pandas: powerful Python data analysis toolkit - 0.15.1stacking and unstacking ..... 476 18.3 Reshaping by Melt ..... 481 18.4 Combining with stats and GroupBy ..... 482 18.5 Pivot tables and cross-tabulations ..... 483 18.6 Tiling ..... 487 18.7 Computing Panel4D 1240 32.7 Index 1286 32.8 DatetimeIndex 1315 32.9 TimedeltaIndex ..... 1344 32.10 GroupBy ..... 1364 32.11 General utility functions ..... 1388 33 Contributing to pandas ..... 1449 dtype: int64 current behavior: In [4]: s.dt.hour Out [4]: 0 0 1 0 2 NaN 3 0 4 0 dtype: float64 • groupby with as_index=False will not add erroneous extra columns to result (GH8582): In [5]: np.random.seed(2718281)0 码力 | 1557 页 | 9.10 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 0.20.3Plotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.3.5 Groupby/Resample/Rolling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.3.6 Sparse . 11 1.3.1.3 .to_datetime() has gained an origin parameter . . . . . . . . . . . . . . . 12 1.3.1.4 Groupby Enhancements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.3.1.5 Better support UInt64 Support Improved . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.3.1.8 GroupBy on Categoricals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.3.1.9 Table Schema0 码力 | 2045 页 | 9.18 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 0.21.1Plotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.1.5.5 Groupby/Resample/Rolling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.1.5.6 Reshaping 2.1.6 CategoricalDtype for specifying categoricals . . . . . . . . . . . . . . . . . 11 1.2.1.7 GroupBy objects now have a pipe method . . . . . . . . . . . . . . . . . . . . . 12 1.2.1.8 Categorical.rename_categories Plotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 1.2.7.5 Groupby/Resample/Rolling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1.2.7.6 Sparse .0 码力 | 2207 页 | 8.59 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 0.19.0symmetric_difference changes 27 Index.unique consistently returns Index 28 MultiIndex constructors, groupby and set_index preserve categorical dtypes 28 read_csv will progressively enumerate chunks 30 Bug Fixes 37 2 v0.18.1 (May 3, 2016) 42 1.2.1 New features 43 Custom Business Hour 43 .groupby(...) syntax with window and resample operations 44 Method chaining improvements 46 Partial string Enhancements 50 1.2.2 Sparse changes 51 1.2.3 API changes 52 .groupby(..).nth() changes 52 numpy function compatibility 53 Using .apply on groupby resampling 54 Changes in read_csv exceptions 55 to_datetime0 码力 | 1937 页 | 12.03 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 0.20.2Bug Fixes 4 1.1.3.1 Conversion 4 1.1.3.2 Indexing 4 1.1.3.3 I/O 4 1.1.3.4 Plotting 5 1.1.3.5 Groupby/Resample/Rolling 5 1.1.3.6 Sparse 5 1.1.3.7 Reshaping 5 1.1.3.8 Numeric 5 1.1.3.9 Categorical 2.1.4 Groupby Enhancements 10 1.2.1.5 Better support for compressed URLs in read_csv 11 1.2.1.6 Pickle file I/O now supports compression 12 1.2.1.7 UInt64 Support Improved 13 1.2.1.8 GroupBy on Categoricals 9 Memory Usage for Index is more Accurate 26 1.2.2.10 DataFrame.sort_index changes 26 1.2.2.11 Groupby Describe Formatting 28 1.2.2.12 Window Binary Corr/Cov operations return a MultiIndex DataFrame0 码力 | 1907 页 | 7.83 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 1.3.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555 2.8.4 Combining with stats and GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 2.8.5 Pivot tables . . . . . . . empties/nans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 604 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 604 2.10.6 Filling missing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1414 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415 3.3.7 Computations / descriptive0 码力 | 3605 页 | 14.68 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 1.3.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 2.8.4 Combining with stats and GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 2.8.5 Pivot tables . . . . . . . empties/nans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 2.10.6 Filling missing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1414 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415 3.3.7 Computations / descriptive0 码力 | 3603 页 | 14.65 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 1.3.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 2.8.4 Combining with stats and GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533 2.8.5 Pivot tables . . . . . . . empties/nans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 576 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577 2.10.6 Filling missing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1361 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1362 3.3.7 Computations / descriptive0 码力 | 3509 页 | 14.01 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 1.4.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555 2.8.4 Combining with stats and GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 2.8.5 Pivot tables . . . . . . . empties/nans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605 2.10.6 Filling missing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1449 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1450 3.3.7 Computations / descriptive0 码力 | 3743 页 | 15.26 MB | 2 年前3
pandas: powerful Python data analysis toolkit - 1.1.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 2.8.4 Combining with stats and GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 2.8.5 Pivot tables . . . . . . . empties/nans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526 2.10.5 NA values in GroupBy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 2.10.6 Filling missing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1252 3.3.6 Function application, GroupBy & window . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 3.3.7 Computations / descriptive0 码力 | 3231 页 | 10.87 MB | 2 年前3
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