Python Bootcamp for Data Science 2021 Numpy Pandas Seaborn

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Python Bootcamp for Data Science 2021 Numpy Pandas Seaborn
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tutsnode
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Files
  1. 5. Housing Dataset Analysis -Part Five.mp440.0 MB
  2. TutsNode.com.txt63 bytes
  3. 2. List.srt9.2 KB
  4. 5. Housing Dataset Analysis -Part Five.srt8.7 KB
  5. [TGx]Downloaded from torrentgalaxy.to .txt585 bytes
  6. 5. Short Quiz.html213 bytes
  7. 0179 bytes
  8. 2. How to Download Course Notebooks.mp438.1 MB
  9. 2.1 How to download course notebooks.pdf140.2 KB
  10. 1. Merging Datasets on Keys (common columns).srt8.2 KB
  11. 2. Dataframe in Pandas.srt7.7 KB
  12. 7. Adding Annotations and Drawings on a Plot.srt7.6 KB
  13. 2. Creating Ndarrays.srt7.4 KB
  14. 3. Basics of Time Series.srt7.4 KB
  15. 3. Concatenating Along an Axis.srt7.2 KB
  16. 2. Tour In Basics of Jupyter Notebooks.srt7.0 KB
  17. 8. Rolling and Moving Windows.srt6.7 KB
  18. 2. Creating Figures and Subplots.srt6.7 KB
  19. 10. Mathematical and Statistical Methods.srt6.6 KB
  20. 5. Shifting Data Through Time (Lagging and Leading).srt6.6 KB
  21. 1. Hierarchical Indexing.srt6.5 KB
  22. 3. Reshaping by Pivoting (Long to Wide).srt6.4 KB
  23. 14. Factor Plots for Categorical Data.srt6.4 KB
  24. 4. Housing Dataset Analysis -Part Four.srt6.2 KB
  25. 2. How to Download Course Notebooks.srt6.2 KB
  26. 1. Creating and Calling Functions.srt6.2 KB
  27. 6. Indexing, Slicing and Filtering.srt6.1 KB
  28. 7. Boolean Indexing.srt6.1 KB
  29. 1. Running Jupyter Notebook.srt5.9 KB
  30. 3. Overview of Course Curriculum.srt5.9 KB
  31. 1. Series in Pandas.srt5.9 KB
  32. 2. Reshaping by Melting (Wide to Long ).srt5.9 KB
  33. 4. Set.srt2.3 KB
  34. 1. Reading Data in Text Format-Part1.srt5.8 KB
  35. 6. Handling Time Zone.srt5.7 KB
  36. 11. Bar Plots with Seaborn.srt5.6 KB
  37. 1. Reshaping by Stacking and Unstacking.srt5.6 KB
  38. 2. Returning Multiple Values.srt2.3 KB
  39. 7. Resampling and Frequency Conversion.srt5.5 KB
  40. 13. Scatter Plots and Pair Plots.srt5.4 KB
  41. 4. Short Quiz.html213 bytes
  42. 2. Converting Between String and Datetime.srt5.3 KB
  43. 1. What Is NumPy Arrays (Ndarrays).srt2.9 KB
  44. 3. Cloud Environment Google Colab Jupyter Notebooks.srt5.3 KB
  45. 12. Histograms and Density Plots.srt5.1 KB
  46. 7. Arithmetic with Dataframe.srt5.0 KB
  47. 1. Tuple.srt5.0 KB
  48. 4. Indexing with Columns in Dataframe.srt5.0 KB
  49. 6. Adding Texts and Arrows on a Plot.srt4.9 KB
  50. 3. Data Types for Ndarrays.srt4.9 KB
  51. 4. Customizing Ticks and Labels.srt4.9 KB
  52. 7. Filtering Outliers.srt4.9 KB
  53. 10. String Object Methods.srt4.8 KB
  54. 9. Line Plots with Dataframe.srt4.8 KB
  55. 6. Indexing and Slicing-Part two.srt4.7 KB
  56. 9. Descriptive Statistics with Dataframe.srt4.7 KB
  57. 4. Generating Date Ranges.srt4.6 KB
  58. 1. Course Introduction.srt4.5 KB
  59. 9. Transposing Arrays.srt2.0 KB
  60. 3. Housing Dataset Analysis -Part Three.srt4.5 KB
  61. 13. Short Quiz.html213 bytes
  62. 150 bytes
  63. 1. Merging Datasets on Keys (common columns).mp436.9 MB
  64. 4. Getting Help in Jupyter Notebook.srt4.5 KB
  65. 3. Filling in Missing Data.srt4.5 KB
  66. 1. Date and time Data types.srt4.5 KB
  67. 5. Adding Legends.srt4.4 KB
  68. 8. Sorting Series and Dataframe.srt4.4 KB
  69. 2. Filtering out Missing Data.srt4.3 KB
  70. 2. Reading Data in Text Format-Part2.srt4.3 KB
  71. 8. Fancy Indexing.srt4.3 KB
  72. 3. Writing Data in Text Format.srt4.2 KB
  73. 10. Bar Plots with Dataframes.srt4.2 KB
  74. 4. Reindexing in Series and DataFrames.srt3.0 KB
  75. 1. Housing Dataset Analysis -Part One.srt4.2 KB
  76. 2. Housing Dataset Analysis -Part Two.srt4.2 KB
  77. 5. Magic Commands.srt4.2 KB
  78. 1. Decide Which Python Environment to Use.srt4.2 KB
  79. 2. Local environment Installing Anaconda.srt4.2 KB
  80. 5. Indexing and Slicing-Part One.srt4.2 KB
  81. 3. Summary Statistics by Level.srt4.1 KB
  82. 8. Shuffling and Random Sampling.srt4.1 KB
  83. 10. Correlation and Covariance.srt4.1 KB
  84. 3. Cell Types in Jupyter Notebook.srt4.1 KB
  85. 3. Changing Colors, Markers and Linestyle.srt4.0 KB
  86. 3. Index Objects.srt4.0 KB
  87. 11. Short Quiz.html213 bytes
  88. 9. Dummy Variables.srt3.9 KB
  89. 8. Saving Plots to a File.srt3.9 KB
  90. 3. Lambda Functions.srt3.8 KB
  91. 5. Replacing Values.srt3.5 KB
  92. 11. Sorting Arrays.srt3.5 KB
  93. 5. Short Quiz.html213 bytes
  94. 11. Short Quiz.html213 bytes
  95. 4. Reading Microsoft Excel Files.srt2.4 KB
  96. 1. Handling Missing Data.srt3.4 KB
  97. 3. Dictionary.srt3.3 KB
  98. 5. Deleting Rows and Columns.srt3.2 KB
  99. 12. File Input and Output with Arrays.srt3.2 KB
  100. 1. Introducing Matplotlib Library.srt3.2 KB
  101. 4. Arithmetic with NumPy Arrays.srt3.1 KB
  102. 2. Merging Datasets on Index.srt3.1 KB
  103. 2. Reordering and Sorting Index Levels.srt3.0 KB
  104. 4. Removing Duplicate Entries.srt2.7 KB
  105. 6. Renaming columns and Index Labels.srt2.8 KB
  106. 5. Short Quiz.html213 bytes
  107. 4. Short Quiz.html213 bytes
  108. 4. Short Quiz.html213 bytes
  109. 15. Short Quiz.html213 bytes
  110. 9. Short Quiz.html213 bytes
  111. 2478.1 KB
  112. 2. List.mp436.4 MB
  113. 3133.6 KB
  114. 13. Scatter Plots and Pair Plots.mp435.8 MB
  115. 4225.7 KB
  116. 10. Mathematical and Statistical Methods.mp435.4 MB
  117. 5113.0 KB
  118. 2. Dataframe in Pandas.mp434.0 MB
  119. 642.1 KB
  120. 6. Handling Time Zone.mp433.5 MB
  121. 741.1 KB
  122. 5. Shifting Data Through Time (Lagging and Leading).mp433.2 MB
  123. 8332.8 KB
  124. 3. Basics of Time Series.mp432.8 MB
  125. 9216.1 KB
  126. 4. Housing Dataset Analysis -Part Four.mp431.9 MB
  127. 1052.6 KB
  128. 7. Adding Annotations and Drawings on a Plot.mp431.5 MB
  129. 11489.3 KB
  130. 2. Creating Figures and Subplots.mp431.2 MB
  131. 12280.2 KB
  132. 1. Hierarchical Indexing.mp431.2 MB
  133. 13284.1 KB
  134. 2. Creating Ndarrays.mp431.2 MB
  135. 14284.2 KB
  136. 3. Concatenating Along an Axis.mp430.1 MB
  137. 15403.6 KB
  138. 8. Rolling and Moving Windows.mp429.8 MB
  139. 16234.8 KB
  140. 3. Housing Dataset Analysis -Part Three.mp429.7 MB
  141. 17277.7 KB
  142. 4. Generating Date Ranges.mp429.5 MB
  143. 1837.6 KB
  144. 3. Reshaping by Pivoting (Long to Wide).mp428.9 MB
  145. 1983.1 KB
  146. 1. Running Jupyter Notebook.mp428.8 MB
  147. 20243.3 KB
  148. 4. Customizing Ticks and Labels.mp428.6 MB
  149. 21420.8 KB
  150. 7. Boolean Indexing.mp428.2 MB
  151. 22347.3 KB
  152. 12. Histograms and Density Plots.mp427.8 MB
  153. 23221.5 KB
  154. 14. Factor Plots for Categorical Data.mp427.3 MB
  155. 24182.6 KB
  156. 3. Overview of Course Curriculum.mp427.1 MB
  157. 25412.9 KB
  158. 2. Tour In Basics of Jupyter Notebooks.mp426.9 MB
  159. 26131.2 KB
  160. 9. Line Plots with Dataframe.mp426.7 MB
  161. 27286.8 KB
  162. 1. Reshaping by Stacking and Unstacking.mp426.5 MB
  163. 2826.7 KB
  164. 2. Converting Between String and Datetime.mp425.9 MB
  165. 29144.8 KB
  166. 11. Bar Plots with Seaborn.mp425.7 MB
  167. 30322.3 KB
  168. 6. Indexing, Slicing and Filtering.mp425.3 MB
  169. 31172.9 KB
  170. 1. Series in Pandas.mp424.6 MB
  171. 32397.3 KB
  172. 5. Adding Legends.mp424.6 MB
  173. 33399.5 KB
  174. 1. Creating and Calling Functions.mp423.7 MB
  175. 34262.7 KB
  176. 6. Adding Texts and Arrows on a Plot.mp423.4 MB
  177. 3556.4 KB
  178. 5. Magic Commands.mp423.4 MB
  179. 36126.4 KB
  180. 2. Housing Dataset Analysis -Part Two.mp423.3 MB
  181. 37217.4 KB
  182. 7. Resampling and Frequency Conversion.mp423.1 MB
  183. 38415.7 KB
  184. 4. Indexing with Columns in Dataframe.mp423.1 MB
  185. 39420.0 KB
  186. 7. Filtering Outliers.mp422.4 MB
  187. 4059.8 KB
  188. 1. Reading Data in Text Format-Part1.mp422.3 MB
  189. 41165.0 KB
  190. 7. Arithmetic with Dataframe.mp422.1 MB
  191. 42371.1 KB
  192. 3. Changing Colors, Markers and Linestyle.mp421.9 MB
  193. 4363.8 KB
  194. 3. Writing Data in Text Format.mp421.9 MB
  195. 44123.9 KB
  196. 2. Reading Data in Text Format-Part2.mp421.6 MB
  197. 45359.0 KB
  198. 3. Filling in Missing Data.mp421.3 MB
  199. 46227.9 KB
  200. 11. Sorting Arrays.mp421.2 MB
  201. 47301.2 KB
  202. 8. Shuffling and Random Sampling.mp420.9 MB
  203. 48104.4 KB
  204. 10. String Object Methods.mp420.7 MB
  205. 49325.6 KB
  206. 3. Data Types for Ndarrays.mp420.6 MB
  207. 50390.6 KB
  208. 10. Bar Plots with Dataframes.mp420.6 MB
  209. 51415.4 KB
  210. 9. Descriptive Statistics with Dataframe.mp420.3 MB
  211. 52183.3 KB
  212. 2. Filtering out Missing Data.mp420.3 MB
  213. 53228.2 KB
  214. 8. Sorting Series and Dataframe.mp420.3 MB
  215. 54237.7 KB
  216. 1. Date and time Data types.mp420.2 MB
  217. 55259.7 KB
  218. 3. Cloud Environment Google Colab Jupyter Notebooks.mp420.2 MB
  219. 56352.8 KB
  220. 1. Tuple.mp419.8 MB
  221. 57170.9 KB
  222. 6. Indexing and Slicing-Part two.mp419.8 MB
  223. 58182.5 KB
  224. 3. Index Objects.mp418.8 MB
  225. 59221.5 KB
  226. 10. Correlation and Covariance.mp418.7 MB
  227. 60260.2 KB
  228. 8. Saving Plots to a File.mp418.1 MB
  229. 61359.3 KB
  230. 8. Fancy Indexing.mp418.0 MB
  231. 6211.0 KB
  232. 5. Indexing and Slicing-Part One.mp417.8 MB
  233. 63168.8 KB
  234. 3. Summary Statistics by Level.mp417.3 MB
  235. 64252.0 KB
  236. 9. Dummy Variables.mp415.7 MB
  237. 65266.3 KB
  238. 12. File Input and Output with Arrays.mp415.6 MB
  239. 66364.3 KB
  240. 4. Getting Help in Jupyter Notebook.mp415.6 MB
  241. 67453.5 KB
  242. 3. Lambda Functions.mp415.3 MB
  243. 68229.2 KB
  244. 3. Cell Types in Jupyter Notebook.mp415.1 MB
  245. 69439.2 KB
  246. 2. Merging Datasets on Index.mp415.0 MB
  247. 70494.8 KB
  248. 3. Dictionary.mp414.8 MB
  249. 71210.3 KB
  250. 2. Reordering and Sorting Index Levels.mp414.3 MB
  251. 72228.4 KB
  252. 1. Course Introduction.mp413.9 MB
  253. 7399.5 KB
  254. 5. Replacing Values.mp413.5 MB
  255. 74494.0 KB
  256. 4. Reindexing in Series and DataFrames.mp413.4 MB
  257. 75100.3 KB
  258. 1. Handling Missing Data.mp413.2 MB
  259. 76294.0 KB
  260. 4. Arithmetic with NumPy Arrays.mp412.9 MB
  261. 77125.2 KB
  262. 4. Removing Duplicate Entries.mp412.7 MB
  263. 78336.9 KB
  264. 4. Reading Microsoft Excel Files.mp412.2 MB
  265. 79330.3 KB
  266. 1. Decide Which Python Environment to Use.mp412.0 MB
  267. 8017.1 KB
  268. 1. What Is NumPy Arrays (Ndarrays).mp411.5 MB
  269. 81470.3 KB
  270. 1. Introducing Matplotlib Library.mp411.5 MB
  271. 8222.8 KB
  272. 6. Renaming columns and Index Labels.mp411.2 MB
  273. 83315.6 KB
  274. 1. Housing Dataset Analysis -Part One.mp410.8 MB
  275. 84239.1 KB
  276. 2. Local environment Installing Anaconda.mp410.4 MB
  277. 8556.9 KB
  278. 2. Reshaping by Melting (Wide to Long ).mp49.5 MB
  279. 8627.8 KB
  280. 2. Returning Multiple Values.mp49.4 MB
  281. 87130.7 KB
  282. 9. Transposing Arrays.mp48.9 MB
  283. 8868.7 KB
  284. 5. Deleting Rows and Columns.mp45.4 MB
  285. 8998.1 KB
  286. 4. Set.mp44.5 MB

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