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  • pdf文档 pandas: powerful Python data analysis toolkit - 0.21.1

    Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.5 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.5 Documentation Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.2.7 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.2 2017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 1.3.1 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 1.3
    0 码力 | 2207 页 | 8.59 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.20.3

    2017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1.1 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1.1 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.3 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2.3 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 1.3.7 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 1.3
    0 码力 | 2045 页 | 9.18 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.20.2

    Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.3 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.3 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 1.2.7 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 1.2 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 1.3.3 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 1.4
    0 码力 | 1907 页 | 7.83 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.19.1

    Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1.2 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 v0 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 1.2.6 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 1.3 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 1.3.5 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 1.4
    0 码力 | 1943 页 | 12.06 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.19.0

    Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 1.1.6 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 1.2 Performance Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 1.2.5 Bug Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 1.3 Signature change for .rank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Bug in QuarterBegin with n=0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Resample
    0 码力 | 1937 页 | 12.03 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.12

    release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes similary to float dtypes to return np.nan or np.inf as appropriate (GH3590). This correct a numpy bug that treats integer and float dtypes differently. In [1]: p = DataFrame({ ’first’ : [4,5,8], ’second’ 10 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.12.0 1.1.5 Bug Fixes • Plotting functions now raise a TypeError before trying to plot anything if the associated objects
    0 码力 | 657 页 | 3.58 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.17.0

    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 3.2 Bug Reports/Enhancement Requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Warning: pandas >= 0.17.0 will no longer Changes – Deprecations – Removal of prior version deprecations/changes • Performance Improvements • Bug Fixes 1.1.1 New features Datetime with TZ We are adding an implementation that natively supports datetime
    0 码力 | 1787 页 | 10.76 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.15

    v0.15.2 (December 12, 2014) This is a minor release from 0.15.1 and includes a large number of bug fixes along with several new features, enhance- ments, and performance improvements. A small number of all users upgrade to this version. • Enhancements • API Changes • Performance Improvements • Bug Fixes 1.1.1 API changes • Indexing in MultiIndex beyond lex-sort depth is now supported, though a lexically df2.index.lexsort_depth Out[7]: 2 In [8]: df2.loc[(1,’z’)] Out[8]: jolie jim joe 1 z 0.571981 • Bug in unique of Series with category dtype, which returned all categories regardless whether they were
    0 码力 | 1579 页 | 9.15 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 1.0.0

    resample("2D").agg(lambda x: 'a').A.dtype Out[50]: dtype('O') This fixes an inconsistency between resample and groupby. This also fixes a potential bug, where the values of the result might change depending on Release 1.0.0 1.9 Bug fixes 1.9.1 Categorical • Added test to assert the fillna() raises the correct ValueError message when the value isn’t a value from categories (GH13628) • Bug in Categorical.astype() wouldn’t fail if the source contained duplicates (GH28107) • Bug in Categorical.astype() not allowing for casting to extension dtypes (GH28668) • Bug where merge() was unable to join on categorical and extension
    0 码力 | 3015 页 | 10.78 MB | 1 年前
    3
  • pdf文档 pandas: powerful Python data analysis toolkit - 0.15.1

    is a minor bug-fix release from 0.15.0 and includes a small number of API changes, several new features, en- hancements, and performance improvements along with a large number of bug fixes. We recommend recommend that all users upgrade to this version. • Enhancements • API Changes • Bug Fixes 1.1.1 API changes • s.dt.hour and other .dt accessors will now return np.nan for missing values (rather than previously null-counts (GH8701) 1.1.3 Bug Fixes • Bug in unpickling of a CustomBusinessDay object (GH8591) • Bug in coercing Categorical to a records array, e.g. df.to_records() (GH8626) • Bug in Categorical not created
    0 码力 | 1557 页 | 9.10 MB | 1 年前
    3
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