GigaCourse Com Udemy - The Data Analyst Course Complete Data Analyst Bootcamp 2022

1. 01 - Introduction to the Course/001 A Practical Example - What Will You Learn in This Course.mp458.11MB
2. 01 - Introduction to the Course/002 What Does the Course Cover.mp460.77MB
3. 02 - Introduction to Data Analytics/001 Introduction to the World of Business and Data.mp410.4MB
4. 02 - Introduction to Data Analytics/002 Relevant Terms Explained.mp417.13MB
5. 02 - Introduction to Data Analytics/003 Data Analyst Compared to Other Data Jobs.mp48.21MB
6. 02 - Introduction to Data Analytics/004 Data Analyst Job Description.mp419.93MB
7. 02 - Introduction to Data Analytics/005 Why Python.mp415.1MB
8. 03 - Setting up the Environment/001 Introduction.mp413.81MB
9. 03 - Setting up the Environment/002 Programming Explained in a Few Minutes.mp414.34MB
10. 03 - Setting up the Environment/003 Jupyter - Introduction.mp48.2MB
11. 03 - Setting up the Environment/004 Jupyter - Installing Anaconda.mp421.46MB
12. 03 - Setting up the Environment/005 Jupyter - Intro to Using Jupyter.mp45.88MB
13. 03 - Setting up the Environment/006 Jupyter - Working with Notebook Files.mp418.63MB
14. 03 - Setting up the Environment/007 Jupyter - Using Shortcuts.mp46.67MB
15. 03 - Setting up the Environment/008 Jupyter - Handling Error Messages.mp413.26MB
16. 03 - Setting up the Environment/009 Jupyter - Restarting the Kernel.mp44.71MB
17. 04 - Python Basics/001 Python Variables.mp414.08MB
18. 04 - Python Basics/002 Types of Data - Numbers and Boolean Values.mp413.7MB
19. 04 - Python Basics/003 Types of Data - Strings.mp419.73MB
20. 04 - Python Basics/004 Basic Python Syntax - Arithmetic Operators.mp47.29MB
21. 04 - Python Basics/005 Basic Python Syntax - The Double Equality Sign.mp42.72MB
22. 04 - Python Basics/006 Basic Python Syntax - Reassign Values.mp41.87MB
23. 04 - Python Basics/007 Basic Python Syntax - Add Comments.mp42.41MB
24. 04 - Python Basics/008 Basic Python Syntax - Line Continuation.mp41.2MB
25. 04 - Python Basics/009 Basic Python Syntax - Indexing Elements.mp42.37MB
26. 04 - Python Basics/010 Basic Python Syntax - Indentation.mp42.8MB
27. 04 - Python Basics/011 Operators - Comparison Operators.mp44.16MB
28. 04 - Python Basics/012 Operators - Logical and Identity Operators.mp415.05MB
29. 04 - Python Basics/013 Conditional Statements - The IF Statement.mp45.33MB
30. 04 - Python Basics/014 Conditional Statements - The ELSE Statement.mp45.25MB
31. 04 - Python Basics/015 Conditional Statements - The ELIF Statement.mp414.25MB
32. 04 - Python Basics/016 Conditional Statements - A Note on Boolean Values.mp44.25MB
33. 04 - Python Basics/017 Functions - Defining a Function in Python.mp43.23MB
34. 04 - Python Basics/018 Functions - Creating a Function with a Parameter.mp410MB
35. 04 - Python Basics/019 Functions - Another Way to Define a Function.mp46.46MB
36. 04 - Python Basics/020 Functions - Using a Function in Another Function.mp43.24MB
37. 04 - Python Basics/021 Functions - Combining Conditional Statements and Functions.mp46.1MB
38. 04 - Python Basics/022 Functions - Creating Functions That Contain a Few Arguments.mp42.82MB
39. 04 - Python Basics/023 Functions - Notable Built-in Functions in Python.mp48.5MB
40. 04 - Python Basics/024 Sequences - Lists.mp49.53MB
41. 04 - Python Basics/025 Sequences - Using Methods.mp47.93MB
42. 04 - Python Basics/026 Sequences - List Slicing.mp419.19MB
43. 04 - Python Basics/027 Sequences - Tuples.mp47.41MB
44. 04 - Python Basics/028 Sequences - Dictionaries.mp410.14MB
45. 04 - Python Basics/029 Iteration - For Loops.mp45.51MB
46. 04 - Python Basics/030 Iteration - While Loops and Incrementing.mp49.15MB
47. 04 - Python Basics/031 Iteration - Create Lists with the range() Function.mp47.25MB
48. 04 - Python Basics/032 Iteration - Use Conditional Statements and Loops Together.mp47.13MB
49. 04 - Python Basics/033 Iteration - Conditional Statements, Functions, and Loops.mp44.27MB
50. 04 - Python Basics/034 Iteration - Iterating over Dictionaries.mp46.54MB
51. 05 - Fundamentals for Coding in Python/001 Object-Oriented Programming (OOP).mp48.43MB
52. 05 - Fundamentals for Coding in Python/002 Modules, Packages, and the Python Standard Library.mp413.61MB
53. 05 - Fundamentals for Coding in Python/003 Importing Modules.mp47.41MB
54. 05 - Fundamentals for Coding in Python/004 Introduction to Using NumPy and pandas.mp431.9MB
55. 05 - Fundamentals for Coding in Python/005 What is Software Documentation.mp413.4MB
56. 05 - Fundamentals for Coding in Python/006 The Python Documentation.mp443.94MB
57. 06 - Mathematics for Python/002 Scalars and Vectors.mp48.39MB
58. 06 - Mathematics for Python/003 Linear Algebra and Geometry.mp413.56MB
59. 06 - Mathematics for Python/004 Arrays in Python.mp419MB
60. 06 - Mathematics for Python/005 What Is a Tensor.mp411.62MB
61. 06 - Mathematics for Python/006 Adding and Subtracting Matrices.mp422.1MB
62. 06 - Mathematics for Python/007 Errors When Adding Matrices.mp45.76MB
63. 06 - Mathematics for Python/008 Transpose.mp420.5MB
64. 06 - Mathematics for Python/009 Dot Product of Vectors.mp411.36MB
65. 06 - Mathematics for Python/010 Dot Product of Matrices.mp426.42MB
66. 06 - Mathematics for Python/011 Why is Linear Algebra Useful.mp486.22MB
67. 07 - NumPy Basics/001 The NumPy Package and Why We Use It.mp413.03MB
68. 07 - NumPy Basics/002 InstallingUpgrading NumPy.mp43.92MB
69. 07 - NumPy Basics/003 Ndarray.mp47.64MB
70. 07 - NumPy Basics/004 The NumPy Documentation.mp415.82MB
71. 08 - Pandas - Basics/001 Introduction to the pandas Library.mp414.22MB
72. 08 - Pandas - Basics/002 Installing and Running pandas.mp437.73MB
73. 08 - Pandas - Basics/003 Introduction to pandas Series.mp424.62MB
74. 08 - Pandas - Basics/004 Working with Attributes in Python.mp426.84MB
75. 08 - Pandas - Basics/005 Using an Index in pandas.mp415.73MB
76. 08 - Pandas - Basics/006 Label-based vs Position-based Indexing.mp424.52MB
77. 08 - Pandas - Basics/007 More on Working with Indices in Python.mp433.21MB
78. 08 - Pandas - Basics/008 Using Methods in Python - Part I.mp417.04MB
79. 08 - Pandas - Basics/009 Using Methods in Python - Part II.mp49.18MB
80. 08 - Pandas - Basics/010 Parameters vs Arguments.mp416.78MB
81. 08 - Pandas - Basics/011 the pandas Documentation.mp452.02MB
82. 08 - Pandas - Basics/012 Introduction to pandas DataFrames.mp411.71MB
83. 08 - Pandas - Basics/013 Creating DataFrames from Scratch - Part I.mp426.06MB
84. 08 - Pandas - Basics/014 Creating DataFrames from Scratch - Part II.mp429.79MB
85. 08 - Pandas - Basics/015 Additional Notes on Using DataFrames.mp412.41MB
86. 09 - Working with Text Files/001 Working with Files in Python - An Introduction.mp411.73MB
87. 09 - Working with Text Files/002 File vs File Object, Read vs Parse.mp49.23MB
88. 09 - Working with Text Files/003 Structured vs Semi-Structured and Unstructured Data.mp410.85MB
89. 09 - Working with Text Files/004 Data Connectivity through Text Files.mp410.57MB
90. 09 - Working with Text Files/005 Principles of Importing Data in Python.mp416.45MB
91. 09 - Working with Text Files/006 More on Text Files (.txt vs .csv).mp412.82MB
92. 09 - Working with Text Files/007 Fixed-width Files.mp44.73MB
93. 09 - Working with Text Files/008 Common Naming Conventions Used in Programming.mp48.22MB
94. 09 - Working with Text Files/009 Importing Text Files in Python ( open() ).mp424.83MB
95. 09 - Working with Text Files/010 Importing Text Files in Python ( with open() ).mp426.29MB
96. 09 - Working with Text Files/011 Importing .csv Files with pandas - Part I.mp449.84MB
97. 09 - Working with Text Files/012 Importing .csv Files with pandas - Part II.mp410.91MB
98. 09 - Working with Text Files/013 Importing .csv Files with pandas - Part III.mp475.11MB
99. 09 - Working with Text Files/014 Importing Data with the index_col Parameter.mp411.65MB
100. 09 - Working with Text Files/015 Importing Data with NumPy - .loadtxt() vs genfromtxt().mp456.48MB
101. 09 - Working with Text Files/016 Importing Data with NumPy - Partial Cleaning While Importing.mp430.51MB
102. 09 - Working with Text Files/018 Importing .json Files.mp448.53MB
103. 09 - Working with Text Files/019 Prelude to Working with Excel Files in Python.mp443.03MB
104. 09 - Working with Text Files/020 Working with Excel Data (the .xlsx Format).mp411.55MB
105. 09 - Working with Text Files/021 An Important Exercise on Importing Data in Python.mp442.97MB
106. 09 - Working with Text Files/022 Importing Data with the pandas' Squeeze Parameter.mp411.58MB
107. 09 - Working with Text Files/023 A Note on Importing Files in Jupyter.mp419.68MB
108. 09 - Working with Text Files/024 Saving Your Data with pandas.mp427.68MB
109. 09 - Working with Text Files/025 Saving Your Data with NumPy - np.save().mp418.93MB
110. 09 - Working with Text Files/026 Saving Your Data with NumPy - np.savez().mp415.41MB
111. 09 - Working with Text Files/027 Saving Your Data with NumPy - np.savetxt().mp420.84MB
112. 09 - Working with Text Files/029 Working with Text Files - Conclusion.mp42.06MB
113. 10 - Working with Text Data/001 Working with Text Data and Argument Specifiers.mp421.35MB
114. 10 - Working with Text Data/002 Manipulating Python Strings.mp412.29MB
115. 10 - Working with Text Data/003 Using Various Python String Methods - Part I.mp423.59MB
116. 10 - Working with Text Data/004 Using Various Python String Methods - Part II.mp420.37MB
117. 10 - Working with Text Data/005 String Accessors.mp430.62MB
118. 10 - Working with Text Data/006 Using the .format() Method.mp421.66MB
119. 11 - Must-Know Python Tools/001 Iterating Over Range Objects.mp411.06MB
120. 11 - Must-Know Python Tools/002 Nested For Loops - Introduction.mp412.21MB
121. 11 - Must-Know Python Tools/003 Triple Nested For Loops.mp419.41MB
122. 11 - Must-Know Python Tools/004 List Comprehensions.mp443.2MB
123. 11 - Must-Know Python Tools/005 Anonymous (Lambda) Functions.mp433.7MB
124. 12 - Data GatheringData Collection/001 What is data gatheringdata collection.mp419.17MB
125. 13 - APIs (POST requests are not needed for this course)/001 Overview of APIs.mp410.4MB
126. 13 - APIs (POST requests are not needed for this course)/002 GET and POST Requests.mp46.27MB
127. 13 - APIs (POST requests are not needed for this course)/003 Data Exchange Format for APIs JSON.mp45.7MB
128. 13 - APIs (POST requests are not needed for this course)/004 Introducing the Exchange Rates API.mp425.19MB
129. 13 - APIs (POST requests are not needed for this course)/005 Including Parameters in a GET Request.mp410.8MB
130. 13 - APIs (POST requests are not needed for this course)/006 More Functionalities of the Exchange Rates API.mp416.6MB
131. 13 - APIs (POST requests are not needed for this course)/007 Coding a Simple Currency Conversion Calculator.mp422.44MB
132. 13 - APIs (POST requests are not needed for this course)/008 iTunes API.mp439.61MB
133. 13 - APIs (POST requests are not needed for this course)/010 iTunes API Structuring and Exporting the Data.mp412.86MB
134. 13 - APIs (POST requests are not needed for this course)/011 Pagination GitHub API.mp428.21MB
135. 14 - Data Cleaning and Data Preprocessing/001 Data Cleaning and Data Preprocessing.mp416.47MB
136. 15 - pandas Series/001 .unique(), .nunique().mp426.29MB
137. 15 - pandas Series/002 Converting Series into Arrays.mp419.86MB
138. 15 - pandas Series/003 .sort_values().mp413.19MB
139. 15 - pandas Series/004 Attribute and Method Chaining.mp414.76MB
140. 15 - pandas Series/005 .sort_index().mp415.69MB
141. 16 - pandas DataFrames/001 A Revision to pandas DataFrames.mp417.82MB
142. 16 - pandas DataFrames/002 Common Attributes for Working with DataFrames.mp429.78MB
143. 16 - pandas DataFrames/003 Data Selection in pandas DataFrames.mp437.28MB
144. 16 - pandas DataFrames/004 Data Selection - Indexing with .iloc[].mp423.53MB
145. 16 - pandas DataFrames/005 Data Selection - Indexing with .loc[].mp421.62MB
146. 16 - pandas DataFrames/006 A Few Comments on Using .loc[] and .iloc[].mp476.91MB
147. 17 - NumPy Fundamentals/001 Indexing in NumPy.mp414.87MB
148. 17 - NumPy Fundamentals/002 Assigning Values in NumPy.mp410.14MB
149. 17 - NumPy Fundamentals/003 Elementwise Properties of Arrays.mp414.92MB
150. 17 - NumPy Fundamentals/004 Types of Data Supported by NumPy.mp418.13MB
151. 17 - NumPy Fundamentals/005 Characteristics of NumPy Functions Part 1.mp423.18MB
152. 17 - NumPy Fundamentals/006 Characteristics of NumPy Functions Part 2.mp410.14MB
153. 18 - NumPy DataTypes/001 ndarrays.mp429.33MB
154. 18 - NumPy DataTypes/002 Arrays vs Lists.mp416.58MB
155. 18 - NumPy DataTypes/003 Strings vs Object vs Number.mp424.78MB
156. 19 - Working with Arrays/001 Basic Slicing in NumPy.mp426.56MB
157. 19 - Working with Arrays/002 Stepwise Slicing in NumPy.mp413.98MB
158. 19 - Working with Arrays/003 Conditional Slicing in NumPy.mp416.14MB
159. 19 - Working with Arrays/004 Dimensions and the Squeeze Function.mp418.26MB
160. 20 - Generating Data with NumPy/001 Arrays of 0s and 1s.mp416.16MB
161. 20 - Generating Data with NumPy/002 _like functions in NumPy.mp48.74MB
162. 20 - Generating Data with NumPy/003 A Non-Random Sequence of Numbers.mp419.98MB
163. 20 - Generating Data with NumPy/004 Random Generators and Seeds.mp419.32MB
164. 20 - Generating Data with NumPy/005 Basic Random Functions in NumPy.mp414.84MB
165. 20 - Generating Data with NumPy/006 Probability Distributions in NumPy.mp431.54MB
166. 20 - Generating Data with NumPy/007 Applications of Random Data in NumPy.mp429.41MB
167. 21 - Statistics with NumPy/001 Using Statistical Functions in NumPy.mp421.25MB
168. 21 - Statistics with NumPy/002 Minimal and Maximal Values in NumPy.mp419.95MB
169. 21 - Statistics with NumPy/003 Statistical Order Functions in NumPy.mp427.37MB
170. 21 - Statistics with NumPy/004 Averages and Variance in NumPy.mp414.57MB
171. 21 - Statistics with NumPy/005 Covariance and Correlation in NumPy.mp48.74MB
172. 21 - Statistics with NumPy/006 Histograms in NumPy (Part 1).mp422.1MB
173. 21 - Statistics with NumPy/007 Histograms in NumPy (Part 2).mp411.52MB
174. 21 - Statistics with NumPy/008 NAN Equivalent Functions in NumPy.mp416.77MB
175. 22 - NumPy - Preprocessing/001 Checking for Missing Values in Ndarrays.mp447.88MB
176. 22 - NumPy - Preprocessing/002 Substituting Missing Values in Ndarrays.mp434.32MB
177. 22 - NumPy - Preprocessing/003 Reshaping Ndarrays.mp424.59MB
178. 22 - NumPy - Preprocessing/004 Removing Values from Ndarrays.mp419.93MB
179. 22 - NumPy - Preprocessing/005 Sorting Ndarrays.mp455.27MB
180. 22 - NumPy - Preprocessing/006 Argument Sort in NumPy.mp429.52MB
181. 22 - NumPy - Preprocessing/007 Argument Where in NumPy.mp451.52MB
182. 22 - NumPy - Preprocessing/008 Shuffling Ndarrays.mp432.96MB
183. 22 - NumPy - Preprocessing/009 Casting Ndarrays.mp440.24MB
184. 22 - NumPy - Preprocessing/010 Striping Values from Ndarrays.mp418.41MB
185. 22 - NumPy - Preprocessing/011 Stacking Ndarrays.mp465.14MB
186. 22 - NumPy - Preprocessing/012 Concatenating Ndarrays.mp435.68MB
187. 22 - NumPy - Preprocessing/013 Finding Unique Values in Ndarrays.mp427.75MB
188. 23 - A Loan Data Example with NumPy/001 Setting Up Introduction to the Practical Example.mp420.53MB
189. 23 - A Loan Data Example with NumPy/002 Setting Up Importing the Data Set.mp436.9MB
190. 23 - A Loan Data Example with NumPy/003 Setting Up Checking for Incomplete Data.mp417.14MB
191. 23 - A Loan Data Example with NumPy/004 Setting Up Splitting the Dataset.mp419.76MB
192. 23 - A Loan Data Example with NumPy/005 Setting Up Creating Checkpoints.mp411.01MB
193. 23 - A Loan Data Example with NumPy/006 Manipulating Text Data Issue Date.mp414.92MB
194. 23 - A Loan Data Example with NumPy/007 Manipulating Text Data Loan Status and Term.mp425.16MB
195. 23 - A Loan Data Example with NumPy/008 Manipulating Text Data Grade and Sub Grade.mp441.2MB
196. 23 - A Loan Data Example with NumPy/009 Manipulating Text Data Verification Status & URL.mp426.67MB
197. 23 - A Loan Data Example with NumPy/010 Manipulating Text Data State Address.mp426.23MB
198. 23 - A Loan Data Example with NumPy/011 Manipulating Text Data Converting Strings and Creating a Checkpoint.mp48.66MB
199. 23 - A Loan Data Example with NumPy/012 Manipulating Numeric Data Substitute Filler Values.mp427.86MB
200. 23 - A Loan Data Example with NumPy/013 Manipulating Numeric Data Currency Change – The Exchange Rate.mp418.99MB
201. 23 - A Loan Data Example with NumPy/014 Manipulating Numeric Data Currency Change - From USD to EUR.mp431.45MB
202. 23 - A Loan Data Example with NumPy/015 Completing the Dataset.mp444.04MB
203. 24 - The Absenteeism Exercise - Introduction/001 An Introduction to the Absenteeism Exercise.mp43.65MB
204. 24 - The Absenteeism Exercise - Introduction/002 The Absenteeism Exercise from a Business Perspective.mp47.19MB
205. 24 - The Absenteeism Exercise - Introduction/003 The Dataset.mp45.66MB
206. 25 - Solution to the Absenteeism Exercise/001 How to Complete the Absenteeism Exercise.mp46.23MB
207. 25 - Solution to the Absenteeism Exercise/002 Eyeball Your Data First.mp454.25MB
208. 25 - Solution to the Absenteeism Exercise/003 Note Programming vs the Rest of the World.mp418.03MB
209. 25 - Solution to the Absenteeism Exercise/004 Using a Statistical Approach to Solve Our Exercise.mp49.9MB
210. 25 - Solution to the Absenteeism Exercise/005 Dropping the 'ID' Column.mp441.33MB
211. 25 - Solution to the Absenteeism Exercise/006 Analysis of the 'Reason for Absence' Column.mp417.18MB
212. 25 - Solution to the Absenteeism Exercise/007 Splitting the Reasons for Absence into Multiple Dummy Variables.mp463.76MB
213. 25 - Solution to the Absenteeism Exercise/008 Working with Dummy Variables - A Statistical Perspective.mp45.82MB
214. 25 - Solution to the Absenteeism Exercise/009 Grouping the Reason for Absence Columns.mp451.32MB
215. 25 - Solution to the Absenteeism Exercise/010 Concatenating Columns in a pandas DataFrame.mp419.77MB
216. 25 - Solution to the Absenteeism Exercise/011 Reordering Columns in a DataFrame.mp47.2MB
217. 25 - Solution to the Absenteeism Exercise/012 Working on the 'Date' Column.mp426.06MB
218. 25 - Solution to the Absenteeism Exercise/013 Extracting the Month Value from the 'Date' Column.mp437.05MB
219. 25 - Solution to the Absenteeism Exercise/014 Creating the 'Day of the Week' Column.mp423.33MB
220. 25 - Solution to the Absenteeism Exercise/015 Understanding the Meaning of 5 More Columns.mp412.25MB
221. 25 - Solution to the Absenteeism Exercise/016 Modifying the 'Education' Column.mp419.66MB
222. 25 - Solution to the Absenteeism Exercise/017 Final Remarks on the Absenteeism Exercise.mp414.91MB
223. 26 - Data Visualization/001 What Is Data Visualization and Why Is It Important.mp413.97MB
224. 26 - Data Visualization/002 Why Learn Data Visualization.mp426.44MB
225. 26 - Data Visualization/003 Choosing the Right Visualization – What Are Some Popular Approaches and Framewor.mp443.8MB
226. 26 - Data Visualization/004 Introduction into Colors and Color Theory.mp456.19MB
227. 26 - Data Visualization/005 Bar Chart - Introduction - General Theory and Getting to Know the Dataset.mp410.81MB
228. 26 - Data Visualization/006 Bar Chart - How to Create a Bar Chart Using Python.mp431.86MB
229. 26 - Data Visualization/007 Bar Chart – Interpreting the Bar Graph. How to Make a Good Bar Graph.mp48.2MB
230. 26 - Data Visualization/008 Pie Chart - Introduction - General Theory and Dataset.mp422.69MB
231. 26 - Data Visualization/009 Pie Chart - How to Create a Pie Chart Using Python.mp416.29MB
232. 26 - Data Visualization/010 Pie Chart – Interpreting the Pie Chart.mp49.74MB
233. 26 - Data Visualization/011 Pie Chart - Why You Should Never Create a Pie Graph.mp446.37MB
234. 26 - Data Visualization/012 Stacked Area Chart - Introduction - General Theory. Getting to Know the Dataset.mp47.61MB
235. 26 - Data Visualization/013 Stacked Area Chart - How to Create a Stacked Area Chart Using Python.mp425.04MB
236. 26 - Data Visualization/014 Stacked Area Chart - Interpreting the Stacked Area Graph.mp49.6MB
237. 26 - Data Visualization/015 Stacked Area Chart - How to Make a Good Stacked Area Chart.mp412.62MB
238. 26 - Data Visualization/016 Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp45.05MB
239. 26 - Data Visualization/017 Line Chart - How to Create a Line Chart in Python.mp440.29MB
240. 26 - Data Visualization/018 Line Chart - Interpretation.mp432.7MB
241. 26 - Data Visualization/019 Line Chart - How to Make a Good Line Chart.mp427.18MB
242. 26 - Data Visualization/020 Histogram - Introduction - General Theory. Getting to Know the Dataset.mp414.34MB
243. 26 - Data Visualization/021 Histogram - How to Create a Histogram Using Python.mp414.59MB
244. 26 - Data Visualization/022 Histogram – Interpreting the Histogram.mp44.88MB
245. 26 - Data Visualization/023 Histogram – Choosing the Number of Bins in a Histogram.mp421.1MB
246. 26 - Data Visualization/024 Histogram - How to Make a Good Histogram.mp421.69MB
247. 26 - Data Visualization/025 Scatter Plot - Introduction - General Theory. Getting to Know the Dataset.mp48.74MB
248. 26 - Data Visualization/026 Scatter Plot - How to Create a Scatter Plot Using Python.mp429.78MB
249. 26 - Data Visualization/027 Scatter Plot – Interpreting the Scatter Plot.mp410.21MB
250. 26 - Data Visualization/028 Scatter Plot - How to Make a Good Scatter Plot.mp418.63MB
251. 26 - Data Visualization/029 Regression Plot - Introduction - General Theory. Getting to Know the Dataset.mp49.38MB
252. 26 - Data Visualization/030 Regression Plot - How to Create a Regression Scatter Plot Using Python.mp421.75MB
253. 26 - Data Visualization/031 Regression Plot – Interpreting the Regression Scatter Plot.mp417.43MB
254. 26 - Data Visualization/032 Regression Plot - How to Make a Good Regression Plot.mp412.35MB
255. 26 - Data Visualization/033 Bar and Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp49.35MB
256. 26 - Data Visualization/034 Bar and Line Chart - How to Create a Combination Bar and Line Graph Using Python.mp426.31MB
257. 26 - Data Visualization/035 Bar and Line Chart – Interpreting the Combination Bar and Line Graph.mp47.74MB
258. 26 - Data Visualization/036 Bar and Line Chart – How to Make a Good Bar and Line Graph.mp416.13MB
259. 27 - Conclusion/001 Conclusion.mp416.19MB