14.51 GB | 00:14:12 | mp4 | 1920X1080  | 16:9
Genre:eLearning |Language:English

Files Included :
1 - Course Structure  (21.94 MB)
2 - Pandas Is Not Single  (27.23 MB)
3 - Anaconda  (31.44 MB)
4 - Jupyter Notebooks  (68.05 MB)
5 - Cloud vs Local  (39.07 MB)
6 - Hello Python  (48.25 MB)
7 - NumPy  (70.33 MB)
8 - all-notebooks  (1005.95 KB)
8 - slides  (2.53 MB)
230 - Section Intro  (37.9 MB)
231 - The Python datetime Module  (59.26 MB)
232 - Parsing Dates From Text  (78.84 MB)
233 - Even Better dateutil  (36.99 MB)
234 - From Datetime To String  (33.34 MB)
235 - Performant Datetimes With Numpy  (54.01 MB)
236 - The Pandas Timestamp  (36.04 MB)
237 - Our Dataset Brent Prices  (43.41 MB)
238 - Date Parsing And DatetimeIndex  (37.4 MB)
239 - A Cool Shorcut readcsv With parsedates  (27.34 MB)
240 - Indexing Dates  (39.65 MB)
241 - Skill Challenge  (5.66 MB)
242 - Solution  (25.39 MB)
243 - DateTimeIndex Attribute Accessors  (58.09 MB)
244 - Creating Date Ranges  (57.13 MB)
245 - Shifting Dates With pdDateOffset  (54.45 MB)
246 - BONUS Timedeltas And Absolute Time  (43.55 MB)
247 - Resampling Timeseries  (55.46 MB)
248 - Upsampling And Interpolation  (74.86 MB)
249 - What About asfreq  (54.17 MB)
250 - BONUS Rolling Windows  (63.86 MB)
251 - Skill Challenge  (6.85 MB)
252 - Solution  (33.9 MB)
253 - Handling-Time-And-Date ipynb  (104.69 KB)
254 - Section Intro  (23.63 MB)
255 - Our Data Boston Marathon Runners  (36.02 MB)
256 - String Methods In Python  (42.33 MB)
257 - Vectorized String Operations In Pandas  (28.46 MB)
258 - Case Operations  (20.99 MB)
259 - Finding Characters And Words  (37.41 MB)
260 - Strips And Whitespace  (48.04 MB)
261 - String Splitting And Concatenation  (70.25 MB)
262 - More Split Parameters  (61.45 MB)
263 - Skill Challenge  (4.62 MB)
264 - Solution  (34.24 MB)
265 - Slicing Substrings  (36.44 MB)
266 - Masking With String Methods  (56.74 MB)
267 - BONUS Parsing Indicators With getdummies  (102.94 MB)
268 - Text Replacement  (64.46 MB)
269 - Introduction To Regular Expressions  (117.87 MB)
270 - More Regex Concepts  (103.1 MB)
271 - How To Approach Regex  (99.04 MB)
272 - Is This A Valid Email  (121.91 MB)
273 - BONUS Whats The Point Of recompile  (29.74 MB)
274 - Pandas str contains split And replace With Regex  (117.94 MB)
275 - Skill Challenge  (7.92 MB)
276 - Solution  (111.36 MB)
277 - Regex-And-Text-Manipulation ipynb  (29.78 KB)
278 - Section Intro  (5.18 MB)
279 - The Art Of Data Visualization  (19.58 MB)
280 - The Preliminaries Of matplotlib  (93.68 MB)
281 - Line Graphs  (80.87 MB)
282 - Bar Charts  (72.37 MB)
283 - Pie Plots  (82.42 MB)
284 - Histograms  (64.56 MB)
285 - Scatter Plots  (95.52 MB)
286 - Other Visualization Options  (103.29 MB)
287 - BONUS Data Ink And Chartjunk  (48.61 MB)
288 - Skill Challenge  (11.45 MB)
289 - Solution  (63.24 MB)
290 - Visualizing-Data ipynb  (500.75 KB)
291 - Section Intro  (2.73 MB)
292 - Reading JSON  (22.65 MB)
293 - Reading HTML  (146.26 MB)
294 - Reading Excel  (83.37 MB)
295 - Creating Output The to Family Of Methods  (111.5 MB)
296 - BONUS Introduction To Pickling  (46.94 MB)
297 - Pickles In Pandas  (33.69 MB)
297 - portfolio  (1.42 KB)
298 - The Many Other Formats  (42.11 MB)
299 - Skill Challenge  (17.82 MB)
300 - Solution  (70.21 MB)
301 - Data-Formats-And-I-O ipynb  (23.64 KB)
302 - Section Intro  (13.18 MB)
303 - Data Types  (14.59 MB)
304 - Variables  (57.62 MB)
305 - Arithmetic And Augmented Assignment Operators  (38.65 MB)
306 - Ints And Floats  (64.15 MB)
307 - Booleans And Comparison Operators  (31.27 MB)
308 - Strings  (46.23 MB)
309 - Methods  (35.7 MB)
310 - Containers I Lists  (43.62 MB)
311 - Lists vs Strings  (39.01 MB)
312 - List Methods And Functions  (47.21 MB)
313 - Containers II Tuples  (29.17 MB)
314 - Containers III Sets  (77.36 MB)
315 - Containers IV Dictionaries  (33.66 MB)
316 - Dictionary Keys And Values  (53.55 MB)
317 - Membership Operators  (28.06 MB)
318 - Controlling Flow if else And elif  (62.63 MB)
319 - Truth Value Of Nonbooleans  (23.54 MB)
320 - For Loops  (30.21 MB)
321 - The range Immutable Sequence  (35.75 MB)
322 - While Loops  (43.94 MB)
323 - Break And Continue  (28.72 MB)
324 - Zipping Iterables  (25.63 MB)
325 - List Comprehensions  (46.66 MB)
326 - Defining Functions  (86.94 MB)
327 - Function Arguments Positional vs Keyword  (46.54 MB)
328 - Lambdas  (33.95 MB)
329 - Importing Modules  (50.62 MB)
330 - Appendix-A-Rapid-Fire-Python-Fundamentals ipynb  (25.62 KB)
331 - Installing Anaconda And Python Windows  (101.47 MB)
332 - Installing Anaconda And Python Mac  (26.22 MB)
333 - Installing Anaconda And Python Linux  (38.36 MB)
10 - What Is A Series  (17.06 MB)
11 - Parameters vs Arguments  (10.75 MB)
12 - Whats In The Data  (29.64 MB)
13 - The dtype Attribute  (9.1 MB)
14 - BONUS What Is dtypeo Really  (14.34 MB)
15 - Index And RangeIndex  (50.1 MB)
16 - Series And Index Names  (28.16 MB)
17 - Skill Challenge  (11.85 MB)
18 - Solution  (36.39 MB)
19 - Another Solution  (16.64 MB)
20 - The head And tail Methods  (33.85 MB)
21 - Extracting By Index Position  (42.03 MB)
22 - Accessing Elements By Label  (40.11 MB)
23 - BONUS The addprefix And addsuffix Methods  (24.66 MB)
24 - Using Dot Notation  (19.18 MB)
25 - Boolean Masks And The loc Indexer  (42.88 MB)
26 - Extracting By Position With iloc  (16.55 MB)
27 - BONUS Using Callables With loc And iloc  (53.63 MB)
28 - Selecting With get  (47.11 MB)
29 - Selection Recap  (40.98 MB)
30 - Skill Challenge  (9.68 MB)
31 - Solution  (34.84 MB)
32 - Series-At-Glance  (13.61 KB)
9 - Section Intro  (10.42 MB)
33 - Section Intro  (18.95 MB)
34 - Reading In Data With readcsv  (80.27 MB)
35 - Series Sizing With size shape And len  (34.85 MB)
36 - Unique Values And Series Monotonicity  (25.86 MB)
37 - The count Method  (8.4 MB)
38 - Accessing And Counting NAs  (54.16 MB)
39 - BONUS Another Approach  (30.68 MB)
40 - The Other Side notnull And notna  (16.49 MB)
41 - BONUS Booleans Are Literally Numbers In Python  (16.58 MB)
42 - Skill Challenge  (5.98 MB)
43 - Solution  (20.31 MB)
44 - Dropping And Filling NAs  (32.17 MB)
45 - Descriptive Statistics  (46.64 MB)
46 - The describe Method  (14.77 MB)
47 - mode And valuecounts  (43.77 MB)
48 - idxmax And idxmin  (32.37 MB)
49 - Sorting With sortvalues  (29.15 MB)
50 - nlargest And nsmallest  (17.53 MB)
51 - Sorting With sortindex  (22.25 MB)
52 - Skill Challenge  (4.57 MB)
53 - Solution  (14.91 MB)
54 - Series Arithmetics And fillvalue  (61.64 MB)
55 - BONUS Calculating Variance And Standard Deviation  (25.04 MB)
56 - Cumulative Operations  (26.59 MB)
57 - Pairwise Differences With diff  (18.47 MB)
58 - Series Iteration  (23.95 MB)
59 - Filtering filter where And mask  (82.76 MB)
60 - Transforming With update apply And map  (105.75 MB)
61 - Skill Challenge  (15.66 MB)
62 - Solution I Reading Data  (22.73 MB)
63 - Solution II Mean Median And Standard Deviation  (30.35 MB)
64 - Solution III Zscores  (73.57 MB)
65 - Series-Methods-And-Handling  (31.84 KB)
100 - Another Skill Challenge  (10.36 MB)
101 - Solution  (56.37 MB)
102 - Working-With-DataFrames  (105.51 KB)
66 - Section Intro  (14.5 MB)
67 - What Is A DataFrame  (67.99 MB)
68 - Creating A DataFrame  (32.63 MB)
69 - BONUS Four More Ways To Build DataFrames  (110.36 MB)
70 - The info Method  (29.65 MB)
71 - Reading In Nutrition Data  (40.97 MB)
72 - Some Cleanup Removing The Duplicated Index  (55.16 MB)
73 - The sample Method  (34.83 MB)
74 - BONUS Sampling With Replacement Or Weights  (59.79 MB)
75 - BONUS How Are Random Numbers Generated  (67.76 MB)
76 - DataFrame Axes  (36.49 MB)
77 - Changing The Index  (79.1 MB)
78 - Extracting From DataFrames By Label  (53.51 MB)
79 - DataFrame Extraction by Position  (71.9 MB)
80 - Single Value Access With at And iat  (40.99 MB)
81 - BONUS The getloc Method  (37.58 MB)
82 - Skill Challenge  (5.89 MB)
83 - Solution  (69.39 MB)
84 - More Cleanup Going Numeric  (29.28 MB)
85 - The astype Method  (38.45 MB)
86 - DataFrame replace A Glimpse At Regex  (67.83 MB)
87 - Part I Collecting The Units  (103.39 MB)
88 - The rename Method  (40.74 MB)
89 - DataFrame dropna  (58.48 MB)
90 - BONUS dropna With Subset  (42.15 MB)
91 - Part II Merging Units With Column Names  (86.99 MB)
92 - Part III Removing Units From Values  (55.44 MB)
93 - Filtering in 2D  (63.76 MB)
94 - DataFrame Sorting  (77.58 MB)
95 - Using Series between With DataFrames  (54.78 MB)
96 - BONUS Min Max and IdxMinMax And Good Foods  (100.78 MB)
97 - DataFrame nlargest And nsmallest  (56.31 MB)
98 - Skill Challenge  (6.11 MB)
99 - Solution  (66.09 MB)
103 - Section Intro  (31.47 MB)
104 - Introducing A New Dataset  (27.8 MB)
105 - Quick Review Indexing With Boolean Masks  (35.04 MB)
106 - More Approaches To Boolean Masking  (104.98 MB)
107 - Binary Operators With Booleans  (55.73 MB)
108 - BONUS XOR and Complement Binary Ops  (72.64 MB)
109 - Combining Conditions  (70.44 MB)
110 - Conditions As Variables  (29.15 MB)
111 - Skill Challenge  (6.06 MB)
112 - Solution  (61.28 MB)
113 - 2d Indexing  (59.58 MB)
114 - Fancy Indexing With lookup  (70.23 MB)
115 - Sorting By Index Or Column  (69.56 MB)
116 - Sorting vs Reordering  (99.54 MB)
117 - BONUS Another Way  (20.11 MB)
118 - 15 BONUS Please Avoid Sorting Like This  (26.2 MB)
119 - Skill Challenge  (6.65 MB)
120 - Solution  (39.84 MB)
121 - Identifying Dupes  (92.68 MB)
122 - Removing Duplicates  (45.55 MB)
123 - Removing DataFrame Rows  (31.12 MB)
124 - BONUS Removing Columns  (24.69 MB)
125 - BONUS Another Way pop  (29.11 MB)
126 - BONUS A Sophisticated Alternative  (51.56 MB)
127 - Null Values In DataFrames  (65.46 MB)
128 - Dropping And Filling DataFrame NAs  (74.69 MB)
129 - BONUS Methods And Axes With fillna  (88.18 MB)
130 - Skill Challenge  (7.95 MB)
131 - Solution  (65.98 MB)
132 - Calculating Aggregates With agg  (55.52 MB)
133 - Sameshape Transforms  (102.21 MB)
134 - More Flexibility With apply  (89.5 MB)
135 - Elementwise Operations With applymap  (103.07 MB)
136 - Skill Challenge  (13.61 MB)
137 - Solution  (40.57 MB)
138 - Setting DataFrame Values  (67.27 MB)
139 - The SettingWithCopy Warning  (62.88 MB)
140 - View vs Copy  (73.16 MB)
141 - Adding DataFrame Columns  (55.42 MB)
142 - Adding Rows To DataFrames  (77.09 MB)
143 - BONUS How Are DataFrames Stored In Memory  (33.32 MB)
144 - Skill Challenge  (7.28 MB)
145 - Solution  (49.83 MB)
146 - DataFrames-In-Depth  (59.45 KB)
146 - Slides  (2.1 MB)
147 - Section Intro  (10.49 MB)
148 - Introducing Five New Datasets  (62.44 MB)
149 - Concatenating DataFrames  (64.5 MB)
150 - The Duplicated Index Issue  (79.42 MB)
151 - Enforcing Unique Indices  (92.01 MB)
152 - BONUS Creating Multiple Indices With concat  (43.68 MB)
153 - Column Axis Concatenation  (43.03 MB)
154 - The append Method A Special Case Of concat  (22.48 MB)
155 - Concat On Different Columns  (60.15 MB)
156 - Skill Challenge  (9.05 MB)
157 - Solution  (91.8 MB)
158 - The merge Method  (53.54 MB)
159 - The lefton And righton Params  (50.52 MB)
160 - Inner vs Outer Joins  (41.32 MB)
161 - Left vs Right Joins  (31.46 MB)
162 - OnetoOne and OnetoMany Joins  (89.97 MB)
163 - ManytoMany Joins  (85.62 MB)
164 - Merging By Index  (58.76 MB)
165 - The join Method  (36.58 MB)
166 - Skill Challenge  (5.75 MB)
167 - Solution  (71.46 MB)
168 - Working-With-Multiple-DataFrames  (27.38 KB)
169 - Section Intro  (58.47 MB)
170 - Introducing New Data  (34.14 MB)
171 - Index And RangeIndex  (42.07 MB)
172 - Creating A MultiIndex  (32.1 MB)
173 - MultiIndex From readcsv  (43.61 MB)
174 - Indexing Hierarchical DataFrames  (61.28 MB)
175 - Indexing Ranges And Slices  (91.48 MB)
176 - BONUS Use With pdIndexSlice  (25.5 MB)
177 - Cross Sections With xs  (51 MB)
178 - Skill Challenge  (5.53 MB)
179 - Solution  (68.92 MB)
180 - The Anatomy Of A MultiIndex Object  (52.94 MB)
181 - Adding Another Level  (51.84 MB)
182 - Shuffling Levels  (37.24 MB)
183 - Removing MultiIndex Levels  (58.66 MB)
184 - MultiIndex sortindex  (55.08 MB)
185 - More MultiIndex Methods  (58.81 MB)
186 - Reshaping With stack  (47.22 MB)
187 - The Flipside unstack  (70.97 MB)
188 - BONUS Creating MultiLevel Columns Manually  (91.34 MB)
189 - An Easier Way transpose  (29.36 MB)
190 - BONUS What About Panels  (43.02 MB)
191 - Skill Challenge  (12.72 MB)
192 - Solution  (76.03 MB)
193 - Going-MultiDimensional  (41.94 KB)
194 - Section Intro  (27.1 MB)
195 - New Data Game Sales  (22.13 MB)
196 - Simple Aggregations Review  (44.26 MB)
197 - Conditional Aggregates  (37.42 MB)
198 - The SplitApplyCombine Pattern  (33.47 MB)
199 - The groupby Method  (33.52 MB)
200 - The DataFrameGroupBy Object  (29.25 MB)
201 - Customizing Index To Group Mappings  (30.91 MB)
202 - BONUS Series groupby  (32.49 MB)
203 - Skill Challenge  (4.7 MB)
204 - Solution  (42.43 MB)
205 - Iterating Through Groups  (31.68 MB)
206 - Handpicking Subgroups  (35.86 MB)
207 - MultiIndex Grouping  (40.53 MB)
208 - Finetuned Aggregates  (67.87 MB)
209 - Named Aggregations  (56.98 MB)
210 - The filter Method  (40.64 MB)
211 - GroupBy Transformations  (59.27 MB)
212 - BONUS Theres Also apply  (63.26 MB)
213 - Skill Challenge  (6 MB)
214 - Solution  (37.7 MB)
215 - GroupBy-And-Aggregates ipynb  (22.42 KB)
216 - Section Intro  (38.75 MB)
217 - New Data New York City SAT Scores  (40.89 MB)
218 - Pivoting Data  (65.86 MB)
219 - Undoing Pivots  (42.97 MB)
220 - What About Aggregates  (53.89 MB)
221 - The pivottable  (52.17 MB)
222 - BONUS The Problem With Average Percentage  (55.09 MB)
223 - Replicating Pivot Tables With GroupBy  (19.07 MB)
224 - Adding Margins  (37.87 MB)
225 - MultiIndex Pivot Tables  (30.4 MB)
226 - Applying Multiple Functions  (27.97 MB)
227 - Skill Challenge  (8.47 MB)
228 - Solution  (56.77 MB)
229 - Reshaping-With-Pivots ipynb  (17.15 KB)
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