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CBTNuggets - Python and Pandas for Data Manipulation

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Title: CBTNuggetsGroup: NOGRPSource: CBTNuggets
Info Hash
2BA17ACE347B118A8231C6B34A5DED15BB84040F
Source
Unverified
Total Size
10.45 GB
Total Files
100
Seeders
0
Leechers
1
Health
Score
1
Type
Bookware

File List

FileSize
1. Introduction.mp446.53 MB
10. Data Types Review.mp460.19 MB
100. Sorting values.mp4150.32 MB
101. Sort by indices.mp456.45 MB
102. Ranking a Series.mp4145.32 MB
103. Introduction.mp448.09 MB
104. Checking for Duplicates.mp4106.81 MB
105. Drop Duplicates.mp495.05 MB
106. Unique Values.mp485.59 MB
107. Inclusion with between().mp4114.66 MB
108. Introduction.mp437.02 MB
109. Setting and Resetting Indices.mp4133.83 MB
11. Cell Types.mp476.56 MB
110. Extraction with loc.mp4120.46 MB
111. Extraction with iloc.mp4109.88 MB
112. Setting New Values.mp464.8 MB
113. Set Multiple Values.mp496.3 MB
12. Shortcuts.mp433.59 MB
13. Introduction.mp458.15 MB
14. Create a Series from a List.mp496.09 MB
15. Create a Series from a Dictionary.mp451.53 MB
16. Read CSV files.mp4104.89 MB
17. Read Excel files.mp469.88 MB
18. Head and Tail Functions.mp493.45 MB
19. Series Attributes.mp453.17 MB
2. What is Pandas.mp4100.15 MB
20. Series Methods.mp460.19 MB
21. Introduction.mp427.22 MB
22. The In Keyword.mp462.14 MB
23. Extract by Position.mp488.22 MB
24. Extract by Label.mp4142.95 MB
25. The get() Method.mp4109.84 MB
26. Math methods.mp469.7 MB
27. The idxmin() and idxmax() Methods.mp434.1 MB
28. Unique Values.mp446.85 MB
29. The apply() Method.mp461.76 MB
3. What is Jupyter Notebook.mp459.49 MB
30. Introduction.mp444.92 MB
31. Handling null values.mp473.65 MB
32. Drop null values.mp499.98 MB
33. Impute missing values.mp466.57 MB
34. Value counts for DataFrames.mp454.76 MB
35. Detect null and not null values.mp476.83 MB
36. Introduction.mp477.91 MB
37. Optimization.mp4164.97 MB
38. Conditional Filtering.mp4185.94 MB
39. Filtering with AND and OR.mp4159.55 MB
4. Anaconda Installation.mp498.43 MB
40. Inclusion Method.mp4101.45 MB
41. Introduction.mp445.45 MB
42. The Drop Method.mp472.31 MB
43. Returning Smallest and Largest Values.mp4115.06 MB
44. The Where Method.mp4103.81 MB
45. The Query Method.mp4112.13 MB
46. The Copy Method.mp4101.31 MB
47. Introduction.mp429.31 MB
48. Manipulating Text Data.mp4148.44 MB
49. String Methods.mp4147.35 MB
5. Conda Environments.mp472.49 MB
50. The Replace String Method.mp4115.62 MB
51. Filtering String Methods.mp4116 MB
52. Strip Strings.mp4203.62 MB
53. Column and Index Methods.mp4110.59 MB
54. Splitting Strings.mp487.59 MB
55. More Splitting.mp483.08 MB
56. Introduction.mp436.87 MB
57. Grouping.mp4118.56 MB
58. Group_by Operations.mp4162.29 MB
59. Get_group Method.mp4126.31 MB
6. Challenge.mp4155.81 MB
60. The Group_by Methods.mp4185.27 MB
61. Introduction.mp460.95 MB
62. Combining DataFrame.mp464.46 MB
63. Concatenation.mp4172.53 MB
64. Inner Joins.mp4104.93 MB
65. Outer Joins.mp440.59 MB
66. DatetimeIndex.mp459.89 MB
67. The to_datetime Method.mp496.78 MB
68. Introduction.mp431.96 MB
69. Date Ranges Part 1 Video 1-A.mp4106.07 MB
7. Introduction.mp4112.26 MB
70. Date Ranges Part 1 Video 1-B.mp4108.92 MB
71. Date Ranges Part 1 Video 1-C.mp486 MB
72. Date Ranges Part 2.mp4120.03 MB
73. Date Ranges Part 3.mp487.4 MB
74. The dt Accessor.mp4119.91 MB
75. Introduction & Setup.mp4128.61 MB
76. Reading Cryptocurrency Data.mp4179.8 MB
77. Selecting Datetime Rows.mp4134.19 MB
78. Timestamp Attributes & Methods.mp4111.37 MB
79. Introduction.mp479.97 MB
8. Brief History.mp4105.07 MB
80. Matplotlib & PyPlot.mp428.34 MB
81. Visualizing Cryptocurrencies.mp4200.11 MB
82. Customizing Visualizations.mp4156.04 MB
83. Creating Charts.mp4147.67 MB
84. Introduction.mp428.39 MB
85. Parameter and Arguments.mp497.88 MB
86. Sort Values.mp474.71 MB
87. Series Attributes.mp488.55 MB

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