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[] Udemy - The Complete Pandas Bootcamp Master your Data in Python

  • 收录时间:2019-12-18 22:14:17
  • 文件大小:10GB
  • 下载次数:50
  • 最近下载:2020-09-25 04:05:37
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文件列表

  1. 22. Python Basics/7. Data Types Lists (Part 2).mp4 134MB
  2. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/4. Olympic Medal Tables (Solution Part 2).mp4 129MB
  3. 22. Python Basics/18. Visualization with Matplotlib.mp4 124MB
  4. 19. Time Series Basics/5. Creating a customized DatetimeIndex with pd.date_range().mp4 115MB
  5. 3. Pandas Basics (DataFrame Basics I)/5. Coding Exercise 0 Coding the Video Lectures.mp4 109MB
  6. 8. Visualization with Matplotlib/3. Customization of Plots.mp4 103MB
  7. 14. Reshaping and Pivoting DataFrames/6. pd.crosstab().mp4 99MB
  8. 12. Merging, Joining, and Concatenating Data/13. Joining on different Column Names Indexes.mp4 95MB
  9. 3. Pandas Basics (DataFrame Basics I)/17. Slicing Rows and Columns with loc (label-based indexing).mp4 91MB
  10. 10. Importing Data/1. Importing csv-files with pd.read_csv.mp4 91MB
  11. 11. Cleaning Data/5. Detection of missing Values.mp4 89MB
  12. 11. Cleaning Data/10. Handling Removing Duplicates.mp4 89MB
  13. 12. Merging, Joining, and Concatenating Data/2. Adding Rows with append() and pd.concat() (Part 1).mp4 88MB
  14. 1. Getting Started/5. Installation of Anaconda.mp4 86MB
  15. 22. Python Basics/11. Conditional Statements (if, elif, else, while).mp4 86MB
  16. 19. Time Series Basics/7. Downsampling Time Series with resample() (Part 1).mp4 85MB
  17. 11. Cleaning Data/6. Removing missing values.mp4 85MB
  18. 15. Data Preparation and Feature Creation/8. Discretization and Binning with pd.qcut().mp4 85MB
  19. 16. Advanced Visualization with Seaborn/3. Categorical Plots.mp4 85MB
  20. 23. The Numpy Package/11. Visualization and (Linear) Regression.mp4 85MB
  21. 13. GroupBy Operations/15. Coding Exercise 13 (Solution).mp4 82MB
  22. 11. Cleaning Data/2. String Operations.mp4 81MB
  23. 12. Merging, Joining, and Concatenating Data/6. Outer Joins with merge().mp4 80MB
  24. 16. Advanced Visualization with Seaborn/4. Joint Plots Regression Plots.mp4 80MB
  25. 11. Cleaning Data/9. Detection of Duplicates.mp4 79MB
  26. 13. GroupBy Operations/12. stack() and unstack().mp4 79MB
  27. 20. Time Series Advanced Financial Time Series/12. Filling NA Values with bfill, ffill and interpolation.mp4 78MB
  28. 22. Python Basics/5. Data Types Strings.mp4 78MB
  29. 4. Pandas Series and Index Objects/5. EXCURSUS Updating Pandas Anaconda.mp4 77MB
  30. 4. Pandas Series and Index Objects/19. Changing Row Index with set_index() and reset_index().mp4 75MB
  31. 7. DataFrame Basics III/9. User-defined Functions with apply(), map() and applymap().mp4 74MB
  32. 10. Importing Data/4. NEW Importing Data from Excel with pd.read_excel().mp4 74MB
  33. 23. The Numpy Package/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4 74MB
  34. 15. Data Preparation and Feature Creation/6. Discretization and Binning with pd.cut() (Part 1).mp4 73MB
  35. 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 73MB
  36. 7. DataFrame Basics III/11. Hierarchical Indexing (Part 2).mp4 73MB
  37. 7. DataFrame Basics III/10. Hierarchical Indexing (Part 1).mp4 73MB
  38. 10. Importing Data/5. Importing messy Data from Excel with pd.read_excel().mp4 72MB
  39. 20. Time Series Advanced Financial Time Series/3. NEW Importing Stock Price Data from Yahoo Finance (it still works!).mp4 72MB
  40. 13. GroupBy Operations/5. split-apply-combine applied.mp4 71MB
  41. 8. Visualization with Matplotlib/2. The plot() method.mp4 70MB
  42. 14. Reshaping and Pivoting DataFrames/2. Transposing Rows and Columns.mp4 68MB
  43. 11. Cleaning Data/1. First Inspection & Handling of inconsistent Data.mp4 68MB
  44. 23. The Numpy Package/7. Generating Random Numbers.mp4 68MB
  45. 1. Getting Started/7. How to use Jupyter Notebooks.mp4 66MB
  46. 4. Pandas Series and Index Objects/9. Indexing and Slicing Pandas Series.mp4 66MB
  47. 5. DataFrame Basics II/5. Advanced Filtering with between(), isin() and ~.mp4 66MB
  48. 1. Getting Started/6. Opening a Jupyter Notebook.mp4 65MB
  49. 23. The Numpy Package/2. Numpy Arrays Vectorization.mp4 65MB
  50. 22. Python Basics/15. User Defined Functions (Part 1).mp4 64MB
  51. 15. Data Preparation and Feature Creation/2. Arithmetic Operations (Part 1).mp4 64MB
  52. 10. Importing Data/2. Importing messy csv-files with pd.read_csv.mp4 63MB
  53. 3. Pandas Basics (DataFrame Basics I)/9. Explore your own Dataset Coding Exercise 1 (Intro).mp4 63MB
  54. 22. Python Basics/6. Data Types Lists (Part 1).mp4 63MB
  55. 3. Pandas Basics (DataFrame Basics I)/19. Summary and Outlook.mp4 62MB
  56. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/3. Chained Indexing How you should NOT do it (Part 1).mp4 60MB
  57. 22. Python Basics/10. Operators & Booleans.mp4 60MB
  58. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/4. Chained Indexing How you should NOT do it (Part 2).mp4 59MB
  59. 15. Data Preparation and Feature Creation/3. Arithmetic Operations (Part 2).mp4 58MB
  60. 22. Python Basics/12. For Loops.mp4 58MB
  61. 14. Reshaping and Pivoting DataFrames/4. Limits of pivot().mp4 58MB
  62. 7. DataFrame Basics III/15. Coding Exercise 8 (Solution).mp4 58MB
  63. 14. Reshaping and Pivoting DataFrames/5. pivot_table().mp4 58MB
  64. 10. Importing Data/6. Importing Data from the Web with pd.read_html().mp4 58MB
  65. 19. Time Series Basics/2. Converting strings to datetime objects with pd.to_datetime().mp4 58MB
  66. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/2. Olympic Medal Tables (Instruction & Hints).mp4 58MB
  67. 5. DataFrame Basics II/15. Coding Exercise 5 (Solution).mp4 58MB
  68. 7. DataFrame Basics III/5. Summary Statistics and Accumulations.mp4 57MB
  69. 22. Python Basics/16. User Defined Functions (Part 2).mp4 57MB
  70. 12. Merging, Joining, and Concatenating Data/3. Adding Rows with pd.concat() (Part 2).mp4 57MB
  71. 3. Pandas Basics (DataFrame Basics I)/4. First Steps (Inspection of Data, Part 2).mp4 57MB
  72. 15. Data Preparation and Feature Creation/10. Scaling Standardization.mp4 56MB
  73. 14. Reshaping and Pivoting DataFrames/3. Pivoting DataFrames with pivot().mp4 56MB
  74. 15. Data Preparation and Feature Creation/11. Creating Dummy Variables.mp4 55MB
  75. 7. DataFrame Basics III/13. String Operations (Part 2).mp4 55MB
  76. 3. Pandas Basics (DataFrame Basics I)/7. Make it easy TAB Completion and Tooltip.mp4 54MB
  77. 7. DataFrame Basics III/2. Sorting DataFrames with sort_index() and sort_values().mp4 54MB
  78. 3. Pandas Basics (DataFrame Basics I)/13. Selecting Rows with iloc (position-based indexing).mp4 54MB
  79. 20. Time Series Advanced Financial Time Series/9. Financial Time Series - Return and Risk.mp4 54MB
  80. 23. The Numpy Package/3. Numpy Arrays Indexing and Slicing.mp4 53MB
  81. 5. DataFrame Basics II/2. Filtering DataFrames by one Condition.mp4 53MB
  82. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/2. Best Practice (How you should do it).mp4 53MB
  83. 22. Python Basics/17. User Defined Functions (Part 3).mp4 52MB
  84. 10. Importing Data/3. OLD Importing Data from Excel with pd.read_excel().mp4 52MB
  85. 3. Pandas Basics (DataFrame Basics I)/3. First Steps (Inspection of Data, Part 1).mp4 52MB
  86. 3. Pandas Basics (DataFrame Basics I)/6. Built-in Functions, Attributes and Methods with Pandas.mp4 51MB
  87. 19. Time Series Basics/10. Advanced Indexing with reindex().mp4 50MB
  88. 13. GroupBy Operations/3. Splitting with many Keys.mp4 50MB
  89. 23. The Numpy Package/8. Performance Issues.mp4 50MB
  90. 5. DataFrame Basics II/8. Removing Rows.mp4 50MB
  91. 22. Python Basics/4. Data Types Integers and Floats.mp4 49MB
  92. 14. Reshaping and Pivoting DataFrames/7. melting DataFrames with melt().mp4 49MB
  93. 19. Time Series Basics/8. Downsampling Time Series with resample (Part 2).mp4 49MB
  94. 1. Getting Started/1. Overview Student FAQ.mp4 48MB
  95. 19. Time Series Basics/4. Indexing and Slicing Time Series.mp4 48MB
  96. 13. GroupBy Operations/4. split-apply-combine explained.mp4 47MB
  97. 13. GroupBy Operations/2. Understanding the GroupBy Object.mp4 46MB
  98. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/6. Simple Rules what to do when....mp4 46MB
  99. 11. Cleaning Data/4. Intro NA values missing values.mp4 46MB
  100. 23. The Numpy Package/9. Case Study Numpy vs. Python Standard Library.mp4 46MB
  101. 11. Cleaning Data/13. Categorical Data.mp4 45MB
  102. 23. The Numpy Package/13. Numpy Quiz Solution.mp4 45MB
  103. 23. The Numpy Package/10. Summary Statistics.mp4 45MB
  104. 13. GroupBy Operations/9. Replacing NA Values by group-specific Values.mp4 45MB
  105. 20. Time Series Advanced Financial Time Series/11. Helpful DatetimeIndex Attributes and Methods.mp4 44MB
  106. 20. Time Series Advanced Financial Time Series/5. Normalizing Time Series to a Base Value (100).mp4 44MB
  107. 23. The Numpy Package/6. Numpy Arrays Boolean Indexing.mp4 44MB
  108. 11. Cleaning Data/11. Detection of Outliers.mp4 44MB
  109. 20. Time Series Advanced Financial Time Series/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 44MB
  110. 1. Getting Started/2. Tips How to get the most out of this course.mp4 44MB
  111. 7. DataFrame Basics III/3. Ranking DataFrames with rank().mp4 43MB
  112. 4. Pandas Series and Index Objects/17. First Steps with Pandas Index Objects.mp4 43MB
  113. 4. Pandas Series and Index Objects/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 43MB
  114. 16. Advanced Visualization with Seaborn/5. Matrixplots Heatmaps.mp4 43MB
  115. 13. GroupBy Operations/10. Generalizing split-apply-combine with apply().mp4 43MB
  116. 15. Data Preparation and Feature Creation/4. TransformationMapping with map().mp4 43MB
  117. 20. Time Series Advanced Financial Time Series/4. Initial Inspection and Visualization.mp4 42MB
  118. 22. Python Basics/8. Data Types Tuples.mp4 42MB
  119. 19. Time Series Basics/1. Importing Time Series Data from csv-files.mp4 42MB
  120. 4. Pandas Series and Index Objects/10. Sorting of Series and Introduction to the inplace - parameter.mp4 41MB
  121. 7. DataFrame Basics III/12. String Operations (Part 1).mp4 41MB
  122. 23. The Numpy Package/1. Introduction to Numpy Arrays.mp4 41MB
  123. 20. Time Series Advanced Financial Time Series/7. The methods diff() and pct_change().mp4 40MB
  124. 7. DataFrame Basics III/8. Coding Exercise 7 (Solution).mp4 40MB
  125. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/9. Coding Exercise 6 (Solution).mp4 39MB
  126. 15. Data Preparation and Feature Creation/9. Floors and Caps.mp4 39MB
  127. 3. Pandas Basics (DataFrame Basics I)/22. Coding Exercise 2 (Solution).mp4 39MB
  128. 12. Merging, Joining, and Concatenating Data/4. Arithmetic with Pandas Objects Data Alignment.mp4 39MB
  129. 11. Cleaning Data/3. Changing Datatype of Columns with astype().mp4 39MB
  130. 19. Time Series Basics/9. The PeriodIndex object.mp4 39MB
  131. 12. Merging, Joining, and Concatenating Data/14. Joining on more than one Column.mp4 39MB
  132. 4. Pandas Series and Index Objects/16. Coding Exercise 3 (Solution).mp4 39MB
  133. 3. Pandas Basics (DataFrame Basics I)/11. Selecting Columns.mp4 39MB
  134. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/3. Olympic Medal Tables (Solution Part 1).mp4 38MB
  135. 22. Python Basics/20. Python Basics Quiz Solution.mp4 38MB
  136. 22. Python Basics/14. Generating Random Numbers.mp4 38MB
  137. 4. Pandas Series and Index Objects/7. Creating Pandas Series (Part 1).mp4 38MB
  138. 4. Pandas Series and Index Objects/13. Manipulating Pandas Series.mp4 38MB
  139. 8. Visualization with Matplotlib/9. Coding Exercise 9 (Solution).mp4 37MB
  140. 22. Python Basics/13. Key words break, pass, continue.mp4 37MB
  141. 8. Visualization with Matplotlib/7. Scatterplots.mp4 36MB
  142. 5. DataFrame Basics II/7. Removing Columns.mp4 36MB
  143. 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.mp4 36MB
  144. 20. Time Series Advanced Financial Time Series/6. The shift() method.mp4 36MB
  145. 23. The Numpy Package/4. Numpy Arrays Shape and Dimensions.mp4 36MB
  146. 12. Merging, Joining, and Concatenating Data/15. pd.merge() and join().mp4 35MB
  147. 13. GroupBy Operations/8. Transformation with transform().mp4 35MB
  148. 19. Time Series Basics/3. Initial Analysis Visualization of Time Series.mp4 35MB
  149. 5. DataFrame Basics II/10. Creating Columns based on other Columns.mp4 35MB
  150. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/5. View vs. Copy.mp4 35MB
  151. 22. Python Basics/2. First Steps.mp4 34MB
  152. 8. Visualization with Matplotlib/5. Histograms (Part 2).mp4 34MB
  153. 4. Pandas Series and Index Objects/21. Renaming Index & Column Labels with rename().mp4 34MB
  154. 15. Data Preparation and Feature Creation/5. Conditional Transformation.mp4 33MB
  155. 13. GroupBy Operations/11. Hierarchical Indexing with Groupby.mp4 33MB
  156. 15. Data Preparation and Feature Creation/7. Discretization and Binning with pd.cut() (Part 2).mp4 33MB
  157. 7. DataFrame Basics III/4. nunique() and nlargest() nsmallest() with DataFrames.mp4 33MB
  158. 12. Merging, Joining, and Concatenating Data/8. Outer Joins (without Intersection) with merge().mp4 31MB
  159. 22. Python Basics/3. Variables.mp4 31MB
  160. 1. Getting Started/3. Did you know that....mp4 31MB
  161. 5. DataFrame Basics II/4. Filtering DataFrames by many Conditions (OR).mp4 31MB
  162. 3. Pandas Basics (DataFrame Basics I)/16. Selecting Rows with loc (label-based indexing).mp4 30MB
  163. 13. GroupBy Operations/7. Advanced aggregation with agg().mp4 30MB
  164. 3. Pandas Basics (DataFrame Basics I)/10. Explore your own Dataset Coding Exercise 1 (Solution).mp4 30MB
  165. 11. Cleaning Data/12. Handling Removing Outliers.mp4 30MB
  166. 15. Data Preparation and Feature Creation/12. String Operations.mp4 30MB
  167. 4. Pandas Series and Index Objects/12. idxmin() and idxmax().mp4 29MB
  168. 12. Merging, Joining, and Concatenating Data/12. Right Joins with merge().mp4 27MB
  169. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/5. Olympic Medal Tables (Solution Part 3).mp4 27MB
  170. 4. Pandas Series and Index Objects/8. Creating Pandas Series (Part 2).mp4 27MB
  171. 4. Pandas Series and Index Objects/24. Coding Exercise 4 (Solution).mp4 26MB
  172. 3. Pandas Basics (DataFrame Basics I)/14. Slicing Rows and Columns with iloc (position-based indexing).mp4 26MB
  173. 5. DataFrame Basics II/3. Filtering DataFrames by many Conditions (AND).mp4 26MB
  174. 3. Pandas Basics (DataFrame Basics I)/1. Intro to Tabular Data Pandas.mp4 26MB
  175. 20. Time Series Advanced Financial Time Series/10. Financial Time Series - Covariance and Correlation.mp4 26MB
  176. 11. Cleaning Data/7. Replacing missing values.mp4 25MB
  177. 8. Visualization with Matplotlib/4. Histograms (Part 1).mp4 25MB
  178. 12. Merging, Joining, and Concatenating Data/11. Left Joins with merge().mp4 24MB
  179. 7. DataFrame Basics III/6. The agg() method.mp4 23MB
  180. 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.mp4 22MB
  181. 3. Pandas Basics (DataFrame Basics I)/12. Selecting Rows with Square Brackets (not advisable).mp4 22MB
  182. 12. Merging, Joining, and Concatenating Data/9. Left Joins (without Intersection) with merge().mp4 22MB
  183. 20. Time Series Advanced Financial Time Series/2. NEW Getting Ready (Installing required package).mp4 22MB
  184. 22. Python Basics/9. Data Types Sets.mp4 21MB
  185. 4. Pandas Series and Index Objects/20. Changing Column Labels.mp4 21MB
  186. 11. Cleaning Data/8. Intro Duplicates.mp4 20MB
  187. 8. Visualization with Matplotlib/6. Barcharts and Piecharts.mp4 20MB
  188. 5. DataFrame Basics II/9. Adding new Columns to a DataFrame.mp4 18MB
  189. 5. DataFrame Basics II/6. any() and all().mp4 18MB
  190. 4. Pandas Series and Index Objects/11. nlargest() and nsmallest().mp4 17MB
  191. 12. Merging, Joining, and Concatenating Data/7. Inner Joins with merge().mp4 16MB
  192. 12. Merging, Joining, and Concatenating Data/10. Right Joins (without Intersection) with merge().mp4 15MB
  193. 15. Data Preparation and Feature Creation/13. Coding Exercise 15 (Intro).mp4 15MB
  194. 4. Pandas Series and Index Objects/18. Creating Index Objects from Scratch.mp4 15MB
  195. 3. Pandas Basics (DataFrame Basics I)/9.1 Pandas-Bootcamp-exc.zip.zip 15MB
  196. 4. Pandas Series and Index Objects/15. Coding Exercise 3 (Intro).mp4 14MB
  197. 5. DataFrame Basics II/11. Adding Columns with insert().mp4 13MB
  198. 10. Importing Data/7. Coding Exercise 10 (Intro).mp4 12MB
  199. 19. Time Series Basics/6. More on pd.date_range().mp4 12MB
  200. 13. GroupBy Operations/14. Coding Exercise 13 (Intro).mp4 12MB
  201. 11. Cleaning Data/14. Coding Exercise 11 (Intro).mp4 11MB
  202. 20. Time Series Advanced Financial Time Series/13. Coding Exercise 17 (Intro).mp4 11MB
  203. 5. DataFrame Basics II/14. Coding Exercise 5 (Intro).mp4 11MB
  204. 13. GroupBy Operations/1. Intro.mp4 10MB
  205. 7. DataFrame Basics III/7. Coding Exercise 7 (Intro).mp4 10MB
  206. 8. Visualization with Matplotlib/8. Coding Exercise 9 (Intro).mp4 10MB
  207. 4. Pandas Series and Index Objects/23. Coding Exercise 4 (Intro).mp4 9MB
  208. 16. Advanced Visualization with Seaborn/6. Coding Exercise 16 (Intro).mp4 9MB
  209. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/8. Coding Exercise 6 (Intro).mp4 9MB
  210. 3. Pandas Basics (DataFrame Basics I)/21. Coding Exercise 2 (Intro).mp4 9MB
  211. 12. Merging, Joining, and Concatenating Data/16. Coding Exercise 12 (Intro).mp4 9MB
  212. 7. DataFrame Basics III/14. Coding Exercise 8 (Intro).mp4 8MB
  213. 14. Reshaping and Pivoting DataFrames/8. Coding Exercsie 14 (Intro).mp4 7MB
  214. 22. Python Basics/1. Intro.mp4 6MB
  215. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/1. Olympic Medal Tables (Intro).mp4 4MB
  216. 3. Pandas Basics (DataFrame Basics I)/5.1 Video_Lecture_NBs.zip.zip 3MB
  217. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/4. Olympic Medal Tables (Solution Part 2).vtt 20KB
  218. 14. Reshaping and Pivoting DataFrames/6. pd.crosstab().vtt 19KB
  219. 22. Python Basics/7. Data Types Lists (Part 2).vtt 18KB
  220. 3. Pandas Basics (DataFrame Basics I)/5. Coding Exercise 0 Coding the Video Lectures.vtt 16KB
  221. 11. Cleaning Data/6. Removing missing values.vtt 16KB
  222. 19. Time Series Basics/5. Creating a customized DatetimeIndex with pd.date_range().vtt 16KB
  223. 11. Cleaning Data/5. Detection of missing Values.vtt 15KB
  224. 16. Advanced Visualization with Seaborn/3. Categorical Plots.vtt 15KB
  225. 1. Getting Started/7. How to use Jupyter Notebooks.vtt 15KB
  226. 22. Python Basics/18. Visualization with Matplotlib.vtt 14KB
  227. 13. GroupBy Operations/12. stack() and unstack().vtt 14KB
  228. 7. DataFrame Basics III/9. User-defined Functions with apply(), map() and applymap().vtt 14KB
  229. 12. Merging, Joining, and Concatenating Data/13. Joining on different Column Names Indexes.vtt 14KB
  230. 19. Time Series Basics/7. Downsampling Time Series with resample() (Part 1).vtt 14KB
  231. 23. The Numpy Package/13. Numpy Quiz Solution.vtt 14KB
  232. 15. Data Preparation and Feature Creation/8. Discretization and Binning with pd.qcut().vtt 14KB
  233. 12. Merging, Joining, and Concatenating Data/6. Outer Joins with merge().vtt 14KB
  234. 14. Reshaping and Pivoting DataFrames/5. pivot_table().vtt 14KB
  235. 12. Merging, Joining, and Concatenating Data/2. Adding Rows with append() and pd.concat() (Part 1).vtt 14KB
  236. 11. Cleaning Data/10. Handling Removing Duplicates.vtt 14KB
  237. 22. Python Basics/11. Conditional Statements (if, elif, else, while).vtt 13KB
  238. 13. GroupBy Operations/15. Coding Exercise 13 (Solution).vtt 13KB
  239. 11. Cleaning Data/9. Detection of Duplicates.vtt 13KB
  240. 4. Pandas Series and Index Objects/3. Analyzing Numerical Series with unique(), nunique() and value_counts().vtt 13KB
  241. 11. Cleaning Data/2. String Operations.vtt 13KB
  242. 15. Data Preparation and Feature Creation/2. Arithmetic Operations (Part 1).vtt 13KB
  243. 7. DataFrame Basics III/11. Hierarchical Indexing (Part 2).vtt 13KB
  244. 15. Data Preparation and Feature Creation/3. Arithmetic Operations (Part 2).vtt 13KB
  245. 10. Importing Data/4. NEW Importing Data from Excel with pd.read_excel().vtt 13KB
  246. 23. The Numpy Package/11. Visualization and (Linear) Regression.vtt 13KB
  247. 13. GroupBy Operations/5. split-apply-combine applied.vtt 12KB
  248. 22. Python Basics/20. Python Basics Quiz Solution.vtt 12KB
  249. 15. Data Preparation and Feature Creation/6. Discretization and Binning with pd.cut() (Part 1).vtt 12KB
  250. 16. Advanced Visualization with Seaborn/4. Joint Plots Regression Plots.vtt 12KB
  251. 8. Visualization with Matplotlib/3. Customization of Plots.vtt 12KB
  252. 11. Cleaning Data/1. First Inspection & Handling of inconsistent Data.vtt 12KB
  253. 14. Reshaping and Pivoting DataFrames/2. Transposing Rows and Columns.vtt 11KB
  254. 7. DataFrame Basics III/10. Hierarchical Indexing (Part 1).vtt 11KB
  255. 5. DataFrame Basics II/2. Filtering DataFrames by one Condition.vtt 11KB
  256. 14. Reshaping and Pivoting DataFrames/4. Limits of pivot().vtt 11KB
  257. 3. Pandas Basics (DataFrame Basics I)/17. Slicing Rows and Columns with loc (label-based indexing).vtt 11KB
  258. 10. Importing Data/3. OLD Importing Data from Excel with pd.read_excel().vtt 11KB
  259. 7. DataFrame Basics III/13. String Operations (Part 2).vtt 10KB
  260. 1. Getting Started/1. Overview Student FAQ.vtt 10KB
  261. 20. Time Series Advanced Financial Time Series/12. Filling NA Values with bfill, ffill and interpolation.vtt 10KB
  262. 4. Pandas Series and Index Objects/19. Changing Row Index with set_index() and reset_index().vtt 10KB
  263. 13. GroupBy Operations/4. split-apply-combine explained.vtt 10KB
  264. 7. DataFrame Basics III/5. Summary Statistics and Accumulations.vtt 10KB
  265. 3. Pandas Basics (DataFrame Basics I)/19. Summary and Outlook.vtt 10KB
  266. 14. Reshaping and Pivoting DataFrames/3. Pivoting DataFrames with pivot().vtt 10KB
  267. 4. Pandas Series and Index Objects/9. Indexing and Slicing Pandas Series.vtt 10KB
  268. 12. Merging, Joining, and Concatenating Data/3. Adding Rows with pd.concat() (Part 2).vtt 10KB
  269. 23. The Numpy Package/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.vtt 10KB
  270. 22. Python Basics/12. For Loops.vtt 10KB
  271. 22. Python Basics/5. Data Types Strings.vtt 10KB
  272. 19. Time Series Basics/2. Converting strings to datetime objects with pd.to_datetime().vtt 10KB
  273. 3. Pandas Basics (DataFrame Basics I)/9. Explore your own Dataset Coding Exercise 1 (Intro).vtt 10KB
  274. 15. Data Preparation and Feature Creation/11. Creating Dummy Variables.vtt 10KB
  275. 22. Python Basics/10. Operators & Booleans.vtt 10KB
  276. 1. Getting Started/6. Opening a Jupyter Notebook.vtt 10KB
  277. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/2. Best Practice (How you should do it).vtt 10KB
  278. 8. Visualization with Matplotlib/2. The plot() method.vtt 9KB
  279. 10. Importing Data/2. Importing messy csv-files with pd.read_csv.vtt 9KB
  280. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/3. Chained Indexing How you should NOT do it (Part 1).vtt 9KB
  281. 7. DataFrame Basics III/2. Sorting DataFrames with sort_index() and sort_values().vtt 9KB
  282. 14. Reshaping and Pivoting DataFrames/7. melting DataFrames with melt().vtt 9KB
  283. 7. DataFrame Basics III/15. Coding Exercise 8 (Solution).vtt 9KB
  284. 20. Time Series Advanced Financial Time Series/8. Measuring Stock Performance with MEAN Returns and STD of Returns.vtt 9KB
  285. 4. Pandas Series and Index Objects/10. Sorting of Series and Introduction to the inplace - parameter.vtt 9KB
  286. 11. Cleaning Data/4. Intro NA values missing values.vtt 9KB
  287. 5. DataFrame Basics II/15. Coding Exercise 5 (Solution).vtt 9KB
  288. 22. Python Basics/15. User Defined Functions (Part 1).vtt 9KB
  289. 11. Cleaning Data/11. Detection of Outliers.vtt 9KB
  290. 16. Advanced Visualization with Seaborn/5. Matrixplots Heatmaps.vtt 9KB
  291. 19. Time Series Basics/10. Advanced Indexing with reindex().vtt 9KB
  292. 19. Time Series Basics/8. Downsampling Time Series with resample (Part 2).vtt 9KB
  293. 20. Time Series Advanced Financial Time Series/3. NEW Importing Stock Price Data from Yahoo Finance (it still works!).vtt 9KB
  294. 20. Time Series Advanced Financial Time Series/9. Financial Time Series - Return and Risk.vtt 9KB
  295. 23. The Numpy Package/7. Generating Random Numbers.vtt 9KB
  296. 22. Python Basics/2. First Steps.vtt 9KB
  297. 13. GroupBy Operations/10. Generalizing split-apply-combine with apply().vtt 9KB
  298. 3. Pandas Basics (DataFrame Basics I)/6. Built-in Functions, Attributes and Methods with Pandas.vtt 9KB
  299. 23. The Numpy Package/2. Numpy Arrays Vectorization.vtt 9KB
  300. 3. Pandas Basics (DataFrame Basics I)/4. First Steps (Inspection of Data, Part 2).vtt 9KB
  301. 13. GroupBy Operations/2. Understanding the GroupBy Object.vtt 9KB
  302. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/6. Simple Rules what to do when....vtt 9KB
  303. 15. Data Preparation and Feature Creation/10. Scaling Standardization.vtt 9KB
  304. 22. Python Basics/6. Data Types Lists (Part 1).vtt 9KB
  305. 19. Time Series Basics/1. Importing Time Series Data from csv-files.vtt 8KB
  306. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/2. Olympic Medal Tables (Instruction & Hints).vtt 8KB
  307. 4. Pandas Series and Index Objects/13. Manipulating Pandas Series.vtt 8KB
  308. 12. Merging, Joining, and Concatenating Data/14. Joining on more than one Column.vtt 8KB
  309. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/4. Chained Indexing How you should NOT do it (Part 2).vtt 8KB
  310. 11. Cleaning Data/13. Categorical Data.vtt 8KB
  311. 7. DataFrame Basics III/12. String Operations (Part 1).vtt 8KB
  312. 12. Merging, Joining, and Concatenating Data/4. Arithmetic with Pandas Objects Data Alignment.vtt 8KB
  313. 5. DataFrame Basics II/5. Advanced Filtering with between(), isin() and ~.vtt 8KB
  314. 10. Importing Data/6. Importing Data from the Web with pd.read_html().vtt 8KB
  315. 3. Pandas Basics (DataFrame Basics I)/11. Selecting Columns.vtt 8KB
  316. 7. DataFrame Basics III/3. Ranking DataFrames with rank().vtt 8KB
  317. 15. Data Preparation and Feature Creation/9. Floors and Caps.vtt 8KB
  318. 23. The Numpy Package/1. Introduction to Numpy Arrays.vtt 8KB
  319. 10. Importing Data/5. Importing messy Data from Excel with pd.read_excel().vtt 8KB
  320. 1. Getting Started/5. Installation of Anaconda.vtt 8KB
  321. 22. Python Basics/17. User Defined Functions (Part 3).vtt 8KB
  322. 13. GroupBy Operations/9. Replacing NA Values by group-specific Values.vtt 8KB
  323. 22. Python Basics/4. Data Types Integers and Floats.vtt 8KB
  324. 23. The Numpy Package/9. Case Study Numpy vs. Python Standard Library.vtt 8KB
  325. 4. Pandas Series and Index Objects/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().vtt 8KB
  326. 20. Time Series Advanced Financial Time Series/6. The shift() method.vtt 7KB
  327. 19. Time Series Basics/4. Indexing and Slicing Time Series.vtt 7KB
  328. 23. The Numpy Package/10. Summary Statistics.vtt 7KB
  329. 3. Pandas Basics (DataFrame Basics I)/13. Selecting Rows with iloc (position-based indexing).vtt 7KB
  330. 20. Time Series Advanced Financial Time Series/7. The methods diff() and pct_change().vtt 7KB
  331. 15. Data Preparation and Feature Creation/5. Conditional Transformation.vtt 7KB
  332. 5. DataFrame Basics II/8. Removing Rows.vtt 7KB
  333. 23. The Numpy Package/3. Numpy Arrays Indexing and Slicing.vtt 7KB
  334. 8. Visualization with Matplotlib/7. Scatterplots.vtt 7KB
  335. 13. GroupBy Operations/3. Splitting with many Keys.vtt 7KB
  336. 22. Python Basics/3. Variables.vtt 7KB
  337. 11. Cleaning Data/3. Changing Datatype of Columns with astype().vtt 7KB
  338. 5. DataFrame Basics II/10. Creating Columns based on other Columns.vtt 7KB
  339. 4. Pandas Series and Index Objects/2. First Steps with Pandas Series.vtt 7KB
  340. 15. Data Preparation and Feature Creation/4. TransformationMapping with map().vtt 7KB
  341. 8. Visualization with Matplotlib/5. Histograms (Part 2).vtt 7KB
  342. 22. Python Basics/14. Generating Random Numbers.vtt 7KB
  343. 20. Time Series Advanced Financial Time Series/5. Normalizing Time Series to a Base Value (100).vtt 7KB
  344. 22. Python Basics/16. User Defined Functions (Part 2).vtt 7KB
  345. 22. Python Basics/8. Data Types Tuples.vtt 7KB
  346. 13. GroupBy Operations/11. Hierarchical Indexing with Groupby.vtt 7KB
  347. 4. Pandas Series and Index Objects/16. Coding Exercise 3 (Solution).vtt 7KB
  348. 13. GroupBy Operations/8. Transformation with transform().vtt 7KB
  349. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/9. Coding Exercise 6 (Solution).vtt 6KB
  350. 3. Pandas Basics (DataFrame Basics I)/22. Coding Exercise 2 (Solution).vtt 6KB
  351. 22. Python Basics/13. Key words break, pass, continue.vtt 6KB
  352. 4. Pandas Series and Index Objects/7. Creating Pandas Series (Part 1).vtt 6KB
  353. 20. Time Series Advanced Financial Time Series/11. Helpful DatetimeIndex Attributes and Methods.vtt 6KB
  354. 4. Pandas Series and Index Objects/5. EXCURSUS Updating Pandas Anaconda.vtt 6KB
  355. 19. Time Series Basics/9. The PeriodIndex object.vtt 6KB
  356. 16. Advanced Visualization with Seaborn/2. First Steps in Seaborn.vtt 6KB
  357. 23. The Numpy Package/6. Numpy Arrays Boolean Indexing.vtt 6KB
  358. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/5. View vs. Copy.vtt 6KB
  359. 13. GroupBy Operations/7. Advanced aggregation with agg().vtt 6KB
  360. 12. Merging, Joining, and Concatenating Data/15. pd.merge() and join().vtt 6KB
  361. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/5. Olympic Medal Tables (Solution Part 3).vtt 6KB
  362. 23. The Numpy Package/4. Numpy Arrays Shape and Dimensions.vtt 6KB
  363. 23. The Numpy Package/8. Performance Issues.vtt 6KB
  364. 11. Cleaning Data/12. Handling Removing Outliers.vtt 6KB
  365. 19. Time Series Basics/3. Initial Analysis Visualization of Time Series.vtt 6KB
  366. 3. Pandas Basics (DataFrame Basics I)/3. First Steps (Inspection of Data, Part 1).vtt 6KB
  367. 4. Pandas Series and Index Objects/17. First Steps with Pandas Index Objects.vtt 6KB
  368. 1. Getting Started/2. Tips How to get the most out of this course.vtt 6KB
  369. 4. Pandas Series and Index Objects/8. Creating Pandas Series (Part 2).vtt 6KB
  370. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/3. Olympic Medal Tables (Solution Part 1).vtt 6KB
  371. 3. Pandas Basics (DataFrame Basics I)/16. Selecting Rows with loc (label-based indexing).vtt 6KB
  372. 11. Cleaning Data/8. Intro Duplicates.vtt 6KB
  373. 7. DataFrame Basics III/4. nunique() and nlargest() nsmallest() with DataFrames.vtt 6KB
  374. 1. Getting Started/4. More FAQ Important Information.html 5KB
  375. 15. Data Preparation and Feature Creation/7. Discretization and Binning with pd.cut() (Part 2).vtt 5KB
  376. 4. Pandas Series and Index Objects/12. idxmin() and idxmax().vtt 5KB
  377. 3. Pandas Basics (DataFrame Basics I)/14. Slicing Rows and Columns with iloc (position-based indexing).vtt 5KB
  378. 5. DataFrame Basics II/7. Removing Columns.vtt 5KB
  379. 3. Pandas Basics (DataFrame Basics I)/1. Intro to Tabular Data Pandas.vtt 5KB
  380. 20. Time Series Advanced Financial Time Series/4. Initial Inspection and Visualization.vtt 5KB
  381. 7. DataFrame Basics III/8. Coding Exercise 7 (Solution).vtt 5KB
  382. 5. DataFrame Basics II/4. Filtering DataFrames by many Conditions (OR).vtt 5KB
  383. 8. Visualization with Matplotlib/9. Coding Exercise 9 (Solution).vtt 5KB
  384. 20. Time Series Advanced Financial Time Series/10. Financial Time Series - Covariance and Correlation.vtt 5KB
  385. 12. Merging, Joining, and Concatenating Data/8. Outer Joins (without Intersection) with merge().vtt 5KB
  386. 15. Data Preparation and Feature Creation/12. String Operations.vtt 5KB
  387. 4. Pandas Series and Index Objects/21. Renaming Index & Column Labels with rename().vtt 5KB
  388. 8. Visualization with Matplotlib/4. Histograms (Part 1).vtt 5KB
  389. 12. Merging, Joining, and Concatenating Data/11. Left Joins with merge().vtt 5KB
  390. 1. Getting Started/3. Did you know that....vtt 5KB
  391. 11. Cleaning Data/7. Replacing missing values.vtt 5KB
  392. 5. DataFrame Basics II/3. Filtering DataFrames by many Conditions (AND).vtt 5KB
  393. 3. Pandas Basics (DataFrame Basics I)/10. Explore your own Dataset Coding Exercise 1 (Solution).vtt 4KB
  394. 4. Pandas Series and Index Objects/24. Coding Exercise 4 (Solution).vtt 4KB
  395. 5. DataFrame Basics II/6. any() and all().vtt 4KB
  396. 12. Merging, Joining, and Concatenating Data/12. Right Joins with merge().vtt 4KB
  397. 8. Visualization with Matplotlib/6. Barcharts and Piecharts.vtt 4KB
  398. 3. Pandas Basics (DataFrame Basics I)/12. Selecting Rows with Square Brackets (not advisable).vtt 4KB
  399. 7. DataFrame Basics III/6. The agg() method.vtt 4KB
  400. 4. Pandas Series and Index Objects/11. nlargest() and nsmallest().vtt 4KB
  401. 22. Python Basics/9. Data Types Sets.vtt 4KB
  402. 4. Pandas Series and Index Objects/20. Changing Column Labels.vtt 3KB
  403. 5. DataFrame Basics II/9. Adding new Columns to a DataFrame.vtt 3KB
  404. 12. Merging, Joining, and Concatenating Data/9. Left Joins (without Intersection) with merge().vtt 3KB
  405. 19. Time Series Basics/6. More on pd.date_range().vtt 3KB
  406. 5. DataFrame Basics II/11. Adding Columns with insert().vtt 3KB
  407. 4. Pandas Series and Index Objects/18. Creating Index Objects from Scratch.vtt 3KB
  408. 12. Merging, Joining, and Concatenating Data/7. Inner Joins with merge().vtt 3KB
  409. 15. Data Preparation and Feature Creation/13. Coding Exercise 15 (Intro).vtt 3KB
  410. 12. Merging, Joining, and Concatenating Data/5. EXCURSUS Comparing two DataFrames Identify Differences.html 3KB
  411. 22. Python Basics/1. Intro.vtt 3KB
  412. 10. Importing Data/7. Coding Exercise 10 (Intro).vtt 2KB
  413. 20. Time Series Advanced Financial Time Series/2. NEW Getting Ready (Installing required package).vtt 2KB
  414. 13. GroupBy Operations/1. Intro.vtt 2KB
  415. 12. Merging, Joining, and Concatenating Data/10. Right Joins (without Intersection) with merge().vtt 2KB
  416. 4. Pandas Series and Index Objects/15. Coding Exercise 3 (Intro).vtt 2KB
  417. 13. GroupBy Operations/14. Coding Exercise 13 (Intro).vtt 2KB
  418. 11. Cleaning Data/14. Coding Exercise 11 (Intro).vtt 2KB
  419. 20. Time Series Advanced Financial Time Series/13. Coding Exercise 17 (Intro).vtt 2KB
  420. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/8. Coding Exercise 6 (Intro).vtt 2KB
  421. 5. DataFrame Basics II/14. Coding Exercise 5 (Intro).vtt 1KB
  422. 4. Pandas Series and Index Objects/23. Coding Exercise 4 (Intro).vtt 1KB
  423. 8. Visualization with Matplotlib/8. Coding Exercise 9 (Intro).vtt 1KB
  424. 24. Bonus/1. Bonus.html 1KB
  425. 3. Pandas Basics (DataFrame Basics I)/21. Coding Exercise 2 (Intro).vtt 1KB
  426. 7. DataFrame Basics III/7. Coding Exercise 7 (Intro).vtt 1KB
  427. 12. Merging, Joining, and Concatenating Data/16. Coding Exercise 12 (Intro).vtt 1KB
  428. 5. DataFrame Basics II/12. Adding new Rows (hands-on approach).html 1KB
  429. 7. DataFrame Basics III/14. Coding Exercise 8 (Intro).vtt 1KB
  430. 16. Advanced Visualization with Seaborn/6. Coding Exercise 16 (Intro).vtt 1KB
  431. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/1. Intro.html 1019B
  432. 20. Time Series Advanced Financial Time Series/1. Intro.html 976B
  433. 14. Reshaping and Pivoting DataFrames/8. Coding Exercsie 14 (Intro).vtt 968B
  434. 14. Reshaping and Pivoting DataFrames/1. Intro.html 894B
  435. 4. Pandas Series and Index Objects/1. Intro.html 838B
  436. 9. -----PART II FULL DATA WORKFLOW A-Z------/1. Welcome to PART II Full Data Analysis Workflow.html 818B
  437. 16. Advanced Visualization with Seaborn/1. Intro.html 775B
  438. 17. -----PART III COMPREHENSIVE PROJECT CHALLENGE -------/1. Olympic Medal Tables (Intro).vtt 748B
  439. 3. Pandas Basics (DataFrame Basics I)/18. Label-based Indexing Cheat Sheets.html 711B
  440. 15. Data Preparation and Feature Creation/1. Intro.html 710B
  441. 3. Pandas Basics (DataFrame Basics I)/15. Position-based Indexing Cheat Sheets.html 700B
  442. 8. Visualization with Matplotlib/1. Intro.html 680B
  443. 18. --------PART IV MANAGING TIME SERIES DATA WITH PANDAS----------/1. Welcome to Part III Time Series Data.html 660B
  444. 7. DataFrame Basics III/1. Intro.html 643B
  445. 2. --------PART I BUILDING BLOCKS--------/1. Welcome to PART I - Pandas Building Blocks.html 606B
  446. 12. Merging, Joining, and Concatenating Data/1. Intro.html 585B
  447. 21. ------APPENDIX PYTHON BASICS AND NUMPY--------/1. Welcome to the Appendix.html 429B
  448. 3. Pandas Basics (DataFrame Basics I)/2. Tabular Data Cheat Sheets.html 421B
  449. 10. Importing Data/8. Coding Exercise 10 (Solution).html 406B
  450. 5. DataFrame Basics II/1. Intro.html 406B
  451. 11. Cleaning Data/15. Coding Exercise 11 (Solution).html 398B
  452. 12. Merging, Joining, and Concatenating Data/17. Coding Exercise 12 (Solution).html 398B
  453. 14. Reshaping and Pivoting DataFrames/9. Coding Exercise 14 (Solution).html 398B
  454. 15. Data Preparation and Feature Creation/14. Coding Exercise 15 (Solution).html 398B
  455. 16. Advanced Visualization with Seaborn/7. Coding Exercise 16 (Solution).html 398B
  456. 20. Time Series Advanced Financial Time Series/14. Coding Exercise 17 (Solution).html 398B
  457. 4. Pandas Series and Index Objects/4. UPDATE Pandas Version 0.24.0 (Jan 2019).html 369B
  458. 3. Pandas Basics (DataFrame Basics I)/6.1 DataFrame Methods and Attributes.html 141B
  459. 3. Pandas Basics (DataFrame Basics I)/6.2 Pandas Series Methods and Attributes.html 138B
  460. 13. GroupBy Operations/13. GroupBy 2.html 123B
  461. 13. GroupBy Operations/6. GroupBy 1.html 123B
  462. 22. Python Basics/19. Python Basics.html 123B
  463. 23. The Numpy Package/12. Numpy.html 123B
  464. 3. Pandas Basics (DataFrame Basics I)/20. Indexing and Slicing.html 123B
  465. 3. Pandas Basics (DataFrame Basics I)/8. First Steps.html 123B
  466. 4. Pandas Series and Index Objects/14. Pandas Series.html 123B
  467. 4. Pandas Series and Index Objects/22. Pandas Index objects.html 123B
  468. 5. DataFrame Basics II/13. DataFrame Basics II.html 123B
  469. 6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/7. Manipulating DataFrames Slices.html 123B
  470. 4. Pandas Series and Index Objects/5.1 Updating Anaconda (Link).html 119B
  471. 1. Getting Started/5.1 Installing on Windows.html 112B
  472. 1. Getting Started/5.2 Installing on macOS.html 111B
  473. 1. Getting Started/5.3 Installing on Linux.html 110B
  474. [DesireCourse.Net].url 51B
  475. [CourseClub.Me].url 48B