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)
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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