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[] Udemy - Data Analysis with Pandas and Python

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文件列表

  1. 1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.mp4 112MB
  2. 1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.mp4 112MB
  3. 1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.mp4 111MB
  4. 5. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.mp4 98MB
  5. 1. Installation and Setup/5. MacOS - Install Anaconda Distribution.mp4 91MB
  6. 2. BONUS Python Crash Course/8. String Methods.mp4 75MB
  7. 11. Working with Dates and Times in Datasets/15. Timeseries Offsets.mp4 75MB
  8. 11. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4 74MB
  9. 1. Installation and Setup/6. MacOS - Access the Terminal Application.mp4 73MB
  10. 4. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.mp4 68MB
  11. 6. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.mp4 61MB
  12. 3. Series/8. Create Series from Dataset with the pd.read_csv Method.mp4 60MB
  13. 6. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.mp4 58MB
  14. 2. BONUS Python Crash Course/7. Custom Functions.mp4 56MB
  15. 2. BONUS Python Crash Course/10. Index Positions and Slicing.mp4 56MB
  16. 11. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.mp4 54MB
  17. 2. BONUS Python Crash Course/11. Dictionaries.mp4 54MB
  18. 2. BONUS Python Crash Course/4. Operators.mp4 51MB
  19. 4. DataFrames I Introduction/1. Intro to DataFrames I Module.mp4 50MB
  20. 12. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.mp4 49MB
  21. 1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp4 47MB
  22. 8. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp4 47MB
  23. 12. Input and Output in pandas/7. Export Excel File with the to_excel Method.mp4 47MB
  24. 3. Series/19. Extract Series Values by Index Label.mp4 46MB
  25. 6. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.mp4 46MB
  26. 8. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.mp4 46MB
  27. 2. BONUS Python Crash Course/9. Lists.mp4 45MB
  28. 11. Working with Dates and Times in Datasets/14. The pd.DateOffset Object.mp4 44MB
  29. 12. Input and Output in pandas/3. Quick Object Conversions.mp4 44MB
  30. 11. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.mp4 42MB
  31. 3. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.mp4 41MB
  32. 12. Input and Output in pandas/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4 40MB
  33. 6. DataFrames III Data Extraction/4. Retrieve Rows by Index Position with iloc Accessor.mp4 40MB
  34. 6. DataFrames III Data Extraction/2. Use the set_index and reset_index methods to define a new DataFrame index.mp4 39MB
  35. 1. Installation and Setup/10. Windows - Install Anaconda Distribution.mp4 39MB
  36. 6. DataFrames III Data Extraction/7. Set Multiple Values in a DataFrame.mp4 39MB
  37. 8. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.mp4 36MB
  38. 8. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.mp4 35MB
  39. 1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.mp4 34MB
  40. 13. Visualization/2. Use the plot Method to Render a Line Chart.mp4 33MB
  41. 1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.mp4 33MB
  42. 11. Working with Dates and Times in Datasets/10. Install pandas-datareader Library.mp4 33MB
  43. 2. BONUS Python Crash Course/6. Built-in Functions.mp4 33MB
  44. 2. BONUS Python Crash Course/3. Basic Data Types.mp4 32MB
  45. 7. Working with Text Data/1. Intro to the Working with Text Data Section.mp4 32MB
  46. 11. Working with Dates and Times in Datasets/16. The Timedelta Object.mp4 32MB
  47. 10. Merging, Joining, and Concatenating DataFrames/3. The pd.concat Method, Part 2.mp4 31MB
  48. 5. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.mp4 27MB
  49. 13. Visualization/4. Creating Bar Graphs to Show Counts.mp4 27MB
  50. 12. Input and Output in pandas/4. Export CSV File with the to_csv Method.mp4 27MB
  51. 10. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.mp4 26MB
  52. 1. Installation and Setup/17. Import Libraries into Jupyter Notebook.mp4 26MB
  53. 2. BONUS Python Crash Course/5. Variables.mp4 24MB
  54. 13. Visualization/3. Modifying Plot Aesthetics with matplotlib Templates.mp4 24MB
  55. 4. DataFrames I Introduction/14. Convert DataFrame Column Types with the astype Method.mp4 24MB
  56. 6. DataFrames III Data Extraction/1. Intro to the DataFrames III Module + Import Dataset.mp4 23MB
  57. 9. The GroupBy Object/2. First Operations with groupby Object.mp4 23MB
  58. 11. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.mp4 23MB
  59. 10. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.mp4 23MB
  60. 8. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.mp4 22MB
  61. 10. Merging, Joining, and Concatenating DataFrames/2. The pd.concat Method, Part 1.mp4 22MB
  62. 13. Visualization/5. Creating Pie Charts to Represent Proportions.mp4 21MB
  63. 9. The GroupBy Object/7. Iterating through Groups.mp4 21MB
  64. 1. Installation and Setup/2. About Me.mp4 21MB
  65. 10. Merging, Joining, and Concatenating DataFrames/1. Intro to the Merging, Joining, and Concatenating Section.mp4 21MB
  66. 10. Merging, Joining, and Concatenating DataFrames/7. Left Joins.mp4 21MB
  67. 8. MultiIndex/3. Extract Index Level Values with the get_level_values Method.mp4 21MB
  68. 9. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.mp4 20MB
  69. 10. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.mp4 20MB
  70. 1. Installation and Setup/14. Cell Types and Cell Modes in Jupyter Notebook.mp4 20MB
  71. 8. MultiIndex/1. Intro to the MultiIndex Module.mp4 20MB
  72. 6. DataFrames III Data Extraction/6. Set New Value for a Specific Cell or Cells In a Row.mp4 20MB
  73. 6. DataFrames III Data Extraction/13. Filter A DataFrame with the query method.mp4 20MB
  74. 14. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.mp4 20MB
  75. 12. Input and Output in pandas/2. Pass a URL to the pd.read_csv Method.mp4 20MB
  76. 11. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4 20MB
  77. 5. DataFrames II Filtering Data/8. Check for Duplicate DataFrame Rows with the duplicated Method.mp4 20MB
  78. 11. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.mp4 20MB
  79. 4. DataFrames I Introduction/11. Drop DataFrame Rows with Null Values with the dropna Method.mp4 19MB
  80. 8. MultiIndex/4. Change Index Level Name with the set_names Method.mp4 19MB
  81. 11. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4 19MB
  82. 3. Series/7. Parameters and Arguments.mp4 18MB
  83. 4. DataFrames I Introduction/9. Broadcasting Operations on DataFrames.mp4 18MB
  84. 3. Series/2. Create A Series Object from a Python List.mp4 18MB
  85. 10. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.mp4 18MB
  86. 1. Installation and Setup/9. Windows - Download the Anaconda Distribution.mp4 18MB
  87. 10. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.mp4 18MB
  88. 5. DataFrames II Filtering Data/9. Delete Duplicate DataFrame Rows with the drop_duplicates Method.mp4 18MB
  89. 7. Working with Text Data/7. Split Strings by Characters with the str.split Method.mp4 18MB
  90. 8. MultiIndex/15. Use the pd.melt method to create a narrow dataset from a wide one.mp4 17MB
  91. 4. DataFrames I Introduction/8. Add New Column to DataFrame.mp4 17MB
  92. 1. Installation and Setup/16. Popular Keyboard Shortcuts in Jupyter Notebook.mp4 17MB
  93. 5. DataFrames II Filtering Data/7. Check For Inclusion Within a Range of Values with the between Method.mp4 17MB
  94. 5. DataFrames II Filtering Data/4. Filter DataFrame with More than One Condition (OR - ).mp4 17MB
  95. 11. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.mp4 17MB
  96. 11. Working with Dates and Times in Datasets/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4 16MB
  97. 6. DataFrames III Data Extraction/9. Delete Rows or Columns from a DataFrame.mp4 16MB
  98. 1. Installation and Setup/4. MacOS - Download the Anaconda Distribution, our Python development environment.mp4 16MB
  99. 7. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.mp4 16MB
  100. 13. Visualization/1. Intro to Visualization Section.mp4 16MB
  101. 7. Working with Text Data/4. Filter a DataFrame's Rows with String Methods.mp4 16MB
  102. 6. DataFrames III Data Extraction/16. Create a Copy of a DataFrame with the copy Method.mp4 15MB
  103. 7. Working with Text Data/9. Exploring the expand and n Parameters of the str.split Method.mp4 15MB
  104. 7. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp4 15MB
  105. 4. DataFrames I Introduction/4. Select One Column from a DataFrame.mp4 15MB
  106. 8. MultiIndex/11. The .unstack() Method, Part 2.mp4 15MB
  107. 2. BONUS Python Crash Course/1. Intro to the Python Crash Course.mp4 14MB
  108. 8. MultiIndex/8. The .swaplevel() Method.mp4 14MB
  109. 9. The GroupBy Object/1. Intro to the Groupby Module.mp4 14MB
  110. 11. Working with Dates and Times in Datasets/1. Intro to the Working with Dates and Times Module.mp4 14MB
  111. 14. Options and Settings in pandas/3. Changing pandas Options with Methods.mp4 14MB
  112. 11. Working with Dates and Times in Datasets/9. The .dt Accessor.mp4 14MB
  113. 6. DataFrames III Data Extraction/12. Filter A DataFrame with the where method.mp4 14MB
  114. 6. DataFrames III Data Extraction/15. Apply a Function to every DataFrame Row with the apply Method.mp4 13MB
  115. 4. DataFrames I Introduction/15. Sort a DataFrame with the sort_values Method, Part I.mp4 13MB
  116. 8. MultiIndex/9. The .stack() Method.mp4 13MB
  117. 9. The GroupBy Object/6. The .agg() Method.mp4 13MB
  118. 4. DataFrames I Introduction/19. Rank Series Values with the rank Method.mp4 13MB
  119. 4. DataFrames I Introduction/3. Differences between Shared Methods.mp4 13MB
  120. 3. Series/26. The Series#map Method.mp4 13MB
  121. 3. Series/5. Intro to Attributes on a Series Object.mp4 13MB
  122. 11. Working with Dates and Times in Datasets/3. The pandas Timestamp Object.mp4 13MB
  123. 5. DataFrames II Filtering Data/5. Check for Inclusion with the isin Method.mp4 13MB
  124. 3. Series/25. Use the apply Method to Invoke a Function on Every Series Values.mp4 12MB
  125. 5. DataFrames II Filtering Data/6. Check for Null and Present DataFrame Values with the isnull and notnull Methods.mp4 12MB
  126. 8. MultiIndex/13. The pivot Method.mp4 12MB
  127. 6. DataFrames III Data Extraction/11. Use the nsmallest nlargest methods to get rows with smallest largest values..mp4 12MB
  128. 8. MultiIndex/12. The .unstack() Method, Part 3.mp4 12MB
  129. 7. Working with Text Data/8. More Practice with the str.split method on a Series.mp4 12MB
  130. 6. DataFrames III Data Extraction/14. A Review of the apply Method on a pandas Series Object.mp4 12MB
  131. 3. Series/12. Accessing More Series Attributes.mp4 12MB
  132. 7. Working with Text Data/6. Invoke String Methods on DataFrame Index and Columns.mp4 11MB
  133. 3. Series/13. Use the sort_values method to sort a Series in ascending or descending order.mp4 11MB
  134. 4. DataFrames I Introduction/13. Fill in Null DataFrame Values with the fillna Method.mp4 11MB
  135. 9. The GroupBy Object/5. Grouping by Multiple Columns.mp4 10MB
  136. 3. Series/22. Math Methods on Series Objects.mp4 10MB
  137. 9. The GroupBy Object/3. Retrieve a group from a GroupBy object with the get_group Method.mp4 10MB
  138. 4. DataFrames I Introduction/6. Select Two or More Columns from a DataFrame.mp4 10MB
  139. 3. Series/11. Passing pandas Objects to Python Built-In Functions.mp4 10MB
  140. 11. Working with Dates and Times in Datasets/4. The pandas DateTimeIndex Object.mp4 10MB
  141. 7. Working with Text Data/5. More DataFrame String Methods - strip, lstrip, and rstrip.mp4 10MB
  142. 3. Series/14. Use the inplace Parameter to permanently mutate a pandas data structure.mp4 9MB
  143. 6. DataFrames III Data Extraction/10. Create Random Sample with the sample Method.mp4 9MB
  144. 5. DataFrames II Filtering Data/3. Filter DataFrame with More than One Condition (AND - &).mp4 9MB
  145. 2. BONUS Python Crash Course/2. Comments.mp4 9MB
  146. 3. Series/18. Extract Series Values by Index Positiox.mp4 9MB
  147. 4. DataFrames I Introduction/16. Sort a DataFrame with the sort_values Method, Part II.mp4 9MB
  148. 1. Installation and Setup/15. Code Cell Execution in Jupyter Notebook.mp4 9MB
  149. 3. Series/15. Use the sort_index Method to Sort the Index of a pandas Series object.mp4 9MB
  150. 8. MultiIndex/10. The .unstack() Method, Part 1.mp4 8MB
  151. 4. DataFrames I Introduction/10. A Review of the value_counts Method.mp4 8MB
  152. 5. DataFrames II Filtering Data/10. Identify and Count Unique Values with the unique and nunique Methods.mp4 8MB
  153. 3. Series/6. Intro to Methods on a Series Object.mp4 8MB
  154. 3. Series/17. Use Python's in Keyword to Check for Inclusion in Series values or index.mp4 7MB
  155. 3. Series/1. Create Jupyter Notebook for the Series Module.mp4 7MB
  156. 10. Merging, Joining, and Concatenating DataFrames/11. The pd.merge() Method.mp4 7MB
  157. 3. Series/24. Use the value_counts Method to See Counts of Unique Values within a Series.mp4 7MB
  158. 4. DataFrames I Introduction/18. Sort DataFrame Indexwith the sort_index Method.mp4 7MB
  159. 3. Series/10. Use the head and tail Methods to Return Rows from Beginning and End of Dataset.mp4 6MB
  160. 10. Merging, Joining, and Concatenating DataFrames/10. The .join() Method.mp4 6MB
  161. 14. Options and Settings in pandas/4. The precision Option.mp4 6MB
  162. 3. Series/23. Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value.mp4 6MB
  163. 12. Input and Output in pandas/1. Intro to the Input and Output Section.mp4 6MB
  164. 3. Series/3. Create A Series Object from a Python Dictionary.mp4 5MB
  165. 14. Options and Settings in pandas/1. Introduction to the Options and Settings Module.mp4 3MB
  166. 15. Conclusion/1. Conclusion.mp4 3MB
  167. 1. Installation and Setup/12.1 pandas.zip 686KB
  168. 1. Installation and Setup/1.1 pandas.zip 685KB
  169. 1. Installation and Setup/8.1 pandas.zip 685KB
  170. 1. Installation and Setup/3.1 notebooks.zip 280KB
  171. 2. BONUS Python Crash Course/8. String Methods.srt 32KB
  172. 1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.srt 30KB
  173. 2. BONUS Python Crash Course/7. Custom Functions.srt 26KB
  174. 5. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.srt 25KB
  175. 2. BONUS Python Crash Course/4. Operators.srt 24KB
  176. 2. BONUS Python Crash Course/11. Dictionaries.srt 24KB
  177. 2. BONUS Python Crash Course/10. Index Positions and Slicing.srt 24KB
  178. 3. Series/8. Create Series from Dataset with the pd.read_csv Method.srt 23KB
  179. 1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.srt 21KB
  180. 1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.srt 21KB
  181. 1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.srt 21KB
  182. 4. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.srt 21KB
  183. 2. BONUS Python Crash Course/9. Lists.srt 20KB
  184. 1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.srt 20KB
  185. 6. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.srt 19KB
  186. 11. Working with Dates and Times in Datasets/15. Timeseries Offsets.srt 19KB
  187. 5. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.srt 19KB
  188. 10. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.srt 18KB
  189. 2. BONUS Python Crash Course/6. Built-in Functions.srt 17KB
  190. 2. BONUS Python Crash Course/3. Basic Data Types.srt 17KB
  191. 11. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.srt 17KB
  192. 11. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.srt 17KB
  193. 3. Series/2. Create A Series Object from a Python List.srt 17KB
  194. 8. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.srt 16KB
  195. 8. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.srt 16KB
  196. 11. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.srt 16KB
  197. 4. DataFrames I Introduction/14. Convert DataFrame Column Types with the astype Method.srt 15KB
  198. 10. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.srt 15KB
  199. 3. Series/19. Extract Series Values by Index Label.srt 15KB
  200. 1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.srt 15KB
  201. 11. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.srt 15KB
  202. 4. DataFrames I Introduction/1. Intro to DataFrames I Module.srt 15KB
  203. 3. Series/7. Parameters and Arguments.srt 15KB
  204. 10. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.srt 15KB
  205. 11. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.srt 14KB
  206. 8. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.srt 14KB
  207. 9. The GroupBy Object/2. First Operations with groupby Object.srt 14KB
  208. 12. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.srt 14KB
  209. 5. DataFrames II Filtering Data/8. Check for Duplicate DataFrame Rows with the duplicated Method.srt 14KB
  210. 6. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.srt 14KB
  211. 3. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.srt 14KB
  212. 1. Installation and Setup/6. MacOS - Access the Terminal Application.srt 14KB
  213. 4. DataFrames I Introduction/9. Broadcasting Operations on DataFrames.srt 14KB
  214. 10. Merging, Joining, and Concatenating DataFrames/7. Left Joins.srt 13KB
  215. 10. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.srt 13KB
  216. 10. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.srt 13KB
  217. 11. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.srt 13KB
  218. 13. Visualization/2. Use the plot Method to Render a Line Chart.srt 13KB
  219. 9. The GroupBy Object/7. Iterating through Groups.srt 13KB
  220. 2. BONUS Python Crash Course/5. Variables.srt 13KB
  221. 9. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.srt 13KB
  222. 11. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.srt 13KB
  223. 7. Working with Text Data/7. Split Strings by Characters with the str.split Method.srt 13KB
  224. 6. DataFrames III Data Extraction/13. Filter A DataFrame with the query method.srt 13KB
  225. 1. Installation and Setup/5. MacOS - Install Anaconda Distribution.srt 13KB
  226. 11. Working with Dates and Times in Datasets/16. The Timedelta Object.srt 12KB
  227. 1. Installation and Setup/17. Import Libraries into Jupyter Notebook.srt 12KB
  228. 5. DataFrames II Filtering Data/9. Delete Duplicate DataFrame Rows with the drop_duplicates Method.srt 12KB
  229. 11. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.srt 12KB
  230. 9. The GroupBy Object/1. Intro to the Groupby Module.srt 12KB
  231. 5. DataFrames II Filtering Data/4. Filter DataFrame with More than One Condition (OR - ).srt 12KB
  232. 8. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.srt 12KB
  233. 8. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.srt 12KB
  234. 7. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.srt 12KB
  235. 4. DataFrames I Introduction/4. Select One Column from a DataFrame.srt 12KB
  236. 6. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.srt 12KB
  237. 12. Input and Output in pandas/7. Export Excel File with the to_excel Method.srt 12KB
  238. 4. DataFrames I Introduction/8. Add New Column to DataFrame.srt 12KB
  239. 14. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.srt 12KB
  240. 3. Series/5. Intro to Attributes on a Series Object.srt 11KB
  241. 8. MultiIndex/13. The pivot Method.srt 11KB
  242. 6. DataFrames III Data Extraction/2. Use the set_index and reset_index methods to define a new DataFrame index.srt 11KB
  243. 1. Installation and Setup/14. Cell Types and Cell Modes in Jupyter Notebook.srt 11KB
  244. 6. DataFrames III Data Extraction/9. Delete Rows or Columns from a DataFrame.srt 11KB
  245. 11. Working with Dates and Times in Datasets/9. The .dt Accessor.srt 11KB
  246. 11. Working with Dates and Times in Datasets/8. Create Range of Dates with the pd.date_range() Method, Part 3.srt 11KB
  247. 7. Working with Text Data/2. Common String Methods - lower, upper, title, and len.srt 11KB
  248. 12. Input and Output in pandas/3. Quick Object Conversions.srt 10KB
  249. 6. DataFrames III Data Extraction/4. Retrieve Rows by Index Position with iloc Accessor.srt 10KB
  250. 7. Working with Text Data/9. Exploring the expand and n Parameters of the str.split Method.srt 10KB
  251. 11. Working with Dates and Times in Datasets/14. The pd.DateOffset Object.srt 10KB
  252. 5. DataFrames II Filtering Data/7. Check For Inclusion Within a Range of Values with the between Method.srt 10KB
  253. 1. Installation and Setup/10. Windows - Install Anaconda Distribution.srt 10KB
  254. 11. Working with Dates and Times in Datasets/3. The pandas Timestamp Object.srt 10KB
  255. 14. Options and Settings in pandas/3. Changing pandas Options with Methods.srt 10KB
  256. 7. Working with Text Data/4. Filter a DataFrame's Rows with String Methods.srt 10KB
  257. 10. Merging, Joining, and Concatenating DataFrames/3. The pd.concat Method, Part 2.srt 10KB
  258. 6. DataFrames III Data Extraction/16. Create a Copy of a DataFrame with the copy Method.srt 10KB
  259. 4. DataFrames I Introduction/3. Differences between Shared Methods.srt 10KB
  260. 3. Series/25. Use the apply Method to Invoke a Function on Every Series Values.srt 10KB
  261. 6. DataFrames III Data Extraction/15. Apply a Function to every DataFrame Row with the apply Method.srt 10KB
  262. 8. MultiIndex/9. The .stack() Method.srt 10KB
  263. 5. DataFrames II Filtering Data/5. Check for Inclusion with the isin Method.srt 10KB
  264. 3. Series/26. The Series#map Method.srt 9KB
  265. 4. DataFrames I Introduction/11. Drop DataFrame Rows with Null Values with the dropna Method.srt 9KB
  266. 13. Visualization/4. Creating Bar Graphs to Show Counts.srt 9KB
  267. 6. DataFrames III Data Extraction/7. Set Multiple Values in a DataFrame.srt 9KB
  268. 8. MultiIndex/11. The .unstack() Method, Part 2.srt 9KB
  269. 3. Series/13. Use the sort_values method to sort a Series in ascending or descending order.srt 9KB
  270. 8. MultiIndex/15. Use the pd.melt method to create a narrow dataset from a wide one.srt 9KB
  271. 7. Working with Text Data/1. Intro to the Working with Text Data Section.srt 9KB
  272. 9. The GroupBy Object/6. The .agg() Method.srt 9KB
  273. 3. Series/12. Accessing More Series Attributes.srt 9KB
  274. 4. DataFrames I Introduction/19. Rank Series Values with the rank Method.srt 9KB
  275. 7. Working with Text Data/8. More Practice with the str.split method on a Series.srt 8KB
  276. 4. DataFrames I Introduction/6. Select Two or More Columns from a DataFrame.srt 8KB
  277. 12. Input and Output in pandas/4. Export CSV File with the to_csv Method.srt 8KB
  278. 4. DataFrames I Introduction/15. Sort a DataFrame with the sort_values Method, Part I.srt 8KB
  279. 3. Series/14. Use the inplace Parameter to permanently mutate a pandas data structure.srt 8KB
  280. 5. DataFrames II Filtering Data/6. Check for Null and Present DataFrame Values with the isnull and notnull Methods.srt 8KB
  281. 10. Merging, Joining, and Concatenating DataFrames/2. The pd.concat Method, Part 1.srt 8KB
  282. 6. DataFrames III Data Extraction/14. A Review of the apply Method on a pandas Series Object.srt 8KB
  283. 13. Visualization/1. Intro to Visualization Section.srt 8KB
  284. 8. MultiIndex/12. The .unstack() Method, Part 3.srt 8KB
  285. 3. Series/22. Math Methods on Series Objects.srt 8KB
  286. 7. Working with Text Data/6. Invoke String Methods on DataFrame Index and Columns.srt 8KB
  287. 6. DataFrames III Data Extraction/11. Use the nsmallest nlargest methods to get rows with smallest largest values..srt 8KB
  288. 1. Installation and Setup/9. Windows - Download the Anaconda Distribution.srt 8KB
  289. 13. Visualization/3. Modifying Plot Aesthetics with matplotlib Templates.srt 7KB
  290. 3. Series/11. Passing pandas Objects to Python Built-In Functions.srt 7KB
  291. 6. DataFrames III Data Extraction/1. Intro to the DataFrames III Module + Import Dataset.srt 7KB
  292. 3. Series/6. Intro to Methods on a Series Object.srt 7KB
  293. 13. Visualization/5. Creating Pie Charts to Represent Proportions.srt 7KB
  294. 8. MultiIndex/1. Intro to the MultiIndex Module.srt 7KB
  295. 10. Merging, Joining, and Concatenating DataFrames/1. Intro to the Merging, Joining, and Concatenating Section.srt 7KB
  296. 6. DataFrames III Data Extraction/12. Filter A DataFrame with the where method.srt 7KB
  297. 11. Working with Dates and Times in Datasets/4. The pandas DateTimeIndex Object.srt 7KB
  298. 1. Installation and Setup/4. MacOS - Download the Anaconda Distribution, our Python development environment.srt 7KB
  299. 4. DataFrames I Introduction/13. Fill in Null DataFrame Values with the fillna Method.srt 7KB
  300. 6. DataFrames III Data Extraction/6. Set New Value for a Specific Cell or Cells In a Row.srt 7KB
  301. 6. DataFrames III Data Extraction/10. Create Random Sample with the sample Method.srt 7KB
  302. 3. Series/15. Use the sort_index Method to Sort the Index of a pandas Series object.srt 7KB
  303. 9. The GroupBy Object/5. Grouping by Multiple Columns.srt 7KB
  304. 11. Working with Dates and Times in Datasets/1. Intro to the Working with Dates and Times Module.srt 7KB
  305. 5. DataFrames II Filtering Data/3. Filter DataFrame with More than One Condition (AND - &).srt 7KB
  306. 5. DataFrames II Filtering Data/10. Identify and Count Unique Values with the unique and nunique Methods.srt 6KB
  307. 12. Input and Output in pandas/2. Pass a URL to the pd.read_csv Method.srt 6KB
  308. 7. Working with Text Data/5. More DataFrame String Methods - strip, lstrip, and rstrip.srt 6KB
  309. 4. DataFrames I Introduction/16. Sort a DataFrame with the sort_values Method, Part II.srt 6KB
  310. 12. Input and Output in pandas/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.srt 6KB
  311. 8. MultiIndex/3. Extract Index Level Values with the get_level_values Method.srt 6KB
  312. 2. BONUS Python Crash Course/1. Intro to the Python Crash Course.srt 6KB
  313. 3. Series/18. Extract Series Values by Index Positiox.srt 6KB
  314. 4. DataFrames I Introduction/10. A Review of the value_counts Method.srt 6KB
  315. 8. MultiIndex/4. Change Index Level Name with the set_names Method.srt 6KB
  316. 8. MultiIndex/10. The .unstack() Method, Part 1.srt 6KB
  317. 3. Series/17. Use Python's in Keyword to Check for Inclusion in Series values or index.srt 6KB
  318. 1. Installation and Setup/16. Popular Keyboard Shortcuts in Jupyter Notebook.srt 6KB
  319. 11. Working with Dates and Times in Datasets/10. Install pandas-datareader Library.srt 6KB
  320. 9. The GroupBy Object/3. Retrieve a group from a GroupBy object with the get_group Method.srt 5KB
  321. 3. Series/10. Use the head and tail Methods to Return Rows from Beginning and End of Dataset.srt 5KB
  322. 8. MultiIndex/8. The .swaplevel() Method.srt 5KB
  323. 3. Series/24. Use the value_counts Method to See Counts of Unique Values within a Series.srt 5KB
  324. 2. BONUS Python Crash Course/2. Comments.srt 5KB
  325. 14. Options and Settings in pandas/4. The precision Option.srt 5KB
  326. 10. Merging, Joining, and Concatenating DataFrames/11. The pd.merge() Method.srt 5KB
  327. 1. Installation and Setup/15. Code Cell Execution in Jupyter Notebook.srt 5KB
  328. 10. Merging, Joining, and Concatenating DataFrames/10. The .join() Method.srt 5KB
  329. 3. Series/23. Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value.srt 4KB
  330. 3. Series/3. Create A Series Object from a Python Dictionary.srt 4KB
  331. 4. DataFrames I Introduction/18. Sort DataFrame Indexwith the sort_index Method.srt 4KB
  332. 3. Series/1. Create Jupyter Notebook for the Series Module.srt 3KB
  333. 15. Conclusion/1. Conclusion.srt 3KB
  334. 14. Options and Settings in pandas/1. Introduction to the Options and Settings Module.srt 3KB
  335. 12. Input and Output in pandas/1. Intro to the Input and Output Section.srt 2KB
  336. 15. Conclusion/2. Bonus!.html 2KB
  337. 1. Installation and Setup/2. About Me.srt 2KB
  338. 1. Installation and Setup/3. Completed Course Files.html 1KB
  339. 1. Installation and Setup/18. Troubleshooting Issues with Jupyter Notebook.html 420B
  340. 6. DataFrames III Data Extraction/4.1 Official pandas documentation for the pandas.DataFrame.iloc accessor.html 183B
  341. 6. DataFrames III Data Extraction/3.1 Official pandas documentation for the pandas.DataFrame.loc accessor.html 180B
  342. 8. MultiIndex/6.1 Official pandas article on advanced indexing with hierarchical index.html 172B
  343. 11. Working with Dates and Times in Datasets/14.1 Official Pandas documentation for the pandas.DateOffset class.html 158B
  344. 5. DataFrames II Filtering Data/9.1 Official documentation for the DataFrame.drop_duplicates method.html 157B
  345. 8. MultiIndex/3.1 Official pandas documentation for the pandas.Index.get_level_values method.html 154B
  346. 6. DataFrames III Data Extraction/2.2 Official pandas documentation for the pandas.DataFrame.reset_index method.html 153B
  347. 5. DataFrames II Filtering Data/8.1 Official documentation for the DataFrame.duplicated method.html 152B
  348. 8. MultiIndex/5.1 Official pandas documentation for the pandas.DataFrame.sort_index method.html 152B
  349. 6. DataFrames III Data Extraction/2.1 Official pandas documentation for the pandas.DataFrame.set_index method.html 151B
  350. 8. MultiIndex/2.1 Official pandas documentation for the pandas.DataFrame.set_index method.html 151B
  351. 8. MultiIndex/7.1 Official pandas documentation for the pandas.DataFrame.transpose method.html 151B
  352. 8. MultiIndex/8.1 Official pandas documentation for the pandas.DataFrame.swaplevel method.html 151B
  353. 7. Working with Text Data/3.1 Official pandas documentation for the pandas.Series.str.replace method.html 150B
  354. 10. Merging, Joining, and Concatenating DataFrames/2.2 Official pandas documentation for the pandas.DataFrame.append method.html 148B
  355. 12. Input and Output in pandas/4.1 Official pandas documentation for the pandas.DataFrame.to_csv Method.html 148B
  356. 4. DataFrames I Introduction/15.1 Official pandas Documentation.html 148B
  357. 4. DataFrames I Introduction/16.1 Official pandas Documentation.html 148B
  358. 6. DataFrames III Data Extraction/8.1 Official pandas documentation for the pandas.DataFrame.rename method.html 148B
  359. 7. Working with Text Data/2.1 Official pandas documentation for the pandas.Series.str.upper method.html 148B
  360. 7. Working with Text Data/2.2 Official pandas documentation for the pandas.Series.str.title method.html 148B
  361. 7. Working with Text Data/2.4 Official pandas documentation for the pandas.Series.str.lower method.html 148B
  362. 3. Series/24.1 Official Documentation for the Series.value_counts Method.html 147B
  363. 4. DataFrames I Introduction/18.1 Official pandas Documentation.html 147B
  364. 8. MultiIndex/4.1 Official pandas documentation for the pandas.Index.set_names method.html 147B
  365. 12. Input and Output in pandas/3.1 Official pandas documentation for the pandas.Series.to_dict method.html 146B
  366. 13. Visualization/2.2 Official pandas documentation for the pandas.DataFrame.plot Method.html 146B
  367. 6. DataFrames III Data Extraction/9.1 Official pandas documentation for the pandas.DataFrame.drop method.html 146B
  368. 7. Working with Text Data/2.3 Official pandas documentation for the pandas.Series.str.len method.html 146B
  369. 12. Input and Output in pandas/3.2 Official pandas documentation for the pandas.Series.tolist method.html 145B
  370. 3. Series/13.1 Official pandas Documentation.html 145B
  371. 6. DataFrames III Data Extraction/9.2 Official pandas documentation for the pandas.DataFrame.pop method.html 145B
  372. 3. Series/15.1 Official pandas Documentation.html 144B
  373. 12. Input and Output in pandas/7.1 Official documentation for the pandas.ExcelWriter class.html 143B
  374. 13. Visualization/2.1 Official pandas documentation for the pandas.Series.plot method.html 143B
  375. 4. DataFrames I Introduction/13.1 Official pandas Documentation.html 143B
  376. 4. DataFrames I Introduction/14.1 Official pandas Documentation.html 143B
  377. 5. DataFrames II Filtering Data/5.1 Official Pandas documentation for the Series.isin method.html 143B
  378. 12. Input and Output in pandas/6.1 Official pandas documentation for the pandas.read_excel Method.html 142B
  379. 3. Series/21.1 Official pandas documentation for the pandas.Series.get method.html 142B
  380. 11. Working with Dates and Times in Datasets/13.1 Official Pandas documentation for the pandas.Timestamp class.html 141B
  381. 11. Working with Dates and Times in Datasets/16.1 Official Pandas documentation for the pandas.Timedelta class.html 141B
  382. 4. DataFrames I Introduction/19.1 Official pandas Documentation.html 141B
  383. 10. Merging, Joining, and Concatenating DataFrames/1.1 Official Pandas documentation for the pandas.read_csv method to import a CSV file.html 140B
  384. 6. DataFrames III Data Extraction/1.1 Official pandas documentation for the pd.read_csv method.html 140B
  385. 7. Working with Text Data/1.1 Official Pandas documentation for the pandas.read_csv method to import a CSV file.html 140B
  386. 8. MultiIndex/1.1 Official Pandas documentation for the pandas.read_csv method to import a CSV file.html 140B
  387. 10. Merging, Joining, and Concatenating DataFrames/2.1 Official pandas documentation for the pandas.concat method.html 138B
  388. 10. Merging, Joining, and Concatenating DataFrames/3.1 Official pandas documentation for the pandas.concat method.html 138B
  389. 3. Series/1.1 Official pandas documentation for the Series class.html 138B
  390. 3. Series/10.1 Official pandas Documentation.html 138B
  391. 11. Working with Dates and Times in Datasets/15.1 Official pandas documentation for various timeseries offsets.html 137B
  392. 3. Series/16. The sort_values and sort_index Methods.html 136B
  393. 3. Series/20. Extract Series Values by Index Position or Index Label.html 136B
  394. 3. Series/3.1 pandas documentation for instantiating Series from variety of inputs.html 136B
  395. 3. Series/4. Create a Series Object.html 136B
  396. 3. Series/9. Import Series with the read_csv Method.html 136B
  397. 4. DataFrames I Introduction/12. Delete DataFrame Rows with Missing Values.html 136B
  398. 4. DataFrames I Introduction/17. The sort_values Method on a DataFrame.html 136B
  399. 4. DataFrames I Introduction/5. Select One Column from a DataFrame.html 136B
  400. 4. DataFrames I Introduction/7. Select Two or More Columns from a DataFrame.html 136B
  401. 12. Input and Output in pandas/8. Input and Output.html 135B
  402. 13. Visualization/6. Visualization.html 135B
  403. 3. Series/27. A Review of the Series Module.html 135B
  404. 0. Websites you may like/[FCS Forum].url 133B
  405. 0. Websites you may like/[FreeCourseSite.com].url 127B
  406. 0. Websites you may like/[CourseClub.ME].url 122B
  407. 11. Working with Dates and Times in Datasets/10.1 Official documentation for the pandas-datareader library.html 112B
  408. 1. Installation and Setup/4.1 Download page for Anaconda.html 99B
  409. 1. Installation and Setup/5.1 Official download page for the Anaconda distribution.html 99B
  410. 1. Installation and Setup/9.1 Official download page for the Anaconda distribution.html 99B
  411. 13. Visualization/1.1 Official website for the matplotlib plotting library for python.html 84B