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[DesireCourse.Net] Udemy - Data Analysis with Pandas and Python

DesireCourseUdemyDataAnalysiswithPandasPython

种子大小：2.34 Gb

收录时间：2026-05-19

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文件列表：

  1. 1. Installation and Setup/7. Mac OS - Update Anaconda Libraries.mp435.27 Mb
  2. 1. Installation and Setup/1. Introduction to the Course.mp434 Mb
  3. 10. Working with Dates and Times/16. More Fun with pd.DateOffset Objects.mp431.91 Mb
  4. 4. DataFrames II/2. Filter a DataFrame Based on A Condition.mp427.4 Mb
  5. 9. Merging, Joining, and Concatenating/7. Outer Joins.mp425.94 Mb
  6. 5. DataFrames III/3. Retrieve Rows by Index Label with .loc[].mp425.87 Mb
  7. 10. Working with Dates and Times/15. pd.DateOffset Objects.mp425.58 Mb
  8. 10. Working with Dates and Times/11. Import Financial Data Set with pandas_datareader Library.mp425.48 Mb
  9. 4. DataFrames II/1. This Module's Dataset + Memory Optimization.mp424.45 Mb
  10. 3. DataFrames I/11. The .astype() Method.mp423.86 Mb
  11. 8. GroupBy/2. First Operations with groupby Object.mp423.08 Mb
  12. 10. Working with Dates and Times/5. The pd.to_datetime() Method.mp422.88 Mb
  13. 9. Merging, Joining, and Concatenating/10. Merging by Indexes with the left_index and right_index Parameters.mp422.7 Mb
  14. 7. MultiIndex/14. The .pivot_table() Method.mp422.16 Mb
  15. 1. Installation and Setup/8. Mac OS - Unpack Course Materials + The Startdown and Shutdown Process.mp422.15 Mb
  16. 8. GroupBy/7. Iterating through Groups.mp421.37 Mb
  17. 1. Installation and Setup/2. About Me.mp421.3 Mb
  18. 2. Series/7. Import Series with the .read_csv() Method.mp421.14 Mb
  19. 7. MultiIndex/2. Create a MultiIndex with the set_index() Method.mp421.05 Mb
  20. 9. Merging, Joining, and Concatenating/8. Left Joins.mp420.99 Mb
  21. 5. DataFrames III/8. Set Multiple Values in DataFrame.mp420.54 Mb
  22. 8. GroupBy/4. Methods on the Groupby Object and DataFrame Columns.mp420.49 Mb
  23. 9. Merging, Joining, and Concatenating/9. The left_on and right_on Parameters.mp420.24 Mb
  24. 5. DataFrames III/14. The .query() Method.mp419.93 Mb
  25. 14. Options and Settings/2. Changing pandas Options with Attributes and Dot Syntax.mp419.83 Mb
  26. 10. Working with Dates and Times/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp419.68 Mb
  27. 10. Working with Dates and Times/13. Timestamp Object Attributes.mp419.57 Mb
  28. 4. DataFrames II/8. The .duplicated() Method.mp419.56 Mb
  29. 10. Working with Dates and Times/18. Timedeltas in a Dataset.mp419.55 Mb
  30. 3. DataFrames I/9. Drop Rows with Null Values.mp419.2 Mb
  31. 12. Input and Output/6. Import Excel File into pandas.mp419.13 Mb
  32. 1. Installation and Setup/11. Windows - Access the Command Prompt and Update Anaconda Libraries.mp419.06 Mb
  33. 13. Visualization/2. The .plot() Method.mp418.97 Mb
  34. 5. DataFrames III/5. The Catch-All .ix[] Method.mp418.56 Mb
  35. 10. Working with Dates and Times/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp418.54 Mb
  36. 10. Working with Dates and Times/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp418.34 Mb
  37. 2. Series/6. Parameters and Arguments.mp418.29 Mb
  38. 3. DataFrames I/7. Broadcasting Operations.mp418.23 Mb
  39. 2. Series/2. Create A Series Object from a Python List.mp418.12 Mb
  40. 1. Installation and Setup/5. Mac OS - Install Anaconda Distribution.mp418.06 Mb
  41. 9. Merging, Joining, and Concatenating/5. Inner Joins, Part 1.mp417.92 Mb
  42. 12. Input and Output/7. Export Excel File.mp417.8 Mb
  43. 9. Merging, Joining, and Concatenating/6. Inner Joins, Part 2.mp417.75 Mb
  44. 3. DataFrames I/1. Intro to DataFrames I Module.mp417.63 Mb
  45. 4. DataFrames II/9. The .drop_duplicates() Method.mp417.55 Mb
  46. 6. Working with Text Data/7. Split Strings by Characters with .str.split() Method.mp417.52 Mb
  47. 7. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp417.34 Mb
  48. 7. MultiIndex/15. The pd.melt() Method.mp417.26 Mb
  49. 3. DataFrames I/6. Add New Column to DataFrame.mp417.23 Mb
  50. 4. DataFrames II/7. The .between() Method.mp416.76 Mb
  51. 4. DataFrames II/4. Filter with More than One Condition (OR - ).mp416.75 Mb
  52. 10. Working with Dates and Times/2. Review of Python's datetime Module.mp416.73 Mb
  53. 7. MultiIndex/3. The .get_level_values() Method.mp416.54 Mb
  54. 10. Working with Dates and Times/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp416.34 Mb
  55. 11. Panels/3. The Axes of a Panel Object.mp416.31 Mb
  56. 5. DataFrames III/10. Delete Rows or Columns from a DataFrame.mp416.22 Mb
  57. 6. Working with Text Data/3. The .str.replace() Method.mp416 Mb
  58. 11. Panels/10. Transpose a Panel with the .transpose() Method.mp415.74 Mb
  59. 3. DataFrames I/2. Shared Methods and Attributes between Series and DataFrames.mp415.62 Mb
  60. 6. Working with Text Data/4. Filtering with String Methods.mp415.54 Mb
  61. 1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp415.47 Mb
  62. 5. DataFrames III/17. The .copy() Method.mp415.44 Mb
  63. 10. Working with Dates and Times/17. The pandas Timedelta Object.mp415.41 Mb
  64. 6. Working with Text Data/9. The expand and n Parameters of the .str.split() Method.mp415.3 Mb
  65. 1. Installation and Setup/10. Windows - Install Anaconda Distribution.mp415.2 Mb
  66. 6. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp414.88 Mb
  67. 3. DataFrames I/4. Select One Column from a DataFrame.mp414.87 Mb
  68. 7. MultiIndex/11. The .unstack() Method, Part 2.mp414.54 Mb
  69. 8. GroupBy/1. Intro to the Groupby Module.mp414.29 Mb
  70. 14. Options and Settings/3. Changing pandas Options with Methods.mp413.92 Mb
  71. 6. Working with Text Data/1. Intro to the Working with Text Data Module.mp413.86 Mb
  72. 2. Series/16. Extract Series Values by Index Label.mp413.73 Mb
  73. 10. Working with Dates and Times/9. The .dt Accessor.mp413.68 Mb
  74. 11. Panels/2. Intro to the Module + Fetch Panel Dataset from Google Finance.mp413.67 Mb
  75. 11. Panels/9. The .minor_xs() Method.mp413.62 Mb
  76. 5. DataFrames III/13. Filtering with the .where() Method.mp413.56 Mb
  77. 11. Panels/6. Extracting with the .loc, .iloc, and .ix Methods.mp413.53 Mb
  78. 5. DataFrames III/16. The .apply() Method with Row Values.mp413.41 Mb
  79. 5. DataFrames III/9. Rename Index Labels or Columns in a DataFrame.mp413.39 Mb
  80. 5. DataFrames III/4. Retrieve Rows by Index Position with .iloc[].mp413.31 Mb
  81. 3. DataFrames I/12. Sort a DataFrame with the .sort_values() Method, Part I.mp413.27 Mb
  82. 9. Merging, Joining, and Concatenating/3. The pd.concat() Method, Part 2.mp413.2 Mb
  83. 7. MultiIndex/9. The .stack() Method.mp413.2 Mb
  84. 5. DataFrames III/2. The .set_index() and .reset_index() Methods.mp413.19 Mb
  85. 8. GroupBy/6. The .agg() Method.mp413.18 Mb
  86. 3. DataFrames I/15. Rank Values with the .rank() Method.mp413.17 Mb
  87. 3. DataFrames I/3. Differences between Shared Methods.mp413.11 Mb
  88. 2. Series/22. The .map() Method.mp413.09 Mb
  89. 2. Series/4. Intro to Attributes.mp412.85 Mb
  90. 10. Working with Dates and Times/3. The pandas Timestamp Object.mp412.8 Mb
  91. 9. Merging, Joining, and Concatenating/2. The pd.concat() Method, Part 1.mp412.56 Mb
  92. 4. DataFrames II/5. The .isin() Method.mp412.53 Mb
  93. 5. DataFrames III/6. Second Arguments to .loc[], .iloc[], and .ix[] Methods.mp412.36 Mb
  94. 2. Series/21. The .apply() Method.mp412.32 Mb
  95. 13. Visualization/4. Bar Graphs.mp412.27 Mb
  96. 4. DataFrames II/6. The .isnull() and .notnull() Methods.mp412.26 Mb
  97. 13. Visualization/6. Histograms.mp412.16 Mb
  98. 11. Panels/8. The .major_xs() Method.mp412.11 Mb
  99. 7. MultiIndex/13. The .pivot() Method.mp412.11 Mb
  100. 13. Visualization/3. Modifying Aesthetics with Templates.mp412.08 Mb
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