pandas: powerful Python data analysis toolkit - 0.7.1What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have python setup.py build --compiler=mingw32 python setup.py install Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in in place: python setup.py build_ext --inplace 2.6 Running the test suite pandas is equipped with an exhaustive set of unit tests covering about 97% of the codebase as of this writing. To run it on your0 码力 | 281 页 | 1.45 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.7.2What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have python setup.py build --compiler=mingw32 python setup.py install Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in in place: python setup.py build_ext --inplace 2.6 Running the test suite pandas is equipped with an exhaustive set of unit tests covering about 97% of the codebase as of this writing. To run it on your0 码力 | 283 页 | 1.45 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.7.3What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have python setup.py build --compiler=mingw32 python setup.py install Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in in place: python setup.py build_ext --inplace 2.6 Running the test suite pandas is equipped with an exhaustive set of unit tests covering about 97% of the codebase as of this writing. To run it on your0 码力 | 297 页 | 1.92 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.12What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have especially if working with large data sets. 2.5 Optional Dependencies • Cython: Only necessary to build development version. Version 0.17.1 or higher. 66 Chapter 2. Installation pandas: powerful Python about HTML parsing libraries Note: – if you’re on a system with apt-get you can do sudo apt-get build-dep python-lxml to get the necessary dependencies for installation of lxml. This will prevent further0 码力 | 657 页 | 3.58 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.25ninja: many operations are faster on pre-aligned data. Adding two unaligned DataFrames internally triggers a reindexing step. For exploratory analysis you will hardly notice the difference (because reindex names. # Build MultiIndex In [304]: idx = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('a', 2), .....: ('b', 2), ('b', 1), ('b', 1)]) .....: In [305]: idx.names = ['first', 'second'] # Build DataFrame includes information on the field names, types, and other attributes. You can use the orient table to build a JSON string with two fields, schema and data. In [267]: df = pd.DataFrame({'A': [1, 2, 3], ...0 码力 | 698 页 | 4.91 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.13.1What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have especially if working with large data sets. 2.5 Optional Dependencies • Cython: Only necessary to build development version. Version 0.17.1 or higher. 98 Chapter 2. Installation pandas: powerful Python about HTML parsing libraries Note: – if you’re on a system with apt-get you can do sudo apt-get build-dep python-lxml to get the necessary dependencies for installation of lxml. This will prevent further0 码力 | 1219 页 | 4.81 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.14.0What’s New CHAPTER TWO INSTALLATION You have the option to install an official release or to build the development version. If you choose to install from source and are running Windows, you will have especially if working with large data sets. 2.5 Optional Dependencies • Cython: Only necessary to build development version. Version 0.17.1 or higher. 126 Chapter 2. Installation pandas: powerful Python about HTML parsing libraries Note: – if you’re on a system with apt-get you can do sudo apt-get build-dep python-lxml to get the necessary dependencies for installation of lxml. This will prevent further0 码力 | 1349 页 | 7.67 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15python setup.py build --compiler=mingw32 python setup.py install Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in in place: python setup.py build_ext --inplace The most recent version of MinGW (any installer dated after 2011-08-03) has removed the ‘-mno-cygwin’ option but Distutils has not yet been updated to reflect especially if working with large data sets. 2.3.2 Optional Dependencies • Cython: Only necessary to build development version. Version 0.19.1 or higher. • SciPy: miscellaneous statistical functions • PyTables:0 码力 | 1579 页 | 9.15 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15.1python setup.py build --compiler=mingw32 python setup.py install Note that you will not be able to import pandas if you open an interpreter in the source directory unless you build the C extensions in in place: python setup.py build_ext --inplace The most recent version of MinGW (any installer dated after 2011-08-03) has removed the ‘-mno-cygwin’ option but Distutils has not yet been updated to reflect especially if working with large data sets. 2.3.2 Optional Dependencies • Cython: Only necessary to build development version. Version 0.19.1 or higher. • SciPy: miscellaneous statistical functions • PyTables:0 码力 | 1557 页 | 9.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.3pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 3.4.2 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 3.4.2.1 Requirements json_normalize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1208 34.1.5.3 pandas.io.json.build_table_schema . . . . . . . . . . . . . . . . . . . . . . . . . . 1209 34.1.6 HTML . . . . . . . sort_index() now correctly handles the inplace option (GH11402) • Incorrectly distributed .c file in the build on PyPi when reading a csv of floats and passing na_values= would show an exception (GH11374)0 码力 | 2045 页 | 9.18 MB | 1 年前3
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