pandas: powerful Python data analysis toolkit - 1.0.0(see below for an overview). It is recommended to first upgrade to pandas 0.25 and to ensure your code is working without warnings, before upgrading to pandas 1.0. 1.1 New Deprecation Policy Starting way to select just text while excluding non-text, but still object-dtype columns. 3. When reading code, the contents of an object dtype array is less clear than string. In [9]: pd.Series(['abc', None using a Series or DataFrame with sparse values instead. See Migrating for help with migrating existing code. Matplotlib unit registration Previously, pandas would register converters with matplotlib as a0 码力 | 3015 页 | 10.78 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.25.1ValueError( 349 "On level {level}, code value ({code})" --> 350 " < -1".format(level=i, code=level_codes.min()) 351 ) 352 if not level.is_unique: ValueError: On level 0, code value (-2) < -1 1.2.3 Groupby evaluated the supplied function consistently twice on the first group to infer if it is safe to use a fast code path. Particularly for functions with side effects, this was an undesired behavior and may have led MultiIndex (GH24813) • Restored performance of DatetimeIndex.__iter__() by re-enabling specialized code path (GH26702) • Improved performance when building MultiIndex with at least one CategoricalIndex0 码力 | 2833 页 | 9.65 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.25.0ValueError( 349 "On level {level}, code value ({code})" --> 350 " < -1".format(level=i, code=level_codes.min()) 351 ) 352 if not level.is_unique: ValueError: On level 0, code value (-2) < -1 1.2.3 Groupby evaluated the supplied function consistently twice on the first group to infer if it is safe to use a fast code path. Particularly for functions with side effects, this was an undesired behavior and may have led MultiIndex (GH24813) • Restored performance of DatetimeIndex.__iter__() by re-enabling specialized code path (GH26702) • Improved performance when building MultiIndex with at least one CategoricalIndex0 码力 | 2827 页 | 9.62 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2329 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2329 4.1.4 Contributing documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2333 4.1.5 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2351 4.1.6 Contributing your changes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2364 4.2 pandas code style guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23670 码力 | 3091 页 | 10.16 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0.4enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2325 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2325 4.1.4 Contributing documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2329 4.1.5 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2347 4.1.6 Contributing your changes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2360 4.2 pandas code style guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23630 码力 | 3081 页 | 10.24 MB | 1 年前3
pandas: powerful Python data analysis toolkit -1.0.3enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2315 5.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2315 viii 5.1.4 Contributing documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2319 5.1.5 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2337 5.1.6 Contributing your changes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2350 5.2 pandas code style guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23530 码力 | 3071 页 | 10.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.1.1enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.4 Contributing documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2426 4.1.5 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2444 4.1.6 Contributing successful pull request . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2460 4.2 pandas code style guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24600 码力 | 3231 页 | 10.87 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.1.0enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2421 4.1.4 Contributing documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2426 4.1.5 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2444 4.1.6 Contributing successful pull request . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2460 4.2 pandas code style guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24600 码力 | 3229 页 | 10.87 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.3.3enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2692 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2693 4.1.4 Contributing . . . . . . . . . 2720 4.4 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2721 4.4.1 Code standards . . . . . . . . . . . . . . . . . . . integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2728 4.4.6 Test-driven development/code writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2728 ix 4.4.7 Running the test0 码力 | 3603 页 | 14.65 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.3.4enhancement requests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2692 4.1.3 Working with the code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2693 4.1.4 Contributing . . . . . . . . . 2720 4.4 Contributing to the code base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2721 4.4.1 Code standards . . . . . . . . . . . . . . . . . . . integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2728 4.4.6 Test-driven development/code writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2728 ix 4.4.7 Running the test0 码力 | 3605 页 | 14.68 MB | 1 年前3
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