python pandas 手册pandas处理参考手册，基于python3案列，本书是一本tool

文件名称: python pandas 手册

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详细说明：pandas处理参考手册，基于python3案列，本书是一本toolkit，对提高pandas技巧有相当实用性，共1579页。CONTENTS 1What’sNew 1.1v0.15.2( december12,2014). 1.2v0.15.1( November9,2014) 1.3V0.15.0( ctober18,2014). “· ..14 1.4V0.14.1(July11,2014 41 1.5V0.14.0(May3l,2014) 47 1.6V0.13.1( February3,2014). 74 1.7v0.13.0( January3,2014) 1.8V0.12.0(July24,2013). ...104 1.9V0.11.0( April22,2013) l15 1.10v0.10.1( January22,2013). 124 1.11V0.10.0( December17,2012) .130 1.12v0.9.1( ovember14,2012). 141 1.13v0.9.0( October7,2012) 145 1.14V0.8.1(July22,2012),,,,,,,,,,..,.,,,, 147 1.15v0.8.0(June29,2012 ...147 1.16v0.7.3( April12,2012 152 17v.0.7.2( March16,2012)...,, ...156 1.18V.0.7.I( February29,2012) 157 1.19V.0.7.0( February9,2012) 157 1.20V.0.6.1(D 13,2011) 1.21v.0.6.0( November25,2011).....,.,...... 163 1.22v.0.5.0( October24,2011) 165 1.23 v043 through vo.4.1(September 25-October 9, 2011) .166 2 Installation 169 2.1 Python version support .,,,,,,,..,169 2.2 Installing pandas 169 2.3 Dependencies .172 3 Frequently Asked Questions (FAQ) 175 3. 1 Data Frame memory usage 175 3.2 PeriodIndex Date Array properties and functions l78 3.3 Frequency conversion 178 3. 4 Plotting 179 3.5 Converting to and from period format l80 3.6 Treatment of missing data 180 3.7 Resampling with timestamps and periods 180 4 Package overview 4. 1 Data structures at a glance 183 4.2 Mutability and copying of data 4.3 Getting Support 4.4 Credits 4.5 Development Team .184 4.6 License 184 5 10 Minutes to pandas 187 5.1 Object Creation 187 5.2 Viewing data ..189 5.3 Selection 190 5. 4 Missing data 195 5.5 Operations 5.6Me ,,...198 5. 7 Grouping ····“· 200 5.8 Resh 5.9 Time Series 203 5.10 Cate 204 5.11 Plotting 206 5.12 Getting Data In/Out 207 5.13 Gotchas 20 6 Tutorials 2 6.1 Internal guides 211 6.2 pandas Cookbook 6.3 Lessons for New pandas Users 212 6.4 Practical data analysis with Python 212 6.5 Excel charts with pandas, vincent and xlsx writer 212 6.6 Various Tutorials 1 7 Cookbook 215 7.1 Idioms 215 7.2 Selection 218 7.3 MultiIndexing 222 7.4 Missing Data 226 7.5 Grouping 7.6 Timeseries 235 7.7 Mer 235 7.8 Plotting 236 7.9 Data In/out 237 7.10 Computation 240 7.11 Timedeltas ...241 7.12 Aliasing Axis names · 242 7.13 Creating Example Data 8 Intro to Data Structures 245 8.1S 245 8. 2 Data frame ...250 8.3 Panel 262 8.4 Panel4D(Experimental 266 8.5 PaneIND(Experimental) 268 9 Essential Basic Functionality 271 9.1 Head and Tail 271 9.2 Attributes and the raw ndarray(s 272 9.3Ac 273 9.4 Flexible binary operations 273 9.5 Descriptive statistics 279 9.6 Function 287 9.7 Reindexing and altering labels 292 9.8 Iterati 299 9.9 Vectorized string method ......303 9.10 Sorting by index and value 304 9.11 Copying 7 9.12 dty 307 9. 13 Selecting columns based on dtype .313 10 Working with Text Data 317 10.1 Splitting and Replacing Strings 318 10.2 Indexing with, str ····“· 319 10.3 Extracting suhstrings 320 10.4 Method Summary 11 Options and Settings 325 11.1O 325 11. 2 Getting and Setting options .326 11.3 Setting Startup Options in python/ipython Environment 327 11. 4 Frequently Used options ..327 11.5 List of options 11.6 Number Formatting .........,.... 12 Indexing and Selecting Data 335 12.1 Different Choices for Indexing 335 12.2 Deprecations 12. 3 Basics 336 12 4 Attribute access 338 12.5 Slicing ranges 340 12.6 Selection By Label............ 341 12.7 Selection By Positi 343 12.8 Setting With Enlargement 347 12.9 Fast scalar value getting and setting 348 12.10 Boolean indexing 349 12.11 Indexing with isin 350 12. 12 The where() Method and Masking 12.13 The query() Method(Experimental) .,,355 12 14 Duplicate Data 366 12.15 Dictionary-like get () method ...367 12.16 The select() Method · 12. 17 The lookup()Method 367 12. 18 Index objects 368 12.19 Set/ Reset Index 370 12.20 Returning a view versus a copy 372 13 MultiIndex Advanced Indexing 377 13. 1 Hierarchical indexing(MultiIndex) 377 13.2 Advanced indexing with hierarchical index 382 13. 3 The need for sortedness with MultiIndex 13. 4 Take methods ..393 13.5 Float64Index 395 14 Computational tools 399 14.1 Statistical functions .399 14.2 Moving(rolling) statistics /moments 403 14.3 Expanding window moment functions 410 14.4 Exponentially weighted moment functions .412 15 Working with missing dat 415 15.1 Missing data basics 15 15.2 Datetime ,,,,,,,417 15.3 Inserting missing data :.· 417 15. 4 Calculations with missing data 418 15.5 Cleaning/ filling missing data 419 15.6 Missing data casting rules and indexing 432 16 Group By: split-apply-combine 435 16. 1 Splitting an object into groups 436 16.2 Iterating th 440 16.3 Selecting a group 441 16.4 Aggregation .,.441 16.5 Transformation 445 16.6 Filtration 449 16. 7 Dispatching to instance method .450 16.8 Flexible apply 451 16.9 Other useful features ..453 16. 10 Examples 17 Merge, join, and concatenate 46 17.1 Concatenating objects 463 17.2 Database-style Data Frame joining/merging ...472 17.3 Merging with Multi-indexes 481 18 Reshaping and Pivot Tables 485 18.1 Reshaping by pivoting Data Frame objects ..485 18.2 Reshaping by stacking and unstacking 486 18.3 Reshaping by Melt 491 18.4 Combining with stats and GroupBy .492 18. 5 Pivot tables and cross-tabulations 493 18.6 Tiling 497 18.7 Computing indicator /dummy variables 497 18.8 Factorizing values .500 19 Time Series/ Date functionality 501 19.1 Time Stamps vs. Time Spans 19.2 Converting to Timestamps 503 19.3 Generating Ranges of Timestamps 504 19.4 atetimelndex 506 19.5 DateOffset objects ... 512 19.6 Time series-related instance methods 521 19.7 Up-and downsampling 19.8 Time Span representation 19.9 Converting between Representations 530 19.10 Representing out-of-bounds spans · 19.11 Time Zone handling 532 20 Time Deltas 539 20.1 Parsing 539 20.2 Operations .541 20.3 Reductions 544 20.4 Frequency Conversion 545 20.5 Attribu 546 20.6 TimedeltaIndex .548 20.7 Resampling 550 21 Categorical Data 551 21.1 Object Creation 551 21.2 Description 21. 3 Working with categorie 21. 4 Sorting and order 21.5 Comparisons 560 21.6 Operations 562 21.7 Data munging· ····“· 21.8 Getting Data In/Out 567 21.9 Missing data 568 21.10 Gotchas 569 22 Plotting 575 22.1 Basic Plotting: plot 575 22.2 Other plots ...578 22.3 Plotting with Missing Data 609 2. 4 Plotting tools 610 22.6 Plotting directly with matplotlib 22.5 Plot formatting .618 .641 22.7 Trellis plotting interface 642 23 IO Tools(Text, CSV, HDF5,.) 65 23.1 Csv Text files .652 23.2 JSON .675 23.3 HTML 683 23. 4 Excel files 691 23.5 Clipboard 23.6 Pickling ...694 23.7 msgpack(experimental) ..695 23. 8 HDF5(Py Tables .697 23.9 SQL Queries 722 23 10 Google Big Query (Experimental) 730 23.11 Stata Format 731 23. 12 Performance Considerations .733 24 Remote data access 737 24.1 Yahoo! finance 737 24.2 Yahoo! Finance Options 38 24. 3 Google Fi 244 FRED 740 24.5 Fama/French 741 24.6 World Bank .741 24.7 Google Analytics ..,,,,,,,.,,,,,,.,,,743 25 Enhancing performance 745 25.1 Cython(Writing C extensions for pandas) 745 25.2 Expression Evaluation via eval()(Experimental 749 26 Sparse data structures 757 26.1 SparseR 759 26.2 Sparselist 26.3 Sparselndex objects 760 27 Caveats and Gotchas 761 27.1 USing If/Truth Statements with pandas 761 27.2 NaN, Integer NA values and NA type promotions .762 27.3 Integer indexing 764 27. 4 Label-based slicing conventions ..764 27.5 Miscellaneous indexing gotchas·.·,: .765 27.6 Timestamp lin 76 27.7 Parsing Dates from Text Files 767 27.8 Differences with nump 768 27.9 Thread-safe 768 27.10 HTML Table p 768 27.11 Byte-Ordering Issues 28 rpy2/R interface 28.1 Transferring R data sets into Python 771 28.2 Converting Data Frames into r objects 772 28.3 Calling r functions with pandas objects .772 28 4 High-level interface to R estimators 29 pandas Ecosystem 29.1 Statistics and Machine Learning 773 29.2 Visualization .773 29.3 DE 774 29.4 API ......774 29.5 Domain Specific 775 29.6 Out-of-core 775 30 Comparison with R/R libraries 30.1 Base R 777 30.2z0o 783 30.3xs 30.4 ply 30.5 reshape/ reshape .784 31 Comparison with SQL 789 31.1 SELECT 789 31. 2 WHERE 790 313 GROUP BY 792 31. 4 JOIN .794 31.5 UNION 796 31.6 UPDATE 797 31.7 DELETE...,. .797 32 API Reference 32 1 Input/oulput ...799 32.2 General functions 32. 3 Series 866 32. 4 Data frame 1017 32.5 Panel l181 32.6 Panel4D 1260 32.7 Inde 1306 32.8 Datetimelnde 1337 32.9 Timedeltalndex 1366 3210 GroupBy· ..,,1386 32 1 1 General utility functions .1410 3 Contributing to panda l471 33.1 Contributing to the documentation ..1471 34 Internals 1475 34.1 Indexing 1475 35 Release notes l477 35.1 pandas0.152 .1477 352 pandas0.15.1 .1479 35.3 pandas0.15.0 .1480 35. 4 pandas o 14.1 ..1482 35.5 pandas0.14.0 1484 356 pandas0.13.1 .1487 35.7 pandas0.13.0.. .·1490 358 pandas0.12.0 1504 35.9 pandas0.11.0,, 1511 35.10 pandas0.10.1 1517 35.1I pandas 0.10.0 1519 35.12 pandas0.9.1 1524 35.13 pandas0.9.0 1526 35.14 pandas0.8.1 .1531 35.15 pandas0.8.0 1533 35.16 pandas0.7.3 ...1538 35.17 pandas.7.2 1539 35.18 pandas0.7.1 .1541 35.19 pandas0.7.0 15 35.20 pandas0.6.1 1548 3521 pandas0.6.0 1550 3522 pandas0.5.0 1554 35.23 pandas0.4.3 1558 35.24 pandas0.4.2 1559 35.25 pandas0.4.1 ..1560 3526 pandas0.4.0 156 35.27 pandas0.3.0 1567 Python Module Index 1569

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