).mp4 18MB
  196. 6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.mp4 18MB
  197. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).mp4 18MB
  198. 4. Pandas Intermediate Topics/25. any() and all().mp4 18MB
  199. 12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.mp4 17MB
  200. 15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.mp4 17MB
  201. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.mp4 16MB
  202. 4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).mp4 15MB
  203. 4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.mp4 13MB
  204. 8. Time Series Data in Pandas Introduction/6. More on pd.date_range().mp4 12MB
  205. 12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.mp4 12MB
  206. 11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).mp4 11MB
  207. 15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).mp4 11MB
  208. 4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).mp4 11MB
  209. 5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).mp4 11MB
  210. 4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).mp4 11MB
  211. 6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.mp4 10MB
  212. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.mp4 10MB
  213. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).mp4 10MB
  214. 8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).mp4 10MB
  215. 6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).mp4 9MB
  216. 17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().mp4 9MB
  217. 8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).mp4 9MB
  218. 3. Pandas Basics/21. Coding Exercise 2 (Intro).mp4 9MB
  219. 6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).mp4 8MB
  220. 4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).mp4 8MB
  221. 19. Appendix 1 Python Crash Course (optional)/1. Intro.mp4 6MB
  222. 3. Pandas Basics/9.1 Finance_Data_Exc.zip.zip 4MB
  223. 3. Pandas Basics/5.1 Video-Lecture-NBs.zip.zip 2MB
  224. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1.1 Final_Project.zip.zip 2MB
  225. 19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).vtt 18KB
  226. 8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().vtt 16KB
  227. 3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.vtt 16KB
  228. 5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.vtt 15KB
  229. 1. Getting Started/7. How to use Jupyter Notebooks.vtt 15KB
  230. 6. Pandas Advanced Topics/18. stack() and unstack().vtt 15KB
  231. 19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.vtt 14KB
  232. 8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).vtt 14KB
  233. 20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.vtt 14KB
  234. 6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.vtt 14KB
  235. 19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).vtt 13KB
  236. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.vtt 13KB
  237. 4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().vtt 13KB
  238. 6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).vtt 13KB
  239. 20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.vtt 13KB
  240. 6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).vtt 13KB
  241. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.vtt 13KB
  242. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.vtt 13KB
  243. 6. Pandas Advanced Topics/16. split-apply-combine applied.vtt 12KB
  244. 19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.vtt 12KB
  245. 5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.vtt 12KB
  246. 5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.vtt 12KB
  247. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).vtt 12KB
  248. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.vtt 12KB
  249. 12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.vtt 12KB
  250. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).vtt 12KB
  251. 4. Pandas Intermediate Topics/30. Handling NA Values missing Values.vtt 11KB
  252. 4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).vtt 11KB
  253. 1. Getting Started/1. Course Overview and how to maximize your learning success.vtt 11KB
  254. 4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).vtt 11KB
  255. 3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).vtt 11KB
  256. 12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).vtt 11KB
  257. 17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.vtt 10KB
  258. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.vtt 10KB
  259. 4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().vtt 10KB
  260. 6. Pandas Advanced Topics/15. split-apply-combine.vtt 10KB
  261. 11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.vtt 10KB
  262. 4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.vtt 10KB
  263. 3. Pandas Basics/19. Summary and Outlook.vtt 10KB
  264. 3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.vtt 10KB
  265. 20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.vtt 10KB
  266. 19. Appendix 1 Python Crash Course (optional)/11. For Loops.vtt 10KB
  267. 19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.vtt 10KB
  268. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.vtt 10KB
  269. 8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().vtt 10KB
  270. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).vtt 10KB
  271. 19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.vtt 10KB
  272. 11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.vtt 10KB
  273. 1. Getting Started/6. Opening a Jupyter Notebook.vtt 10KB
  274. 11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.vtt 10KB
  275. 5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).vtt 9KB
  276. 4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().vtt 9KB
  277. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().vtt 9KB
  278. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.vtt 9KB
  279. 4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.vtt 9KB
  280. 4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.vtt 9KB
  281. 19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).vtt 9KB
  282. 11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.vtt 9KB
  283. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).vtt 9KB
  284. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).vtt 9KB
  285. 5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.vtt 9KB
  286. 8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().vtt 9KB
  287. 8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).vtt 9KB
  288. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).vtt 9KB
  289. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.vtt 9KB
  290. 20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.vtt 9KB
  291. 19. Appendix 1 Python Crash Course (optional)/2. First Steps.vtt 9KB
  292. 3. Pandas Basics/6. Built-in Functions, Attributes and Methods.vtt 9KB
  293. 20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.vtt 9KB
  294. 12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.vtt 9KB
  295. 11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).vtt 9KB
  296. 3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).vtt 9KB
  297. 11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.vtt 9KB
  298. 6. Pandas Advanced Topics/13. Understanding the GroupBy Object.vtt 9KB
  299. 19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).vtt 9KB
  300. 8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.vtt 8KB
  301. 4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).vtt 8KB
  302. 3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).vtt 8KB
  303. 17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.vtt 8KB
  304. 4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.vtt 8KB
  305. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).vtt 8KB
  306. 11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).vtt 8KB
  307. 3. Pandas Basics/11. Selecting Columns.vtt 8KB
  308. 20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.vtt 8KB
  309. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.vtt 8KB
  310. 1. Getting Started/5. Installation of Anaconda.vtt 8KB
  311. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.vtt 8KB
  312. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.vtt 8KB
  313. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).vtt 8KB
  314. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).vtt 8KB
  315. 11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).vtt 8KB
  316. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.vtt 8KB
  317. 19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.vtt 8KB
  318. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).vtt 8KB
  319. 20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.vtt 8KB
  320. 4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().vtt 8KB
  321. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.vtt 7KB
  322. 20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.vtt 7KB
  323. 8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.vtt 7KB
  324. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).vtt 7KB
  325. 3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).vtt 7KB
  326. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().vtt 7KB
  327. 12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.vtt 7KB
  328. 5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).vtt 7KB
  329. 12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.vtt 7KB
  330. 6. Pandas Advanced Topics/3. Removing Rows.vtt 7KB
  331. 5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.vtt 7KB
  332. 6. Pandas Advanced Topics/14. Splitting with many Keys.vtt 7KB
  333. 19. Appendix 1 Python Crash Course (optional)/3. Variables.vtt 7KB
  334. 4. Pandas Intermediate Topics/2. First Steps with Pandas Series.vtt 7KB
  335. 5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).vtt 7KB
  336. 15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.vtt 7KB
  337. 3. Pandas Basics/22. Coding Exercise 2 (Solution).vtt 7KB
  338. 19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.vtt 7KB
  339. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.vtt 7KB
  340. 19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).vtt 7KB
  341. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).vtt 7KB
  342. 11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.vtt 7KB
  343. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).vtt 7KB
  344. 19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.vtt 7KB
  345. 6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.vtt 7KB
  346. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).vtt 7KB
  347. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.vtt 7KB
  348. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.vtt 7KB
  349. 6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).vtt 7KB
  350. 17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().vtt 6KB
  351. 6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).vtt 6KB
  352. 19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.vtt 6KB
  353. 17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.vtt 6KB
  354. 4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.vtt 6KB
  355. 8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.vtt 6KB
  356. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).vtt 6KB
  357. 15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.vtt 6KB
  358. 11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.vtt 6KB
  359. 20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.vtt 6KB
  360. 5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.vtt 6KB
  361. 20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.vtt 6KB
  362. 20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.vtt 6KB
  363. 8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.vtt 6KB
  364. 11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.vtt 6KB
  365. 3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).vtt 6KB
  366. 4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.vtt 6KB
  367. 1. Getting Started/2. Tips How to get the most out of this Course.vtt 6KB
  368. 3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).vtt 6KB
  369. 4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.vtt 6KB
  370. 15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.vtt 6KB
  371. 8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).vtt 5KB
  372. 1. Getting Started/4. FAQ Important Information.html 5KB
  373. 8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).vtt 5KB
  374. 3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).vtt 5KB
  375. 3. Pandas Basics/1. Intro to Tabular Data Pandas.vtt 5KB
  376. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.vtt 5KB
  377. 6. Pandas Advanced Topics/2. Removing Columns.vtt 5KB
  378. 12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.vtt 5KB
  379. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).vtt 5KB
  380. 4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).vtt 5KB
  381. 17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().vtt 5KB
  382. 4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).vtt 5KB
  383. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.vtt 5KB
  384. 14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.vtt 5KB
  385. 3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).vtt 5KB
  386. 6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.vtt 5KB
  387. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).vtt 5KB
  388. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).vtt 5KB
  389. 15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.vtt 5KB
  390. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.vtt 5KB
  391. 12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.vtt 5KB
  392. 17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).vtt 5KB
  393. 15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.vtt 5KB
  394. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).vtt 5KB
  395. 17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().vtt 5KB
  396. 4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().vtt 5KB
  397. 5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).vtt 5KB
  398. 17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).vtt 5KB
  399. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.vtt 5KB
  400. 4. Pandas Intermediate Topics/7. The copy() method.vtt 5KB
  401. 4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).vtt 5KB
  402. 15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.vtt 5KB
  403. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.vtt 4KB
  404. 12. Create, Analyze and Optimize Financial Portfolios/1. Intro.vtt 4KB
  405. 4. Pandas Intermediate Topics/25. any() and all().vtt 4KB
  406. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).vtt 4KB
  407. 3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).vtt 4KB
  408. 4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).vtt 4KB
  409. 4. Pandas Intermediate Topics/33. The agg() method.vtt 4KB
  410. 11. Create and Analyze Financial Indexes/3. Getting the Data.vtt 4KB
  411. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.vtt 4KB
  412. 4. Pandas Intermediate Topics/14. Changing Column Labels.vtt 3KB
  413. 6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.vtt 3KB
  414. 17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.vtt 3KB
  415. 1. Getting Started/3. Did you know that....vtt 3KB
  416. 8. Time Series Data in Pandas Introduction/6. More on pd.date_range().vtt 3KB
  417. 12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).vtt 3KB
  418. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).vtt 3KB
  419. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.vtt 3KB
  420. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).vtt 3KB
  421. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).vtt 3KB
  422. 19. Appendix 1 Python Crash Course (optional)/1. Intro.vtt 3KB
  423. 4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.vtt 2KB
  424. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).vtt 2KB
  425. 6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.vtt 2KB
  426. 12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.vtt 2KB
  427. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).vtt 2KB
  428. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.vtt 2KB
  429. 4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).vtt 2KB
  430. 15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).vtt 2KB
  431. 15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.vtt 2KB
  432. 15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).vtt 2KB
  433. 11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).vtt 2KB
  434. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).vtt 2KB
  435. 4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).vtt 2KB
  436. 3. Pandas Basics/21. Coding Exercise 2 (Intro).vtt 1KB
  437. 17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().vtt 1KB
  438. 4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).vtt 1KB
  439. 5. Data Visualization with Matplotlib and Seaborn/1. Intro.html 1KB
  440. 8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).vtt 1KB
  441. 4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).vtt 1KB
  442. 8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).vtt 1KB
  443. 7. ----- PART 2 FINANCIAL DATA ANALYSIS ------/1. Welcome.html 1KB
  444. 6. Pandas Advanced Topics/7. Adding new Rows (Hands-on).html 1KB
  445. 6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).vtt 1KB
  446. 5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).vtt 1014B
  447. 6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).vtt 1014B
  448. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/1. Intro.html 969B
  449. 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/10. Additional Bonus Question.html 957B
  450. 2. -- PART 1 DATA ANALYSIS WITH PYTHON & PANDAS FROM ZERO TO HERO --/1. Welcome to Part 1 Intro.html 757B
  451. 4. Pandas Intermediate Topics/1. Intro.html 708B
  452. 3. Pandas Basics/15. Position-based Indexing Cheat Sheets.html 700B
  453. 3. Pandas Basics/18. Label-based Indexing Cheat Sheets.html 700B
  454. 6. Pandas Advanced Topics/1. Intro.html 423B
  455. 15. Interactive Financial Charts with Plotly and Cufflinks/10. Coding Exercise 17.html 407B
  456. 3. Pandas Basics/2. Tabular Data Cheat Sheets.html 383B
  457. 4. Pandas Intermediate Topics/4. UPDATE Pandas Version 0.24.0 (Jan 2019).html 369B
  458. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/12. Interpreting the Return Triangle.html 146B
  459. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/5. Trading Strategies.html 146B
  460. 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/9. Simple Returns vs. Log Returns.html 146B
  461. 11. Create and Analyze Financial Indexes/11. VWI.html 146B
  462. 11. Create and Analyze Financial Indexes/2. Financial Indexes.html 146B
  463. 11. Create and Analyze Financial Indexes/5. PWI.html 146B
  464. 11. Create and Analyze Financial Indexes/8. EWI.html 146B
  465. 12. Create, Analyze and Optimize Financial Portfolios/10. Portfolios.html 146B
  466. 12. Create, Analyze and Optimize Financial Portfolios/7. Sharpe Ratio and Risk Free Asset.html 146B
  467. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/12. Beta and Alpha.html 146B
  468. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/3. Two-Fund-Theorem.html 146B
  469. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/6. Risk Diversification.html 146B
  470. 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/8. CAPM.html 146B
  471. 19. Appendix 1 Python Crash Course (optional)/18. Python Basics.html 146B
  472. 20. Appendix 2 Numpy Crash Course (optional)/12. Numpy.html 146B
  473. 3. Pandas Basics/20. Indexing and Slicing.html 146B
  474. 3. Pandas Basics/8. First Steps.html 146B
  475. 4. Pandas Intermediate Topics/16. Pandas Index Objects.html 146B
  476. 4. Pandas Intermediate Topics/26. Sorting and Filtering.html 146B
  477. 4. Pandas Intermediate Topics/9. Pandas Series.html 146B
  478. 6. Pandas Advanced Topics/19. GroupBy.html 146B
  479. 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/10. Risk & Return.html 146B
  480. 0. Websites you may like/[FCS Forum].url 133B
  481. 0. Websites you may like/[FreeCourseSite.com].url 127B
  482. 0. Websites you may like/[CourseClub.ME].url 122B
  483. 18. ------------------ APPENDIX -------------------/1. Welcome to the Appendix.html 66B
  484. 21. Bonus/1. Bonus Lecture.html 66B