pandas: powerful Python data analysis toolkit - 0.12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 2.7 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3 Frequently Improved network test decorator to catch IOError (and therefore URLError as well). Added with_connectivity_check decorator to allow explicitly checking a website as a proxy for seeing if there is network connectivity leading to a connection reset issue (GH3982, GH3985, GH4028, GH4054) • Fixed failing tests in test_yahoo, test_google where symbols were not retrieved but were being accessed (GH3982, GH3985, GH4028, GH4054)0 码力 | 657 页 | 3.58 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.5.0rc0function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2954 3.16.4 Test suite runner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2954 . . . . . . . . . . . . . 2990 4.4.7 Test-driven development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2991 4.4.8 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2997 4.4.9 Running the performance test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2998 4.4.10 Documenting your code . . . . . .0 码力 | 3943 页 | 15.73 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.13.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 2.7 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 3 Frequently Format Changes. A much more string-like query format is now supported. See the docs. In [39]: path = ’test.h5’ In [40]: dfq = DataFrame(randn(10,4), ....: columns=list(’ABCD’), ....: index=date_range(’20130101’ format. This default format can be set as an option by setting io.hdf.default_format. In [44]: path = ’test.h5’ In [45]: df = DataFrame(randn(10,2)) In [46]: df.to_hdf(path,’df_table’,format=’table’) 180 码力 | 1219 页 | 4.81 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.14.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 2.7 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 3 Frequently the rest of pandas (GH5129). • Bug in read_html tests where redirected invalid URLs would make one test fail (GH6445). • Bug in multi-axis indexing using .loc on non-unique indices (GH6504) • Bug that Format Changes. A much more string-like query format is now supported. See the docs. In [39]: path = ’test.h5’ In [40]: dfq = DataFrame(randn(10,4), ....: columns=list(’ABCD’), ....: index=date_range(’20130101’0 码力 | 1349 页 | 7.67 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.17.0col1 foo bar col2 a b a b i1 i2 j l 1 2 3 4 k 5 6 7 8 In [33]: df.to_excel('test.xlsx') In [34]: df = pd.read_excel('test.xlsx', header=[0,1], index_col=[0,1]) In [35]: df Out[35]: col1 foo bar col2 ValueError (GH10505) • Bug in groupby(axis=1) with filter() throws IndexError (GH11041) • Bug in test_categorical on big-endian builds (GH10425) • Bug in Series.shift and DataFrame.shift not supporting the group name (GH7313). • Bug in isnull() when mode.use_inf_as_null == True where isnull wouldn’t test True when it encountered an inf/-inf (GH7315). • Bug in inferred_freq results in None for eastern0 码力 | 1787 页 | 10.76 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.21.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.2.6 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.3 Dependencies With Continuous Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 3.5.3 Test-driven development/code writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 3.5 . . . . . . . 416 3.5.4 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 3.5.5 Running the performance test suite . . . . . . . . . . . . . . .0 码力 | 2207 页 | 8.59 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15the group name (GH7313). • Bug in isnull() when mode.use_inf_as_null == True where isnull wouldn’t test True when it encountered an inf/-inf (GH7315). • Bug in inferred_freq results in None for eastern the rest of pandas (GH5129). • Bug in read_html tests where redirected invalid URLs would make one test fail (GH6445). • Bug in multi-axis indexing using .loc on non-unique indices (GH6504) • Bug that Format Changes. A much more string-like query format is now supported. See the docs. In [39]: path = ’test.h5’ In [40]: dfq = DataFrame(randn(10,4), ....: columns=list(’ABCD’), ....: index=date_range(’20130101’0 码力 | 1579 页 | 9.15 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15.1the group name (GH7313). • Bug in isnull() when mode.use_inf_as_null == True where isnull wouldn’t test True when it encountered an inf/-inf (GH7315). • Bug in inferred_freq results in None for eastern the rest of pandas (GH5129). • Bug in read_html tests where redirected invalid URLs would make one test fail (GH6445). • Bug in multi-axis indexing using .loc on non-unique indices (GH6504) • Bug that Format Changes. A much more string-like query format is now supported. See the docs. In [39]: path = ’test.h5’ In [40]: dfq = DataFrame(randn(10,4), ....: columns=list(’ABCD’), ....: index=date_range(’20130101’0 码力 | 1557 页 | 9.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 2.2.6 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 2.3 Dependencies With Continuous Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 3.5.3 Test-driven development/code writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 3.5 . . . . . 388 3.5.4 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 viii 3.5.5 Running the performance test suite . . . . . . . . . . . . . .0 码力 | 2045 页 | 9.18 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 2.2.6 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 2.3 Dependencies With Continuous Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 3.5.3 Test-driven development/code writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 3.5 . . . . . . . 386 3.5.4 Running the test suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387 3.5.5 Running the performance test suite . . . . . . . . . . . . . . .0 码力 | 1907 页 | 7.83 MB | 1 年前3
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