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[] Udemy - Data Analysis with Pandas and Python

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文件列表

  1. 1. Installation and Setup/6. Mac OS - Update Anaconda Libraries.mp4 35MB
  2. 1. Installation and Setup/1. Introduction to the Course.mp4 34MB
  3. 10. Working with Dates and Times/16. More Fun with pd.DateOffset Objects.mp4 32MB
  4. 4. DataFrames II/2. Filter a DataFrame Based on A Condition.mp4 27MB
  5. 9. Merging, Joining, and Concatenating/7. Outer Joins.mp4 26MB
  6. 5. DataFrames III/3. Retrieve Rows by Index Label with .loc[].mp4 26MB
  7. 10. Working with Dates and Times/15. pd.DateOffset Objects.mp4 26MB
  8. 10. Working with Dates and Times/11. Import Financial Data Set with pandas_datareader Library.mp4 25MB
  9. 4. DataFrames II/1. This Module's Dataset + Memory Optimization.mp4 24MB
  10. 3. DataFrames I/11. The .astype() Method.mp4 24MB
  11. 8. GroupBy/2. First Operations with groupby Object.mp4 23MB
  12. 10. Working with Dates and Times/5. The pd.to_datetime() Method.mp4 23MB
  13. 9. Merging, Joining, and Concatenating/10. Merging by Indexes with the left_index and right_index Parameters.mp4 23MB
  14. 7. MultiIndex/14. The .pivot_table() Method.mp4 22MB
  15. 1. Installation and Setup/7. Mac OS - Unpack Course Materials + The Startdown and Shutdown Process.mp4 22MB
  16. 8. GroupBy/7. Iterating through Groups.mp4 21MB
  17. 2. Series/7. Import Series with the .read_csv() Method.mp4 21MB
  18. 7. MultiIndex/2. Create a MultiIndex with the set_index() Method.mp4 21MB
  19. 9. Merging, Joining, and Concatenating/8. Left Joins.mp4 21MB
  20. 5. DataFrames III/8. Set Multiple Values in DataFrame.mp4 21MB
  21. 8. GroupBy/4. Methods on the Groupby Object and DataFrame Columns.mp4 20MB
  22. 9. Merging, Joining, and Concatenating/9. The left_on and right_on Parameters.mp4 20MB
  23. 5. DataFrames III/14. The .query() Method.mp4 20MB
  24. 14. Options and Settings/2. Changing pandas Options with Attributes and Dot Syntax.mp4 20MB
  25. 10. Working with Dates and Times/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4 20MB
  26. 10. Working with Dates and Times/13. Timestamp Object Attributes.mp4 20MB
  27. 4. DataFrames II/8. The .duplicated() Method.mp4 20MB
  28. 10. Working with Dates and Times/18. Timedeltas in a Dataset.mp4 20MB
  29. 3. DataFrames I/9. Drop Rows with Null Values.mp4 19MB
  30. 12. Input and Output/6. Import Excel File into pandas.mp4 19MB
  31. 1. Installation and Setup/10. Windows - Access the Command Prompt and Update Anaconda Libraries.mp4 19MB
  32. 13. Visualization/2. The .plot() Method.mp4 19MB
  33. 5. DataFrames III/5. The Catch-All .ix[] Method.mp4 19MB
  34. 10. Working with Dates and Times/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4 19MB
  35. 10. Working with Dates and Times/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4 18MB
  36. 2. Series/6. Parameters and Arguments.mp4 18MB
  37. 3. DataFrames I/7. Broadcasting Operations.mp4 18MB
  38. 2. Series/2. Create A Series Object from a Python List.mp4 18MB
  39. 1. Installation and Setup/4. Mac OS - Install Anaconda Distribution.mp4 18MB
  40. 9. Merging, Joining, and Concatenating/5. Inner Joins, Part 1.mp4 18MB
  41. 12. Input and Output/7. Export Excel File.mp4 18MB
  42. 9. Merging, Joining, and Concatenating/6. Inner Joins, Part 2.mp4 18MB
  43. 3. DataFrames I/1. Intro to DataFrames I Module.mp4 18MB
  44. 4. DataFrames II/9. The .drop_duplicates() Method.mp4 18MB
  45. 6. Working with Text Data/7. Split Strings by Characters with .str.split() Method.mp4 18MB
  46. 7. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp4 17MB
  47. 7. MultiIndex/15. The pd.melt() Method.mp4 17MB
  48. 3. DataFrames I/6. Add New Column to DataFrame.mp4 17MB
  49. 4. DataFrames II/7. The .between() Method.mp4 17MB
  50. 4. DataFrames II/4. Filter with More than One Condition (OR - ).mp4 17MB
  51. 10. Working with Dates and Times/2. Review of Python's datetime Module.mp4 17MB
  52. 7. MultiIndex/3. The .get_level_values() Method.mp4 17MB
  53. 10. Working with Dates and Times/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4 16MB
  54. 11. Panels/2. The Axes of a Panel Object.mp4 16MB
  55. 5. DataFrames III/10. Delete Rows or Columns from a DataFrame.mp4 16MB
  56. 6. Working with Text Data/3. The .str.replace() Method.mp4 16MB
  57. 11. Panels/9. Transpose a Panel with the .transpose() Method.mp4 16MB
  58. 3. DataFrames I/2. Shared Methods and Attributes between Series and DataFrames.mp4 16MB
  59. 6. Working with Text Data/4. Filtering with String Methods.mp4 16MB
  60. 1. Installation and Setup/11. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp4 15MB
  61. 5. DataFrames III/17. The .copy() Method.mp4 15MB
  62. 10. Working with Dates and Times/17. The pandas Timedelta Object.mp4 15MB
  63. 6. Working with Text Data/9. The expand and n Parameters of the .str.split() Method.mp4 15MB
  64. 1. Installation and Setup/9. Windows - Install Anaconda Distribution.mp4 15MB
  65. 6. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp4 15MB
  66. 3. DataFrames I/4. Select One Column from a DataFrame.mp4 15MB
  67. 7. MultiIndex/11. The .unstack() Method, Part 2.mp4 15MB
  68. 8. GroupBy/1. Intro to the Groupby Module.mp4 14MB
  69. 14. Options and Settings/3. Changing pandas Options with Methods.mp4 14MB
  70. 6. Working with Text Data/1. Intro to the Working with Text Data Module.mp4 14MB
  71. 2. Series/16. Extract Series Values by Index Label.mp4 14MB
  72. 10. Working with Dates and Times/9. The .dt Accessor.mp4 14MB
  73. 11. Panels/1. Intro to the Module + Fetch Panel Dataset from Google Finance.mp4 14MB
  74. 11. Panels/8. The .minor_xs() Method.mp4 14MB
  75. 5. DataFrames III/13. Filtering with the .where() Method.mp4 14MB
  76. 11. Panels/5. Extracting with the .loc, .iloc, and .ix Methods.mp4 14MB
  77. 5. DataFrames III/16. The .apply() Method with Row Values.mp4 13MB
  78. 5. DataFrames III/9. Rename Index Labels or Columns in a DataFrame.mp4 13MB
  79. 5. DataFrames III/4. Retrieve Rows by Index Position with .iloc[].mp4 13MB
  80. 3. DataFrames I/12. Sort a DataFrame with the .sort_values() Method, Part I.mp4 13MB
  81. 9. Merging, Joining, and Concatenating/3. The pd.concat() Method, Part 2.mp4 13MB
  82. 7. MultiIndex/9. The .stack() Method.mp4 13MB
  83. 5. DataFrames III/2. The .set_index() and .reset_index() Methods.mp4 13MB
  84. 8. GroupBy/6. The .agg() Method.mp4 13MB
  85. 3. DataFrames I/15. Rank Values with the .rank() Method.mp4 13MB
  86. 2. Series/22. The .map() Method.mp4 13MB
  87. 3. DataFrames I/3. Differences between Shared Methods.mp4 13MB
  88. 2. Series/4. Intro to Attributes.mp4 13MB
  89. 10. Working with Dates and Times/3. The pandas Timestamp Object.mp4 13MB
  90. 9. Merging, Joining, and Concatenating/2. The pd.concat() Method, Part 1.mp4 13MB
  91. 4. DataFrames II/5. The .isin() Method.mp4 13MB
  92. 5. DataFrames III/6. Second Arguments to .loc[], .iloc[], and .ix[] Methods.mp4 12MB
  93. 2. Series/21. The .apply() Method.mp4 12MB
  94. 13. Visualization/4. Bar Graphs.mp4 12MB
  95. 4. DataFrames II/6. The .isnull() and .notnull() Methods.mp4 12MB
  96. 13. Visualization/6. Histograms.mp4 12MB
  97. 11. Panels/7. The .major_xs() Method.mp4 12MB
  98. 7. MultiIndex/13. The .pivot() Method.mp4 12MB
  99. 5. DataFrames III/12. The .nsmallest() and .nlargest() Methods.mp4 12MB
  100. 13. Visualization/3. Modifying Aesthetics with Templates.mp4 12MB
  101. 1. Installation and Setup/17. Python Crash Course, Part 1 - Data Types and Variables.mp4 12MB
  102. 7. MultiIndex/12. The .unstack() Method, Part 3.mp4 12MB
  103. 6. Working with Text Data/8. More Practice with Splits.mp4 12MB
  104. 7. MultiIndex/7. The .transpose() Method and MultiIndex on Column Level.mp4 12MB
  105. 5. DataFrames III/15. A Review of the .apply() Method on Single Columns.mp4 12MB
  106. 1. Installation and Setup/13. Cell Types and Cell Modes.mp4 12MB
  107. 2. Series/10. More Series Attributes.mp4 12MB
  108. 1. Installation and Setup/16. Import Libraries into Jupyter Notebook.mp4 12MB
  109. 9. Merging, Joining, and Concatenating/1. Intro to the Merging, Joining, and Concatenating Module.mp4 11MB
  110. 12. Input and Output/4. Export DataFrame to CSV File with the .to_csv() Method.mp4 11MB
  111. 12. Input and Output/3. Quick Object Conversions.mp4 11MB
  112. 6. Working with Text Data/6. String Methods on Index and Columns.mp4 11MB
  113. 2. Series/11. The .sort_values() Method.mp4 11MB
  114. 3. DataFrames I/10. Fill in Null Values with the .fillna() Method.mp4 11MB
  115. 11. Panels/3. Panel Attributes.mp4 11MB
  116. 8. GroupBy/5. Grouping by Multiple Columns.mp4 10MB
  117. 7. MultiIndex/5. The sort_index() Method.mp4 10MB
  118. 2. Series/18. Math Methods on Series Objects.mp4 10MB
  119. 8. GroupBy/3. Retrieve A Group with the .get_group() Method.mp4 10MB
  120. 1. Installation and Setup/21. Python Crash Course, Part 5 - Functions.mp4 10MB
  121. 3. DataFrames I/5. Select Two or More Columns from a DataFrame.mp4 10MB
  122. 13. Visualization/5. Pie Charts.mp4 10MB
  123. 2. Series/9. Python Built-In Functions.mp4 10MB
  124. 11. Panels/10. The .swapaxes() Method.mp4 10MB
  125. 10. Working with Dates and Times/4. The pandas DateTimeIndex Object.mp4 10MB
  126. 2. Series/17. The .get() Method on a Series.mp4 10MB
  127. 6. Working with Text Data/5. More String Methods - strip, lstrip, and rstrip.mp4 10MB
  128. 2. Series/12. The inplace Parameter.mp4 9MB
  129. 5. DataFrames III/11. Create Random Sample with the .sample() Method.mp4 9MB
  130. 1. Installation and Setup/12. Intro to the Jupyter Notebook Interface.mp4 9MB
  131. 4. DataFrames II/3. Filter with More than One Condition (AND - &).mp4 9MB
  132. 10. Working with Dates and Times/14. The .truncate() Method.mp4 9MB
  133. 1. Installation and Setup/18. Python Crash Course, Part 2 - Lists.mp4 9MB
  134. 5. DataFrames III/7. Set New Values for a Specific Cell or Row.mp4 9MB
  135. 2. Series/15. Extract Series Values by Index Position.mp4 9MB
  136. 3. DataFrames I/13. Sort a DataFrame with the .sort_values() Method, Part II.mp4 9MB
  137. 11. Panels/6. Convert Panel to a MultiIndex DataFrame (and Vice Versa).mp4 9MB
  138. 2. Series/13. The .sort_index() Method.mp4 9MB
  139. 7. MultiIndex/10. The .unstack() Method, Part 1.mp4 8MB
  140. 3. DataFrames I/8. A Review of the .value_counts() Method.mp4 8MB
  141. 7. MultiIndex/1. Intro to the MultiIndex Module.mp4 8MB
  142. 11. Panels/4. Use Bracket Notation to Extract a DataFrame from a Panel.mp4 8MB
  143. 1. Installation and Setup/14. Code Cell Execution.mp4 8MB
  144. 4. DataFrames II/10. The .unique() and .nunique() Methods.mp4 8MB
  145. 1. Installation and Setup/3. Mac OS - Download the Anaconda Distribution.mp4 8MB
  146. 2. Series/5. Intro to Methods.mp4 8MB
  147. 1. Installation and Setup/20. Python Crash Course, Part 4 - Operators.mp4 8MB
  148. 5. DataFrames III/1. Intro to the DataFrames III Module + Import Dataset.mp4 8MB
  149. 1. Installation and Setup/8. Windows - Download the Anaconda Distribution.mp4 8MB
  150. 12. Input and Output/2. Feed pd.read_csv() Method a URL Argument.mp4 8MB
  151. 13. Visualization/1. Intro to Visualization Module.mp4 7MB
  152. 2. Series/14. Python's in Keyword.mp4 7MB
  153. 1. Installation and Setup/19. Python Crash Course, Part 3 - Dictionaries.mp4 7MB
  154. 9. Merging, Joining, and Concatenating/12. The pd.merge() Method.mp4 7MB
  155. 2. Series/20. The .value_counts() Method.mp4 7MB
  156. 3. DataFrames I/14. Sort DataFrame with the .sort_index() Method.mp4 7MB
  157. 2. Series/8. The .head() and .tail() Methods.mp4 6MB
  158. 1. Installation and Setup/5. Mac OS - Access the Terminal.mp4 6MB
  159. 10. Working with Dates and Times/1. Intro to the Working with Dates and Times Module.mp4 6MB
  160. 9. Merging, Joining, and Concatenating/11. The .join() Method.mp4 6MB
  161. 1. Installation and Setup/15. Popular Keyboard Shortcuts.mp4 6MB
  162. 14. Options and Settings/4. The precision Option.mp4 6MB
  163. 7. MultiIndex/4. The .set_names() Method.mp4 6MB
  164. 12. Input and Output/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4 6MB
  165. 10. Working with Dates and Times/10. Install pandas-datareader Library.mp4 6MB
  166. 2. Series/19. The .idxmax() and .idxmin() Methods.mp4 6MB
  167. 2. Series/3. Create A Series Object from a Python Dictionary.mp4 5MB
  168. 7. MultiIndex/8. The .swaplevel() Method.mp4 5MB
  169. 9. Merging, Joining, and Concatenating/4. The .append() Method on a DataFrame.mp4 5MB
  170. 2. Series/1. Create Jupyter Notebook for the Series Module.mp4 4MB
  171. 14. Options and Settings/1. Introduction to the Options and Settings Module.mp4 3MB
  172. 15. Conclusion/1. Conclusion.mp4 3MB
  173. 12. Input and Output/1. Intro to the Input and Output Module.mp4 3MB
  174. 1. Installation and Setup/1.1 pandas.zip.zip 685KB
  175. 1. Installation and Setup/2.1 CompletedCourseFiles.zip.zip 363KB
  176. 10. Working with Dates and Times/16. More Fun with pd.DateOffset Objects.vtt 19KB
  177. 1. Installation and Setup/1. Introduction to the Course.vtt 17KB
  178. 4. DataFrames II/2. Filter a DataFrame Based on A Condition.vtt 16KB
  179. 10. Working with Dates and Times/15. pd.DateOffset Objects.vtt 16KB
  180. 1. Installation and Setup/10. Windows - Access the Command Prompt and Update Anaconda Libraries.vtt 16KB
  181. 1. Installation and Setup/7. Mac OS - Unpack Course Materials + The Startdown and Shutdown Process.vtt 16KB
  182. 9. Merging, Joining, and Concatenating/7. Outer Joins.vtt 16KB
  183. 1. Installation and Setup/6. Mac OS - Update Anaconda Libraries.vtt 16KB
  184. 4. DataFrames II/1. This Module's Dataset + Memory Optimization.vtt 15KB
  185. 10. Working with Dates and Times/6. Create Range of Dates with the pd.date_range() Method, Part 1.vtt 15KB
  186. 7. MultiIndex/14. The .pivot_table() Method.vtt 14KB
  187. 2. Series/2. Create A Series Object from a Python List.vtt 14KB
  188. 10. Working with Dates and Times/11. Import Financial Data Set with pandas_datareader Library.vtt 14KB
  189. 2. Series/7. Import Series with the .read_csv() Method.vtt 14KB
  190. 10. Working with Dates and Times/5. The pd.to_datetime() Method.vtt 14KB
  191. 3. DataFrames I/11. The .astype() Method.vtt 14KB
  192. 9. Merging, Joining, and Concatenating/10. Merging by Indexes with the left_index and right_index Parameters.vtt 14KB
  193. 1. Installation and Setup/11. Windows - Unpack Course Materials + The Startdown and Shutdown Process.vtt 13KB
  194. 13. Visualization/2. The .plot() Method.vtt 13KB
  195. 12. Input and Output/6. Import Excel File into pandas.vtt 13KB
  196. 2. Series/6. Parameters and Arguments.vtt 13KB
  197. 9. Merging, Joining, and Concatenating/5. Inner Joins, Part 1.vtt 13KB
  198. 5. DataFrames III/8. Set Multiple Values in DataFrame.vtt 13KB
  199. 12. Input and Output/7. Export Excel File.vtt 13KB
  200. 10. Working with Dates and Times/18. Timedeltas in a Dataset.vtt 13KB
  201. 5. DataFrames III/3. Retrieve Rows by Index Label with .loc[].vtt 13KB
  202. 8. GroupBy/2. First Operations with groupby Object.vtt 12KB
  203. 4. DataFrames II/8. The .duplicated() Method.vtt 12KB
  204. 9. Merging, Joining, and Concatenating/8. Left Joins.vtt 12KB
  205. 3. DataFrames I/7. Broadcasting Operations.vtt 12KB
  206. 5. DataFrames III/5. The Catch-All .ix[] Method.vtt 12KB
  207. 9. Merging, Joining, and Concatenating/6. Inner Joins, Part 2.vtt 12KB
  208. 9. Merging, Joining, and Concatenating/9. The left_on and right_on Parameters.vtt 12KB
  209. 10. Working with Dates and Times/2. Review of Python's datetime Module.vtt 12KB
  210. 7. MultiIndex/2. Create a MultiIndex with the set_index() Method.vtt 11KB
  211. 7. MultiIndex/3. The .get_level_values() Method.vtt 11KB
  212. 8. GroupBy/4. Methods on the Groupby Object and DataFrame Columns.vtt 11KB
  213. 8. GroupBy/7. Iterating through Groups.vtt 11KB
  214. 10. Working with Dates and Times/7. Create Range of Dates with the pd.date_range() Method, Part 2.vtt 11KB
  215. 5. DataFrames III/14. The .query() Method.vtt 11KB
  216. 6. Working with Text Data/7. Split Strings by Characters with .str.split() Method.vtt 11KB
  217. 4. DataFrames II/9. The .drop_duplicates() Method.vtt 11KB
  218. 8. GroupBy/1. Intro to the Groupby Module.vtt 11KB
  219. 1. Installation and Setup/16. Import Libraries into Jupyter Notebook.vtt 11KB
  220. 11. Panels/2. The Axes of a Panel Object.vtt 11KB
  221. 10. Working with Dates and Times/17. The pandas Timedelta Object.vtt 11KB
  222. 4. DataFrames II/4. Filter with More than One Condition (OR - ).vtt 11KB
  223. 3. DataFrames I/4. Select One Column from a DataFrame.vtt 11KB
  224. 11. Panels/1. Intro to the Module + Fetch Panel Dataset from Google Finance.vtt 11KB
  225. 6. Working with Text Data/3. The .str.replace() Method.vtt 11KB
  226. 3. DataFrames I/1. Intro to DataFrames I Module.vtt 10KB
  227. 11. Panels/9. Transpose a Panel with the .transpose() Method.vtt 10KB
  228. 7. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.vtt 10KB
  229. 14. Options and Settings/2. Changing pandas Options with Attributes and Dot Syntax.vtt 10KB
  230. 3. DataFrames I/6. Add New Column to DataFrame.vtt 10KB
  231. 3. DataFrames I/2. Shared Methods and Attributes between Series and DataFrames.vtt 10KB
  232. 1. Installation and Setup/13. Cell Types and Cell Modes.vtt 10KB
  233. 1. Installation and Setup/17. Python Crash Course, Part 1 - Data Types and Variables.vtt 10KB
  234. 10. Working with Dates and Times/12. Selecting Rows from a DataFrame with a DateTimeIndex.vtt 10KB
  235. 2. Series/4. Intro to Attributes.vtt 10KB
  236. 7. MultiIndex/13. The .pivot() Method.vtt 10KB
  237. 2. Series/16. Extract Series Values by Index Label.vtt 9KB
  238. 10. Working with Dates and Times/13. Timestamp Object Attributes.vtt 9KB
  239. 5. DataFrames III/10. Delete Rows or Columns from a DataFrame.vtt 9KB
  240. 10. Working with Dates and Times/9. The .dt Accessor.vtt 9KB
  241. 10. Working with Dates and Times/8. Create Range of Dates with the pd.date_range() Method, Part 3.vtt 9KB
  242. 6. Working with Text Data/2. Common String Methods - lower, upper, title, and len.vtt 9KB
  243. 13. Visualization/4. Bar Graphs.vtt 9KB
  244. 6. Working with Text Data/9. The expand and n Parameters of the .str.split() Method.vtt 9KB
  245. 4. DataFrames II/7. The .between() Method.vtt 9KB
  246. 11. Panels/5. Extracting with the .loc, .iloc, and .ix Methods.vtt 9KB
  247. 10. Working with Dates and Times/3. The pandas Timestamp Object.vtt 9KB
  248. 14. Options and Settings/3. Changing pandas Options with Methods.vtt 9KB
  249. 6. Working with Text Data/4. Filtering with String Methods.vtt 9KB
  250. 3. DataFrames I/3. Differences between Shared Methods.vtt 9KB
  251. 9. Merging, Joining, and Concatenating/3. The pd.concat() Method, Part 2.vtt 9KB
  252. 5. DataFrames III/17. The .copy() Method.vtt 9KB
  253. 2. Series/21. The .apply() Method.vtt 9KB
  254. 5. DataFrames III/16. The .apply() Method with Row Values.vtt 9KB
  255. 1. Installation and Setup/21. Python Crash Course, Part 5 - Functions.vtt 8KB
  256. 5. DataFrames III/9. Rename Index Labels or Columns in a DataFrame.vtt 8KB
  257. 7. MultiIndex/9. The .stack() Method.vtt 8KB
  258. 11. Panels/8. The .minor_xs() Method.vtt 8KB
  259. 13. Visualization/6. Histograms.vtt 8KB
  260. 4. DataFrames II/5. The .isin() Method.vtt 8KB
  261. 3. DataFrames I/9. Drop Rows with Null Values.vtt 8KB
  262. 2. Series/22. The .map() Method.vtt 8KB
  263. 7. MultiIndex/11. The .unstack() Method, Part 2.vtt 8KB
  264. 12. Input and Output/4. Export DataFrame to CSV File with the .to_csv() Method.vtt 8KB
  265. 6. Working with Text Data/1. Intro to the Working with Text Data Module.vtt 8KB
  266. 2. Series/11. The .sort_values() Method.vtt 8KB
  267. 7. MultiIndex/15. The pd.melt() Method.vtt 8KB
  268. 9. Merging, Joining, and Concatenating/1. Intro to the Merging, Joining, and Concatenating Module.vtt 8KB
  269. 8. GroupBy/6. The .agg() Method.vtt 8KB
  270. 2. Series/10. More Series Attributes.vtt 8KB
  271. 1. Installation and Setup/4. Mac OS - Install Anaconda Distribution.vtt 8KB
  272. 5. DataFrames III/6. Second Arguments to .loc[], .iloc[], and .ix[] Methods.vtt 8KB
  273. 9. Merging, Joining, and Concatenating/2. The pd.concat() Method, Part 1.vtt 8KB
  274. 5. DataFrames III/4. Retrieve Rows by Index Position with .iloc[].vtt 8KB
  275. 3. DataFrames I/15. Rank Values with the .rank() Method.vtt 8KB
  276. 6. Working with Text Data/8. More Practice with Splits.vtt 8KB
  277. 1. Installation and Setup/12. Intro to the Jupyter Notebook Interface.vtt 7KB
  278. 11. Panels/7. The .major_xs() Method.vtt 7KB
  279. 13. Visualization/3. Modifying Aesthetics with Templates.vtt 7KB
  280. 3. DataFrames I/5. Select Two or More Columns from a DataFrame.vtt 7KB
  281. 3. DataFrames I/12. Sort a DataFrame with the .sort_values() Method, Part I.vtt 7KB
  282. 13. Visualization/5. Pie Charts.vtt 7KB
  283. 2. Series/12. The inplace Parameter.vtt 7KB
  284. 7. MultiIndex/5. The sort_index() Method.vtt 7KB
  285. 5. DataFrames III/15. A Review of the .apply() Method on Single Columns.vtt 7KB
  286. 4. DataFrames II/6. The .isnull() and .notnull() Methods.vtt 7KB
  287. 7. MultiIndex/7. The .transpose() Method and MultiIndex on Column Level.vtt 7KB
  288. 7. MultiIndex/12. The .unstack() Method, Part 3.vtt 7KB
  289. 2. Series/18. Math Methods on Series Objects.vtt 7KB
  290. 1. Installation and Setup/14. Code Cell Execution.vtt 7KB
  291. 12. Input and Output/3. Quick Object Conversions.vtt 7KB
  292. 1. Installation and Setup/18. Python Crash Course, Part 2 - Lists.vtt 7KB
  293. 6. Working with Text Data/6. String Methods on Index and Columns.vtt 7KB
  294. 11. Panels/3. Panel Attributes.vtt 7KB
  295. 5. DataFrames III/12. The .nsmallest() and .nlargest() Methods.vtt 7KB
  296. 2. Series/9. Python Built-In Functions.vtt 7KB
  297. 2. Series/5. Intro to Methods.vtt 6KB
  298. 5. DataFrames III/2. The .set_index() and .reset_index() Methods.vtt 6KB
  299. 5. DataFrames III/13. Filtering with the .where() Method.vtt 6KB
  300. 10. Working with Dates and Times/4. The pandas DateTimeIndex Object.vtt 6KB
  301. 2. Series/17. The .get() Method on a Series.vtt 6KB
  302. 13. Visualization/1. Intro to Visualization Module.vtt 6KB
  303. 7. MultiIndex/1. Intro to the MultiIndex Module.vtt 6KB
  304. 3. DataFrames I/10. Fill in Null Values with the .fillna() Method.vtt 6KB
  305. 5. DataFrames III/11. Create Random Sample with the .sample() Method.vtt 6KB
  306. 1. Installation and Setup/20. Python Crash Course, Part 4 - Operators.vtt 6KB
  307. 2. Series/13. The .sort_index() Method.vtt 6KB
  308. 8. GroupBy/5. Grouping by Multiple Columns.vtt 6KB
  309. 4. DataFrames II/3. Filter with More than One Condition (AND - &).vtt 6KB
  310. 4. DataFrames II/10. The .unique() and .nunique() Methods.vtt 6KB
  311. 11. Panels/4. Use Bracket Notation to Extract a DataFrame from a Panel.vtt 6KB
  312. 1. Installation and Setup/19. Python Crash Course, Part 3 - Dictionaries.vtt 6KB
  313. 11. Panels/10. The .swapaxes() Method.vtt 6KB
  314. 6. Working with Text Data/5. More String Methods - strip, lstrip, and rstrip.vtt 6KB
  315. 3. DataFrames I/13. Sort a DataFrame with the .sort_values() Method, Part II.vtt 5KB
  316. 1. Installation and Setup/9. Windows - Install Anaconda Distribution.vtt 5KB
  317. 10. Working with Dates and Times/1. Intro to the Working with Dates and Times Module.vtt 5KB
  318. 1. Installation and Setup/8. Windows - Download the Anaconda Distribution.vtt 5KB
  319. 12. Input and Output/2. Feed pd.read_csv() Method a URL Argument.vtt 5KB
  320. 11. Panels/6. Convert Panel to a MultiIndex DataFrame (and Vice Versa).vtt 5KB
  321. 2. Series/15. Extract Series Values by Index Position.vtt 5KB
  322. 5. DataFrames III/7. Set New Values for a Specific Cell or Row.vtt 5KB
  323. 3. DataFrames I/8. A Review of the .value_counts() Method.vtt 5KB
  324. 7. MultiIndex/10. The .unstack() Method, Part 1.vtt 5KB
  325. 2. Series/14. Python's in Keyword.vtt 5KB
  326. 8. GroupBy/3. Retrieve A Group with the .get_group() Method.vtt 5KB
  327. 2. Series/8. The .head() and .tail() Methods.vtt 5KB
  328. 5. DataFrames III/1. Intro to the DataFrames III Module + Import Dataset.vtt 5KB
  329. 2. Series/20. The .value_counts() Method.vtt 5KB
  330. 1. Installation and Setup/3. Mac OS - Download the Anaconda Distribution.vtt 5KB
  331. 1. Installation and Setup/15. Popular Keyboard Shortcuts.vtt 5KB
  332. 14. Options and Settings/4. The precision Option.vtt 4KB
  333. 7. MultiIndex/4. The .set_names() Method.vtt 4KB
  334. 9. Merging, Joining, and Concatenating/12. The pd.merge() Method.vtt 4KB
  335. 9. Merging, Joining, and Concatenating/11. The .join() Method.vtt 4KB
  336. 2. Series/19. The .idxmax() and .idxmin() Methods.vtt 4KB
  337. 2. Series/3. Create A Series Object from a Python Dictionary.vtt 4KB
  338. 10. Working with Dates and Times/14. The .truncate() Method.vtt 4KB
  339. 3. DataFrames I/14. Sort DataFrame with the .sort_index() Method.vtt 4KB
  340. 12. Input and Output/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.vtt 3KB
  341. 10. Working with Dates and Times/10. Install pandas-datareader Library.vtt 3KB
  342. 7. MultiIndex/8. The .swaplevel() Method.vtt 3KB
  343. 2. Series/1. Create Jupyter Notebook for the Series Module.vtt 3KB
  344. 9. Merging, Joining, and Concatenating/4. The .append() Method on a DataFrame.vtt 3KB
  345. 1. Installation and Setup/5. Mac OS - Access the Terminal.vtt 3KB
  346. 15. Conclusion/1. Conclusion.vtt 2KB
  347. 14. Options and Settings/1. Introduction to the Options and Settings Module.vtt 2KB
  348. 12. Input and Output/1. Intro to the Input and Output Module.vtt 2KB
  349. 1. Installation and Setup/2. Completed Course Files.html 782B
  350. 4. DataFrames II/9.1 Official documentation for the DataFrame.drop_duplicates method.html 157B
  351. 4. DataFrames II/8.1 Official documentation for the DataFrame.duplicated method.html 152B
  352. 5. DataFrames III/2.2 reset_index Documentation.html 149B
  353. 3. DataFrames I/12.1 Official pandas Documentation.html 148B
  354. 3. DataFrames I/13.1 Official pandas Documentation.html 148B
  355. 2. Series/20.1 Official Documentation for the Series.value_counts Method.html 147B
  356. 3. DataFrames I/14.1 Official pandas Documentation.html 147B
  357. 5. DataFrames III/2.1 set_index Documentation.html 147B
  358. 2. Series/11.1 Official pandas Documentation.html 145B
  359. 2. Series/13.1 Official pandas Documentation.html 144B
  360. 3. DataFrames I/10.1 Official pandas Documentation.html 143B
  361. 3. DataFrames I/11.1 Official pandas Documentation.html 143B
  362. 3. DataFrames I/15.1 Official pandas Documentation.html 141B
  363. 5. DataFrames III/3.1 loc[] Documentation.html 141B
  364. 2. Series/8.1 Official pandas Documentation.html 138B
  365. 11. Panels/11. A Review of the Panels Module.html 135B
  366. 12. Input and Output/8. Input and Output.html 135B
  367. 13. Visualization/7. Visualization.html 135B
  368. 2. Series/23. A Review of the Series Module.html 135B
  369. [Tutorialsplanet.NET].url 128B