{
    "info": {
        "author": "Ted Petrou",
        "author_email": "petrou.theodore@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering"
        ],
        "description": "pandas\\_lite\n============\n\nA simpler alternative to pandas\n\nMain Goals\n==========\n\n-  A very minimal set of features\n-  Be as explicit as possible\n-  There should be one-- and preferably only one --obvious way to do it.\n\nData Structures\n~~~~~~~~~~~~~~~\n\n-  Only DataFrames\n-  No Series\n\nData Types\n~~~~~~~~~~\n\n-  Only primitive types - int, float, boolean, numpy.unicode\n-  No object data types\n\nRow and Column Labels\n~~~~~~~~~~~~~~~~~~~~~\n\n-  No index, meaning no row labels\n-  No hierarchical index\n-  Column names must be strings\n-  Column names must be unique\n-  Columns stored in a numpy array\n\nSubset Selection\n~~~~~~~~~~~~~~~~\n\n-  Only one way to select data - ``[ ]``\n-  Subset selection will be explicit and necessitate both rows and\n   columns\n-  Rows will be selected only by integer location\n-  Columns will be selected by either label or integer location. Since\n   columns must be strings, this will not be amibguous\n-  Column names cannot be duplicated\n\nAll selections and operations copy\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n-  All selections and operations provide new copies of the data\n-  This will avoid any chained indexing confusion\n\nDevelopment\n~~~~~~~~~~~\n\n-  Must use type hints\n-  Must use 3.6 - fstrings\n-  Must have numpy, bottleneck, numexpr\n\nSmall feature set\n~~~~~~~~~~~~~~~~~\n\n-  Implement as few attributes and methods as possible\n-  Focus on good idiomatic cookbook examples for doing more complex\n   tasks\n\nOnly Scalar Data Types\n~~~~~~~~~~~~~~~~~~~~~~\n\nNo complex Python data types - [x] bool - always 8 bits, not-null - [x]\nint - always 64 bits, not-null - [x] float - always 64 bits, nulls\nallowed - [x] str - A python unicode object, nulls allowed - [ ]\ncategorical - [ ] datetime - [ ] timedelta\n\nAttributes to implement\n^^^^^^^^^^^^^^^^^^^^^^^\n\n-  [x] size\n-  [x] shape\n-  [x] values\n-  [x] dtypes\n\nMay not implement any of the binary operators as methods (add, sub, mul,\netc...)\n\nMethods\n^^^^^^^\n\n**Stats** - [x] abs - [x] all - [x] any - [x] argmax - [x] argmin - [x]\nclip - [ ] corr - [x] count - [ ] cov - [x] cummax - [x] cummin - [ ]\ncumprod - [x] cumsum - [ ] describe - [x] max - [x] min - [x] median -\n[x] mean - [ ] mode - [ ] nlargest - [ ] nsmallest - [ ] quantile - [ ]\nrank - [x] std - [x] sum - [x] var - [ ] unique - [ ] nunique\n\n**Selection** - [ ] drop - [ ] drop\\_duplicates - [x] head - [ ] isin -\n[ ] sample - [x] select\\_dtypes - [x] tail - [ ] where\n\n**Missing Data** - [ ] isna - [ ] dropna - [ ] fillna - [ ] interpolate\n\n**Other** - [ ] append - [ ] apply - [ ] assign - [x] astype - [ ]\ngroupby - [ ] info - [ ] melt - [ ] memory\\_usage - [ ] merge - [ ]\npivot - [ ] replace - [ ] rolling - [ ] sort\\_values\n\n**Functions** - [ ] read\\_csv - [ ] read\\_sql - [ ] concat\n\n\n",
        "description_content_type": null,
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/tdpetrou/pandas_lite",
        "keywords": "data pandas aggregation",
        "license": "BSD 3-clause",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pandas-lite",
        "package_url": "https://pypi.org/project/pandas-lite/",
        "platform": "",
        "project_url": "https://pypi.org/project/pandas-lite/",
        "project_urls": {
            "Homepage": "https://github.com/tdpetrou/pandas_lite"
        },
        "release_url": "https://pypi.org/project/pandas-lite/0.1.2/",
        "requires_dist": [
            "numpy"
        ],
        "requires_python": ">=3.6",
        "summary": "A lighter version of pandas. No Series, No hierarchical indexing, only one indexer [ ]",
        "version": "0.1.2"
    },
    "last_serial": 3478793,
    "releases": {
        "0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "b6556d2db09ec53b54ff2e52dcdbdfd4",
                    "sha256": "fb30d5b826fe5c69618e1088bfd47b88bfef8e36fe221d04020cbeaae96bc191"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1-py2.py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "b6556d2db09ec53b54ff2e52dcdbdfd4",
                "packagetype": "bdist_wheel",
                "python_version": "py2.py3",
                "requires_python": ">=3.6",
                "size": 6888,
                "upload_time": "2017-12-19T20:03:50",
                "url": "https://files.pythonhosted.org/packages/64/64/01503e00fe14cfd56d0b457bca699a4d9967eb831c78807b3dd829df6ac8/pandas_lite-0.1-py2.py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "086bf3e7bea9d5a34a20d85b2629730e",
                    "sha256": "7aa2834a0d7d8f5e06d7c1f6d63cbcec160abe0ed825fcdd0f1f84a8a240909e"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "086bf3e7bea9d5a34a20d85b2629730e",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.6",
                "size": 6622,
                "upload_time": "2017-12-19T20:03:51",
                "url": "https://files.pythonhosted.org/packages/0b/b1/e866bddda30d72b6cd72a5113937744629a8d1d8b9a6a595527fa71acbd8/pandas_lite-0.1.tar.gz"
            }
        ],
        "0.1.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "82709d1baebe11b01eafd344035464c7",
                    "sha256": "88a689d4d873ca4f5084b59045bdaab5cbef36cfc950834cf403af9ae5b3f69f"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1.1-cp36-cp36m-macosx_10_7_x86_64.whl",
                "has_sig": false,
                "md5_digest": "82709d1baebe11b01eafd344035464c7",
                "packagetype": "bdist_wheel",
                "python_version": "cp36",
                "requires_python": ">=3.6",
                "size": 291003,
                "upload_time": "2018-01-10T20:33:45",
                "url": "https://files.pythonhosted.org/packages/cf/e8/5af14366389fdfbfd4425fe328f4f0e527ffbf92aeed76434190f4550f06/pandas_lite-0.1.1-cp36-cp36m-macosx_10_7_x86_64.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "cd6196fab407669ee523ba7cee5272b9",
                    "sha256": "9860ea310243f74c1176b4b601aa99a7cd9a426468f8d2df24374c90781edb42"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "cd6196fab407669ee523ba7cee5272b9",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": ">=3.6",
                "size": 10119,
                "upload_time": "2017-12-21T02:50:50",
                "url": "https://files.pythonhosted.org/packages/70/50/8a08b0e9b39e44e670569d98604c285ca0471e5202598c96cd5f5ce8b003/pandas_lite-0.1.1-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "39eb26a910895f7d1e818b843d5cda77",
                    "sha256": "2de365912574eb42a4951a77161c3f8c8f339e7d6d61f403a43a39cc948a4116"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1.1.tar.gz",
                "has_sig": false,
                "md5_digest": "39eb26a910895f7d1e818b843d5cda77",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.6",
                "size": 9652,
                "upload_time": "2017-12-21T02:50:51",
                "url": "https://files.pythonhosted.org/packages/31/de/7eee9b97fb04c5ebde8017f4551f935194ebee9a3e34300730f86b08eab9/pandas_lite-0.1.1.tar.gz"
            }
        ],
        "0.1.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "00bafda3b5362cbe5dddc9bb16323251",
                    "sha256": "a3f39f86b30241ffac9aca06825553d9ce069ede80caf1d5abb8529d66c861d3"
                },
                "downloads": -1,
                "filename": "pandas_lite-0.1.2-cp36-cp36m-macosx_10_7_x86_64.whl",
                "has_sig": false,
                "md5_digest": "00bafda3b5362cbe5dddc9bb16323251",
                "packagetype": "bdist_wheel",
                "python_version": "cp36",
                "requires_python": ">=3.6",
                "size": 291001,
                "upload_time": "2018-01-10T20:33:49",
                "url": "https://files.pythonhosted.org/packages/c8/57/7e8f26c5459aa7cdd673ebded037772179273a0e1506263f3adb9ef695f5/pandas_lite-0.1.2-cp36-cp36m-macosx_10_7_x86_64.whl"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "00bafda3b5362cbe5dddc9bb16323251",
                "sha256": "a3f39f86b30241ffac9aca06825553d9ce069ede80caf1d5abb8529d66c861d3"
            },
            "downloads": -1,
            "filename": "pandas_lite-0.1.2-cp36-cp36m-macosx_10_7_x86_64.whl",
            "has_sig": false,
            "md5_digest": "00bafda3b5362cbe5dddc9bb16323251",
            "packagetype": "bdist_wheel",
            "python_version": "cp36",
            "requires_python": ">=3.6",
            "size": 291001,
            "upload_time": "2018-01-10T20:33:49",
            "url": "https://files.pythonhosted.org/packages/c8/57/7e8f26c5459aa7cdd673ebded037772179273a0e1506263f3adb9ef695f5/pandas_lite-0.1.2-cp36-cp36m-macosx_10_7_x86_64.whl"
        }
    ]
}