FreeCourseSite com Udemy - The Data Analyst Course Complete Data Analyst Bootcamp 2021

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/005 Introduction to the World of Business and Data.mp428.33MB
4. 02 Introduction to Data Analytics/006 Relevant Terms Explained.mp452.77MB
5. 02 Introduction to Data Analytics/007 Data Analyst Compared to Other Data Jobs.mp427.64MB
6. 02 Introduction to Data Analytics/008 Data Analyst Job Description.mp468.12MB
7. 02 Introduction to Data Analytics/009 Why Python.mp445.97MB
8. 03 Setting up the Environment/010 Introduction.mp413.81MB
9. 03 Setting up the Environment/011 Programming Explained in a Few Minutes.mp444.75MB
10. 03 Setting up the Environment/012 Jupyter - Introduction.mp431.16MB
11. 03 Setting up the Environment/013 Jupyter - Installing Anaconda.mp429.59MB
12. 03 Setting up the Environment/014 Jupyter - Intro to Using Jupyter.mp412.11MB
13. 03 Setting up the Environment/015 Jupyter - Working with Notebook Files.mp423.74MB
14. 03 Setting up the Environment/016 Jupyter - Using Shortcuts.mp417.33MB
15. 03 Setting up the Environment/017 Jupyter - Handling Error Messages.mp439.46MB
16. 03 Setting up the Environment/018 Jupyter - Restarting the Kernel.mp48.37MB
17. 04 Python Basics/019 Python Variables.mp414.08MB
18. 04 Python Basics/020 Types of Data - Numbers and Boolean Values.mp413.7MB
19. 04 Python Basics/021 Types of Data - Strings.mp424.15MB
20. 04 Python Basics/022 Basic Python Syntax - Arithmetic Operators.mp415.44MB
21. 04 Python Basics/023 Basic Python Syntax - The Double Equality Sign.mp44.96MB
22. 04 Python Basics/024 Basic Python Syntax - Reassign Values.mp43.34MB
23. 04 Python Basics/025 Basic Python Syntax - Add Comments.mp44.67MB
24. 04 Python Basics/026 Basic Python Syntax - Line Continuation.mp42.11MB
25. 04 Python Basics/027 Basic Python Syntax - Indexing Elements.mp44.87MB
26. 04 Python Basics/028 Basic Python Syntax - Indentation.mp45.47MB
27. 04 Python Basics/029 Operators - Comparison Operators.mp48.23MB
28. 04 Python Basics/030 Operators - Logical and Identity Operators.mp424.07MB
29. 04 Python Basics/031 Conditional Statements - The IF Statement.mp410.81MB
30. 04 Python Basics/032 Conditional Statements - The ELSE Statement.mp410.82MB
31. 04 Python Basics/033 Conditional Statements - The ELIF Statement.mp425.07MB
32. 04 Python Basics/034 Conditional Statements - A Note on Boolean Values.mp48.9MB
33. 04 Python Basics/035 Functions - Defining a Function in Python.mp46.29MB
34. 04 Python Basics/036 Functions - Creating a Function with a Parameter.mp418.08MB
35. 04 Python Basics/037 Functions - Another Way to Define a Function.mp411.14MB
36. 04 Python Basics/038 Functions - Using a Function in Another Function.mp46.49MB
37. 04 Python Basics/039 Functions - Combining Conditional Statements and Functions.mp413.07MB
38. 04 Python Basics/040 Functions - Creating Functions That Contain a Few Arguments.mp46.01MB
39. 04 Python Basics/041 Functions - Notable Built-in Functions in Python.mp417.85MB
40. 04 Python Basics/042 Sequences - Lists.mp417.63MB
41. 04 Python Basics/043 Sequences - Using Methods.mp417.3MB
42. 04 Python Basics/044 Sequences - List Slicing.mp423.91MB
43. 04 Python Basics/045 Sequences - Tuples.mp413.5MB
44. 04 Python Basics/046 Sequences - Dictionaries.mp419.19MB
45. 04 Python Basics/047 Iteration - For Loops.mp411.56MB
46. 04 Python Basics/048 Iteration - While Loops and Incrementing.mp413.08MB
47. 04 Python Basics/049 Iteration - Create Lists with the range() Function.mp414.68MB
48. 04 Python Basics/050 Iteration - Use Conditional Statements and Loops Together.mp412.61MB
49. 04 Python Basics/051 Iteration - Conditional Statements, Functions, and Loops.mp48.15MB
50. 04 Python Basics/052 Iteration - Iterating over Dictionaries.mp413.44MB
51. 05 Fundamentals for Coding in Python/053 Object-Oriented Programming (OOP).mp426.39MB
52. 05 Fundamentals for Coding in Python/054 Modules, Packages, and the Python Standard Library.mp440.43MB
53. 05 Fundamentals for Coding in Python/055 Importing Modules.mp413.15MB
54. 05 Fundamentals for Coding in Python/056 Introduction to Using NumPy and pandas.mp457.56MB
55. 05 Fundamentals for Coding in Python/057 What is Software Documentation_.mp441.16MB
56. 05 Fundamentals for Coding in Python/058 The Python Documentation.mp450.49MB
57. 06 Mathematics for Python/059 What Is а Matrix_.mp426.78MB
58. 06 Mathematics for Python/060 Scalars and Vectors.mp425.84MB
59. 06 Mathematics for Python/061 Linear Algebra and Geometry.mp440.11MB
60. 06 Mathematics for Python/062 Arrays in Python.mp423.87MB
61. 06 Mathematics for Python/063 What Is a Tensor_.mp420.06MB
62. 06 Mathematics for Python/064 Adding and Subtracting Matrices.mp428.79MB
63. 06 Mathematics for Python/065 Errors When Adding Matrices.mp410.16MB
64. 06 Mathematics for Python/066 Transpose.mp433.13MB
65. 06 Mathematics for Python/067 Dot Product of Vectors.mp421.53MB
66. 06 Mathematics for Python/068 Dot Product of Matrices.mp444.15MB
67. 06 Mathematics for Python/069 Why is Linear Algebra Useful.mp4121.2MB
68. 07 NumPy Basics/070 The NumPy Package and Why We Use It.mp436.96MB
69. 07 NumPy Basics/071 Installing_Upgrading NumPy.mp49.1MB
70. 07 NumPy Basics/072 Ndarray.mp415.64MB
71. 07 NumPy Basics/073 The NumPy Documentation.mp436.98MB
72. 08 Pandas - Basics/075 Introduction to the pandas Library.mp451.53MB
73. 08 Pandas - Basics/076 Installing and Running pandas.mp443.82MB
74. 08 Pandas - Basics/077 Introduction to pandas Series.mp442.11MB
75. 08 Pandas - Basics/078 Working with Attributes in Python.mp434.71MB
76. 08 Pandas - Basics/079 Using an Index in pandas.mp427.78MB
77. 08 Pandas - Basics/080 Label-based vs Position-based Indexing.mp431.64MB
78. 08 Pandas - Basics/081 More on Working with Indices in Python.mp437.67MB
79. 08 Pandas - Basics/082 Using Methods in Python - Part I.mp436.24MB
80. 08 Pandas - Basics/083 Using Methods in Python - Part II.mp420.46MB
81. 08 Pandas - Basics/084 Parameters vs Arguments.mp429.67MB
82. 08 Pandas - Basics/085 the pandas Documentation.mp468.48MB
83. 08 Pandas - Basics/086 Introduction to pandas DataFrames.mp425.03MB
84. 08 Pandas - Basics/087 Creating DataFrames from Scratch - Part I.mp450.42MB
85. 08 Pandas - Basics/088 Creating DataFrames from Scratch - Part II.mp440.81MB
86. 08 Pandas - Basics/089 Additional Notes on Using DataFrames.mp417.22MB
87. 09 Working with Text Files/091 Working with Files in Python - An Introduction.mp429.18MB
88. 09 Working with Text Files/092 File vs File Object, Read vs Parse.mp423.82MB
89. 09 Working with Text Files/093 Structured vs Semi-Structured and Unstructured Data.mp432.37MB
90. 09 Working with Text Files/094 Data Connectivity through Text Files.mp429.1MB
91. 09 Working with Text Files/095 Principles of Importing Data in Python.mp449.24MB
92. 09 Working with Text Files/096 More on Text Files (_.txt vs _.csv).mp429.33MB
93. 09 Working with Text Files/097 Fixed-width Files.mp413.83MB
94. 09 Working with Text Files/098 Common Naming Conventions Used in Programming.mp418.19MB
95. 09 Working with Text Files/099 Importing Text Files in Python ( open() ).mp448.76MB
96. 09 Working with Text Files/100 Importing Text Files in Python ( with open() ).mp433.34MB
97. 09 Working with Text Files/101 Importing _.csv Files with pandas - Part I.mp451.63MB
98. 09 Working with Text Files/102 Importing _.csv Files with pandas - Part II.mp424.02MB
99. 09 Working with Text Files/103 Importing _.csv Files with pandas - Part III.mp475.08MB
100. 09 Working with Text Files/104 Importing Data with the _index_col_ Parameter.mp422.3MB
101. 09 Working with Text Files/105 Importing Data with NumPy - .loadtxt() vs genfromtxt().mp476.26MB
102. 09 Working with Text Files/106 Importing Data with NumPy - Partial Cleaning While Importing.mp460.29MB
103. 09 Working with Text Files/108 Importing _.json Files.mp480.58MB
104. 09 Working with Text Files/109 Prelude to Working with Excel Files in Python.mp443.78MB
105. 09 Working with Text Files/110 Working with Excel Data (the _.xlsx Format).mp417.05MB
106. 09 Working with Text Files/111 An Important Exercise on Importing Data in Python.mp448.53MB
107. 09 Working with Text Files/112 Importing Data with the pandas' _Squeeze_ Parameter.mp421.81MB
108. 09 Working with Text Files/113 A Note on Importing Files in Jupyter.mp426.26MB
109. 09 Working with Text Files/114 Saving Your Data with pandas.mp428.77MB
110. 09 Working with Text Files/115 Saving Your Data with NumPy - np.save().mp434.86MB
111. 09 Working with Text Files/116 Saving Your Data with NumPy - np.savez().mp429.64MB
112. 09 Working with Text Files/117 Saving Your Data with NumPy - np.savetxt().mp427.54MB
113. 09 Working with Text Files/119 Working with Text Files - Conclusion.mp45.11MB
114. 10 Working with Text Data/120 Using the .format() Method.mp447.62MB
115. 11 Must-Know Python Tools/121 Iterating Over Range Objects.mp422.44MB
116. 11 Must-Know Python Tools/122 Nested For Loops - Introduction.mp429.44MB
117. 11 Must-Know Python Tools/123 Triple Nested For Loops.mp446.58MB
118. 11 Must-Know Python Tools/124 List Comprehensions.mp455.36MB
119. 11 Must-Know Python Tools/125 Anonymous (Lambda) Functions.mp438.52MB
120. 12 Data Gathering_Data Collection/126 What is data gathering_data collection_.mp451.97MB
121. 13 APIs (POST requests are not needed for this course)/127 Overview of APIs.mp432.22MB
122. 13 APIs (POST requests are not needed for this course)/128 GET and POST Requests.mp424.06MB
123. 13 APIs (POST requests are not needed for this course)/129 Data Exchange Format for APIs_ JSON.mp422.26MB
124. 13 APIs (POST requests are not needed for this course)/130 Introducing the Exchange Rates API.mp436.43MB
125. 13 APIs (POST requests are not needed for this course)/131 Including Parameters in a GET Request.mp421.64MB
126. 13 APIs (POST requests are not needed for this course)/132 More Functionalities of the Exchange Rates API.mp432.42MB
127. 13 APIs (POST requests are not needed for this course)/133 Coding a Simple Currency Conversion Calculator.mp428.73MB
128. 13 APIs (POST requests are not needed for this course)/134 iTunes API.mp440.75MB
129. 13 APIs (POST requests are not needed for this course)/136 iTunes API_ Structuring and Exporting the Data.mp419.79MB
130. 13 APIs (POST requests are not needed for this course)/137 Pagination_ GitHub API.mp433.81MB
131. 14 Data Cleaning and Data Preprocessing/139 Data Cleaning and Data Preprocessing.mp451.14MB
132. 15 pandas Series/140 .unique(), .nunique().mp427.79MB
133. 15 pandas Series/141 Converting Series into Arrays.mp441.78MB
134. 15 pandas Series/142 .sort_values().mp427.68MB
135. 15 pandas Series/143 Attribute and Method Chaining.mp431.15MB
136. 15 pandas Series/144 .sort_index().mp429.35MB
137. 16 pandas DataFrames/145 A Revision to pandas DataFrames.mp435.9MB
138. 16 pandas DataFrames/146 Common Attributes for Working with DataFrames.mp433.79MB
139. 16 pandas DataFrames/147 Data Selection in pandas DataFrames.mp450.08MB
140. 16 pandas DataFrames/148 Data Selection - Indexing with .iloc[].mp441.37MB
141. 16 pandas DataFrames/149 Data Selection - Indexing with .loc[].mp428.38MB
142. 16 pandas DataFrames/150 A Few Comments on Using .loc[] and .iloc[].mp4105.68MB
143. 17 NumPy Fundamentals/151 Indexing in NumPy.mp430.5MB
144. 17 NumPy Fundamentals/152 Assigning Values in NumPy.mp419.74MB
145. 17 NumPy Fundamentals/153 Elementwise Properties of Arrays.mp426.02MB
146. 17 NumPy Fundamentals/154 Types of Data Supported by NumPy.mp437.16MB
147. 17 NumPy Fundamentals/155 Characteristics of NumPy Functions Part 1.mp432.91MB
148. 17 NumPy Fundamentals/156 Characteristics of NumPy Functions Part 2.mp421.4MB
149. 18 NumPy DataTypes/158 ndarrays.mp452.22MB
150. 18 NumPy DataTypes/159 Arrays vs Lists.mp431.26MB
151. 18 NumPy DataTypes/160 Strings vs Object vs Number.mp446.68MB
152. 19 Working with Arrays/162 Basic Slicing in NumPy.mp452.24MB
153. 19 Working with Arrays/163 Stepwise Slicing in NumPy.mp428.32MB
154. 19 Working with Arrays/164 Conditional Slicing in NumPy.mp427.73MB
155. 19 Working with Arrays/165 Dimensions and the Squeeze Function.mp433.78MB
156. 20 Generating Data with NumPy/167 Arrays of 0s and 1s.mp427.47MB
157. 20 Generating Data with NumPy/168 __like_ functions in NumPy.mp417.41MB
158. 20 Generating Data with NumPy/169 A Non-Random Sequence of Numbers.mp425.6MB
159. 20 Generating Data with NumPy/170 Random Generators and Seeds.mp435.36MB
160. 20 Generating Data with NumPy/171 Basic Random Functions in NumPy.mp426.01MB
161. 20 Generating Data with NumPy/172 Probability Distributions in NumPy.mp436.32MB
162. 20 Generating Data with NumPy/173 Applications of Random Data in NumPy.mp433.35MB
163. 21 Statistics with NumPy/175 Using Statistical Functions in NumPy.mp444.04MB
164. 21 Statistics with NumPy/176 Minimal and Maximal Values in NumPy.mp436.12MB
165. 21 Statistics with NumPy/177 Statistical Order Functions in NumPy.mp435.54MB
166. 21 Statistics with NumPy/178 Averages and Variance in NumPy.mp425.31MB
167. 21 Statistics with NumPy/179 Covariance and Correlation in NumPy.mp420.33MB
168. 21 Statistics with NumPy/180 Histograms in NumPy (Part 1).mp443.67MB
169. 21 Statistics with NumPy/181 Histograms in NumPy (Part 2).mp424.21MB
170. 21 Statistics with NumPy/182 NAN Equivalent Functions in NumPy.mp419.42MB
171. 22 NumPy - Preprocessing/184 Checking for Missing Values in Ndarrays.mp451.94MB
172. 22 NumPy - Preprocessing/185 Substituting Missing Values in Ndarrays.mp442.57MB
173. 22 NumPy - Preprocessing/186 Reshaping Ndarrays.mp445.08MB
174. 22 NumPy - Preprocessing/187 Removing Values from Ndarrays.mp425.29MB
175. 22 NumPy - Preprocessing/188 Sorting Ndarrays.mp459.54MB
176. 22 NumPy - Preprocessing/189 Argument Sort in NumPy.mp438.36MB
177. 22 NumPy - Preprocessing/190 Argument Where in NumPy.mp466.26MB
178. 22 NumPy - Preprocessing/191 Shuffling Ndarrays.mp442.56MB
179. 22 NumPy - Preprocessing/192 Casting Ndarrays.mp445.61MB
180. 22 NumPy - Preprocessing/193 Striping Values from Ndarrays.mp436.62MB
181. 22 NumPy - Preprocessing/194 Stacking Ndarrays.mp474.54MB
182. 22 NumPy - Preprocessing/195 Concatenating Ndarrays.mp447.82MB
183. 22 NumPy - Preprocessing/196 Finding Unique Values in Ndarrays.mp435.53MB
184. 23 A Loan Data Example with NumPy/197 Setting Up_ Introduction to the Practical Example.mp452.12MB
185. 23 A Loan Data Example with NumPy/198 Setting Up_ Importing the Data Set.mp437.38MB
186. 23 A Loan Data Example with NumPy/199 Setting Up_ Checking for Incomplete Data.mp430.3MB
187. 23 A Loan Data Example with NumPy/200 Setting Up_ Splitting the Dataset.mp433.49MB
188. 23 A Loan Data Example with NumPy/201 Setting Up_ Creating Checkpoints.mp420.07MB
189. 23 A Loan Data Example with NumPy/202 Manipulating Text Data_ Issue Date.mp426.36MB
190. 23 A Loan Data Example with NumPy/203 Manipulating Text Data_ Loan Status and Term.mp440.35MB
191. 23 A Loan Data Example with NumPy/204 Manipulating Text Data_ Grade and Sub Grade.mp451.47MB
192. 23 A Loan Data Example with NumPy/205 Manipulating Text Data_ Verification Status & URL.mp432.68MB
193. 23 A Loan Data Example with NumPy/206 Manipulating Text Data_ State Address.mp449.57MB
194. 23 A Loan Data Example with NumPy/207 Manipulating Text Data_ Converting Strings and Creating a Checkpoint.mp420.4MB
195. 23 A Loan Data Example with NumPy/208 Manipulating Numeric Data_ Substitute Filler Values.mp446.34MB
196. 23 A Loan Data Example with NumPy/209 Manipulating Numeric Data_ Currency Change – The Exchange Rate.mp435.75MB
197. 23 A Loan Data Example with NumPy/210 Manipulating Numeric Data_ Currency Change - From USD to EUR.mp452.68MB
198. 23 A Loan Data Example with NumPy/211 Completing the Dataset.mp446.45MB
199. 24 The _Absenteeism_ Exercise - Introduction/212 An Introduction to the _Absenteeism_ Exercise.mp49.68MB
200. 24 The _Absenteeism_ Exercise - Introduction/213 The _Absenteeism_ Exercise from a Business Perspective.mp419.77MB
201. 24 The _Absenteeism_ Exercise - Introduction/214 The Dataset.mp411.95MB
202. 25 Solution to the _Absenteeism_ Exercise/215 How to Complete the Absenteeism Exercise.mp418.13MB
203. 25 Solution to the _Absenteeism_ Exercise/216 Eyeball Your Data First.mp456.24MB
204. 25 Solution to the _Absenteeism_ Exercise/217 Note_ Programming vs the Rest of the World.mp425.65MB
205. 25 Solution to the _Absenteeism_ Exercise/218 Using a Statistical Approach to Solve Our Exercise.mp417.86MB
206. 25 Solution to the _Absenteeism_ Exercise/219 Dropping the 'ID' Column.mp455.13MB
207. 25 Solution to the _Absenteeism_ Exercise/220 Analysis of the 'Reason for Absence' Column.mp435.78MB
208. 25 Solution to the _Absenteeism_ Exercise/221 Splitting the Reasons for Absence into Multiple Dummy Variables.mp472.82MB
209. 25 Solution to the _Absenteeism_ Exercise/222 Working with Dummy Variables - A Statistical Perspective.mp412.05MB
210. 25 Solution to the _Absenteeism_ Exercise/223 Grouping the Reason for Absence Columns.mp466MB
211. 25 Solution to the _Absenteeism_ Exercise/224 Concatenating Columns in a pandas DataFrame.mp434.2MB
212. 25 Solution to the _Absenteeism_ Exercise/225 Reordering Columns in a DataFrame.mp412.38MB
213. 25 Solution to the _Absenteeism_ Exercise/226 Working on the 'Date' Column.mp450.22MB
214. 25 Solution to the _Absenteeism_ Exercise/227 Extracting the Month Value from the 'Date' Column.mp441.91MB
215. 25 Solution to the _Absenteeism_ Exercise/228 Creating the 'Day of the Week' Column.mp424.9MB
216. 25 Solution to the _Absenteeism_ Exercise/229 Understanding the Meaning of 5 More Columns.mp425.9MB
217. 25 Solution to the _Absenteeism_ Exercise/230 Modifying the 'Education' Column.mp434.53MB
218. 25 Solution to the _Absenteeism_ Exercise/231 Final Remarks on the Absenteeism Exercise.mp417.85MB
219. 26 Data Visualization/232 What Is Data Visualization and Why Is It Important_.mp435.4MB
220. 26 Data Visualization/233 Why Learn Data Visualization_.mp469.71MB
221. 26 Data Visualization/234 Choosing the Right Visualization – What Are Some Popular Approaches and Framewor.mp466.2MB
222. 26 Data Visualization/235 Introduction into Colors and Color Theory.mp485.1MB
223. 26 Data Visualization/236 Bar Chart - Introduction - General Theory and Getting to Know the Dataset.mp417.37MB
224. 26 Data Visualization/237 Bar Chart - How to Create a Bar Chart Using Python.mp470MB
225. 26 Data Visualization/238 Bar Chart – Interpreting the Bar Graph. How to Make a Good Bar Graph.mp422.18MB
226. 26 Data Visualization/239 Pie Chart - Introduction - General Theory and Dataset.mp433.05MB
227. 26 Data Visualization/240 Pie Chart - How to Create a Pie Chart Using Python.mp435.48MB
228. 26 Data Visualization/241 Pie Chart – Interpreting the Pie Chart.mp415.35MB
229. 26 Data Visualization/242 Pie Chart - Why You Should Never Create a Pie Graph.mp468.97MB
230. 26 Data Visualization/243 Stacked Area Chart - Introduction - General Theory. Getting to Know the Dataset.mp424.36MB
231. 26 Data Visualization/244 Stacked Area Chart - How to Create a Stacked Area Chart Using Python.mp449.78MB
232. 26 Data Visualization/245 Stacked Area Chart - Interpreting the Stacked Area Graph.mp422.75MB
233. 26 Data Visualization/246 Stacked Area Chart - How to Make a Good Stacked Area Chart.mp434.73MB
234. 26 Data Visualization/247 Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp417.11MB
235. 26 Data Visualization/248 Line Chart - How to Create a Line Chart in Python.mp452.25MB
236. 26 Data Visualization/249 Line Chart - Interpretation.mp433.21MB
237. 26 Data Visualization/250 Line Chart - How to Make a Good Line Chart.mp463.37MB
238. 26 Data Visualization/251 Histogram - Introduction - General Theory. Getting to Know the Dataset.mp429.46MB
239. 26 Data Visualization/252 Histogram - How to Create a Histogram Using Python.mp428.15MB
240. 26 Data Visualization/253 Histogram – Interpreting the Histogram.mp416.23MB
241. 26 Data Visualization/254 Histogram – Choosing the Number of Bins in a Histogram.mp443.93MB
242. 26 Data Visualization/255 Histogram - How to Make a Good Histogram.mp430.65MB
243. 26 Data Visualization/256 Scatter Plot - Introduction - General Theory. Getting to Know the Dataset.mp420.39MB
244. 26 Data Visualization/257 Scatter Plot - How to Create a Scatter Plot Using Python.mp453.48MB
245. 26 Data Visualization/258 Scatter Plot – Interpreting the Scatter Plot.mp422.76MB
246. 26 Data Visualization/259 Scatter Plot - How to Make a Good Scatter Plot.mp427.85MB
247. 26 Data Visualization/260 Regression Plot - Introduction - General Theory. Getting to Know the Dataset.mp424.38MB
248. 26 Data Visualization/261 Regression Plot - How to Create a Regression Scatter Plot Using Python.mp450.19MB
249. 26 Data Visualization/262 Regression Plot – Interpreting the Regression Scatter Plot.mp437.17MB
250. 26 Data Visualization/263 Regression Plot - How to Make a Good Regression Plot.mp429.58MB
251. 26 Data Visualization/264 Bar and Line Chart - Introduction - General Theory. Getting to Know the Dataset.mp426.41MB
252. 26 Data Visualization/265 Bar and Line Chart - How to Create a Combination Bar and Line Graph Using Python.mp445.66MB
253. 26 Data Visualization/266 Bar and Line Chart – Interpreting the Combination Bar and Line Graph.mp422.81MB
254. 26 Data Visualization/267 Bar and Line Chart – How to Make a Good Bar and Line Graph.mp438.18MB
255. 27 Conclusion/269 Conclusion.mp424.52MB