Package: jsonr
jsonr - PyPijsonr: (V8.6.6)

Highly customizable JSON objects and dataframes, and your python toolkit all in one.Installing# Linux/macOSpython3pipinstall-Ujsonr# Windowspy-3-mpipinstall-UjsonrArchitecture.mailmapAUTHORSLICENSEMANIFEST.inREADME.mdSECURITY.mdVERSIONpyproject.tomlsetup.cfgsetup.pyjsonr/__init__.pyjsonr/__main__.pyjsonr/help.pyjsonr.egg-info/PKG-INFOjsonr.egg-info/SOURCES.txtjsonr.egg-info/dependency_links.txtjsonr.egg-info/requires.txtjsonr.egg-info/top_level.txtjsonr/_core/__init__.pyjsonr/_core/_binary.pyjsonr/_core/_code.pyjsonr/_core/_concurrent.pyjsonr/_core/_crypto.pyjsonr/_core/_data.pyjsonr/_core/_dcompress.pyjsonr/_core/_debug.pyjsonr/_core/_devtools.pyjsonr/_core/_dtypes.pyjsonr/_core/_file.pyjsonr/_core/_formats.pyjsonr/_core/_functional.pyjsonr/_core/_guitk.pyjsonr/_core/_idata.pyjsonr/_core/_import.pyjsonr/_core/_international.pyjsonr/_core/_iprotocols.pyjsonr/_core/_language.pyjsonr/_core/_markup.pyjsonr/_core/_math.pyjsonr/_core/_mswindows.pyjsonr/_core/_mutimedia.pyjsonr/_core/_networking.pyjsonr/_core/_os.pyjsonr/_core/_packaging.pyjsonr/_core/_program.pyjsonr/_core/_runtime.pyjsonr/_core/_superseded.pyjsonr/_core/_text.pyjsonr/_core/_unix.pyjsonr/_typing/__init__.pyjsonr/_typing/jsonr_typing_flowa.pyjsonr/_typing/jsonr_typing_json.pyjsonr/_typing/jsonr_typing_pollinations.pyjsonr/_typing/jsonr_typing_string.pyjsonr/_utils/__init__.pyjsonr/_utils/_bond.pyjsonr/_utils/_convertions.pyjsonr/_utils/_infinity.pyjsonr/_utils/_insepct.pyjsonr/bases/__init__.pyjsonr/bases/new_base.pyjsonr/core/__init__.pyjsonr/core/dataframe.pyjsonr/core/new.pyjsonr/libs/__init__.pyjsonr/libs/flowa/__init__.pyjsonr/libs/flowa/_version.pyjsonr/libs/flowa/main/__init__.pyjsonr/libs/flowa/main/decisiontree.pyjsonr/libs/flowa/main/imagemodel.pyjsonr/libs/flowa/main/labelencoder.pyjsonr/libs/flowa/types/__init__.pyjsonr/libs/flowa/utils/__init__.pyjsonr/libs/pollinations/__init__.pyjsonr/libs/pollinations/abc/__init__.pyjsonr/libs/pollinations/abc/imageprotocol.pyjsonr/libs/pollinations/abc/textprotocol.pyjsonr/libs/pollinations/ai/__init__.pyjsonr/libs/pollinations/ext/__init__.pyjsonr/libs/pollinations/types/ImageModel.pyjsonr/libs/pollinations/types/ImageObject.pyjsonr/libs/pollinations/types/TextModel.pyjsonr/libs/pollinations/types/TextObject.pyjsonr/libs/pollinations/types/__init__.pyjsonr/typing/__init__.pyjsonr/utils/__init__.pytest/test_import.pyJSON Objectsimportjsonrjson:jsonr.JSON=jsonr.New(auto=True,some_var='thanks for using jsonr!',other_var='im a random var!',lol='lol')// >>> {'some_var': 'thanks for using jsonr!', 'other_var': 'im a random var!', 'lol': 'lol'}json.test:int=123print(json['test'])// >>> 123json_copy:dict=json.copy()new_json:jsonr.JSON=jsonr.New()new_json.to(json_copy)print(new_json)// >>> {'some_var': 'thanks for using jsonr!', 'other_var': 'im a random var!', 'lol': 'lol', 'test': 123}json.wipe()// >>> {}For more JSON Object Examples view thejsonr/examplesDataFrame Objectsframe=jsonr.Frame(columns=["1A TEST-A","B","C"],rows=[[1,2,3],[4,5,6]])// >>>      | 1A TEST-A | B | C// >>> -----------------------// >>> 0    |         1 | 2 | 3// >>> 1    |         4 | 5 | 6print(frame._1A_TEST_A)// >>> [1, 4]frame.add_row([7,8,9])// >>>      | 1A TEST-A | B | C// >>> -----------------------// >>> 0    |         1 | 2 | 3// >>> 1    |         4 | 5 | 6// >>> 2    |         7 | 8 | 9frame.add_column("D",[10,11,12])// >>>      | 1A TEST-A | B | C |  D// >>> ----------------------------// >>> 0    |         1 | 2 | 3 | 10// >>> 1    |         4 | 5 | 6 | 11// >>> 2    |         7 | 8 | 9 | 12X:list=frame.drop(columns=['B','C'])# Creates a new dataframe to not alter the original frame.// >>>      | 1A TEST-A |  D// >>> --------------------// >>> 0    |         1 | 10// >>> 1    |         4 | 11// >>> 2    |         7 | 12print(frame.describe())// >>> {'1A TEST-A': {'count': 3, 'mean': 4.0, 'std': 2.449489742783178, 'min': 1, '25%': 1, '50%': 4, '75%': 7, 'max': 7}, 'B': {'count': 3, 'mean': 5.0, 'std': 2.449489742783178, 'min': 2, '25%': 2, '50%': 5, '75%': 8, 'max': 8}, 'C': {'count': 3, 'mean': 6.0, 'std': 2.449489742783178, 'min': 3, '25%': 3, '50%': 6, '75%': 9, 'max': 9}, 'D': {'count': 3, 'mean': 11.0, 'std': 0.816496580927726, 'min': 10, '25%': 10, '50%': 11, '75%': 12, 'max': 12}}For more DataFrame Object Examples view thejsonr/examplesLinksGitHub =https://github.com/jsonr-pyRepository =https://github.com/jsonr-py/jsonrPyPi =https://pypi.org/project/jsonr