pandas: powerful Python data analysis toolkit - 1.3.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 934 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 934 2.23.2 Numba (JIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2741 4.9 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2744 4 >= 6.0 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas (continues on next page) 8 Chapter 1. Getting0 码力 | 3603 页 | 14.65 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.3.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 896 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 897 2.23.2 Numba (JIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2662 4.9 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2664 4 >= 6.0 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas ============================= test session0 码力 | 3509 页 | 14.01 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.3.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 935 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 935 2.23.2 Numba (JIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2741 4.9 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2744 4 >= 6.0 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas (continues on next page) 8 Chapter 1. Getting0 码力 | 3605 页 | 14.68 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.2.0. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 845 2.23.2 Using Numba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2514 4.6 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2516 4 >= 5.0.1 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas ============================= test session0 码力 | 3313 页 | 10.91 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.2.3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 845 2.23.2 Using Numba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2520 4.6 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2522 4 >= 5.0.1 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas ============================= test session0 码力 | 3323 页 | 12.74 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.4.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 943 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 944 2.23.2 Numba (JIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2836 4.9 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2839 4 >= 6.0 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas (continues on next page) 8 Chapter 1. Getting0 码力 | 3743 页 | 15.26 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.4.2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 943 2.23.1 Cython (writing C extensions for pandas) . . . . . . . . . . . . . . . . . . . . . . . . . . . 944 2.23.2 Numba (JIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2834 4.9 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2837 4 >= 6.0 and Hypothesis >= 3.58, then run: >>> pd.test() running: pytest --skip-slow --skip-network C:\Users\TP\Anaconda3\envs\py36\lib\site- ˓→packages\pandas (continues on next page) 8 Chapter 1. Getting0 码力 | 3739 页 | 15.24 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.5.0rc0pandas data structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3006 4.7 Debugging C extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3007 4 orientation of the data set when writing functions; axes are considered more or less equivalent (except when C- or Fortran-contiguousness matters for performance). In pandas, the axes are intended to lend more semantic License BSD 3-Clause License Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData␣ ˓→Development Team All rights reserved. Copyright (c) 2011-2022, Open source contributors0 码力 | 3943 页 | 15.73 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.25.0column. In [12]: df = pd.DataFrame([{'var1': 'a,b,c', 'var2': 1}, ....: {'var1': 'd,e,f', 'var2': 2}]) ....: In [13]: df Out[13]: var1 var2 0 a,b,c 1 1 d,e,f 2 [2 rows x 2 columns] Creating a long In [14]: df.assign(var1=df.var1.str.split(',')).explode('var1') Out[14]: var1 var2 0 a 1 0 b 1 0 c 1 1 d 2 1 e 2 1 f 2 [6 rows x 2 columns] 1.1.7 Other enhancements • DataFrame.plot() keywords index. In [46]: s = pd.Series(list('abc'), index=ii) In [47]: s Out[47]: (0, 4] a (1, 5] b (5, 8] c Length: 3, dtype: object Selecting from a Series or DataFrame using [] (__getitem__) or loc now only0 码力 | 2827 页 | 9.62 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0.0----------------------- RuntimeError Traceback (most recent call last)c97> in ----> 1 mi.levels[0].name = "new name" /pandas/pandas/core/indexes/base.py in name(self (GH17304) pandas 0.25.x >>> df = pd.DataFrame({"int_col": [1, 2, 3], ... "text_col": ["a", "b", "c"], ... "float_col": [0.0, 0.1, 0.2]}) >>> df.info(verbose=True) bytes pandas 1.0.0 In [34]: df = pd.DataFrame({"int_col": [1, 2, 3], ....: "text_col": ["a", "b", "c"], ....: "float_col": [0.0, 0.1, 0.2]}) ....: In [35]: df.info(verbose=True) 0 码力 | 3015 页 | 10.78 MB | 1 年前3
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