Package: kaggle-dataset-creator
kaggle_dataset_creator - A  Python package to generate csv/jsonA Python package that allows you to create CSV/JSON files by manually entering each
of the entries of cells row by row in Terminal (Windows CMD / Bash).InstallationOpen terminal and enter the below command (Python 3).pip install kaggle_dataset_creatorFeaturesIt allows you to create your own CSV file if you are looking for creating a CSV with manually entered data. You can also get the JSON version of the entered data.You can also view your data at any point of time in your Terminal and again continue
to enter data if you wish to add more rows/records for your final CSV/JSON file.Note: Currently the package is in development, it will be released soon.Examplefromkaggle_dataset_creatorimportKaggleDataSetkd=KaggleDataSet()kd.start()print(kd.columns)print(kd.container)kd.view();# To view the final DataFrame on Terminalkd.to_csv();# To save in csv, default file name is take if filename is not providedprint("DATA:- ")print(kd.dataset)# Accessing dataset attribute to get the final DataFrameprint('Total rows: ',kd.rows)print('Types: ',kd.data_types)If you want to try above in the terminal, try as below after installation.In next version, it will be released with more features. Here our intension is to get the final CSV/JSON.>>>fromkaggle_dataset_creatorimportKaggleDataSet
>>>
>>>kd=KaggleDataSet()>>>kd.start()Enternumberofcolumnsthatyouwantinyourdataset:3SUCCESS:Youaresuccessfullydonewithno.ofcolumns
Enterthenameof1stcolumn:fullname
Enterthenameof2ndcolumn:age
Enterthenameof3rdcolumn:salary

SUCCESS:Youaresuccessfullydonewiththecolumnnames[DATAENTRY]<row:1>fullname:RajShekhar[DATAENTRY]<row:1>age:45[DATAENTRY]<row:1>salary:600000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):y==================================================[DATAENTRY]<row:2>fullname:VencBell[DATAENTRY]<row:2>age:67[DATAENTRY]<row:2>salary:900000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):y==================================================[DATAENTRY]<row:3>fullname:RobertGrime[DATAENTRY]<row:3>age:89[DATAENTRY]<row:3>salary:9000000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):v

--------------------------------------------------fullnameagesalary0RajShekhar456000001VencBell679000002RobertGrime899000000--------------------------------------------------==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):y==================================================[DATAENTRY]<row:4>fullname:ElenGoom[DATAENTRY]<row:4>age:55[DATAENTRY]<row:4>salary:800000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):y==================================================[DATAENTRY]<row:5>fullname:RitaOra[DATAENTRY]<row:5>age:36[DATAENTRY]<row:5>salary:9900000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):v

--------------------------------------------------fullnameagesalary0RajShekhar456000001VencBell679000002RobertGrime8990000003ElenGoom558000004RitaOra369900000--------------------------------------------------==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):y==================================================[DATAENTRY]<row:6>fullname:SensoTomy[DATAENTRY]<row:6>age:54[DATAENTRY]<row:6>salary:7700000==================================================Doyouwanttoadd1morerow/viewdata(y/n/v):n
Isthismistakenlytyped(y/n):n==================================================SUCCESS:Youaresuccessfullydonewithenteringdataforyourdataset
>>>
>>># View the data...
>>>kd.view()--------------------------------------------------fullnameagesalary0RajShekhar456000001VencBell679000002RobertGrime8990000003ElenGoom558000004RitaOra3699000005SensoTomy547700000--------------------------------------------------
True
>>>
>>>success=kd.view()--------------------------------------------------fullnameagesalary0RajShekhar456000001VencBell679000002RobertGrime8990000003ElenGoom558000004RitaOra3699000005SensoTomy547700000--------------------------------------------------
>>>
>>>success
True
>>>
>>># Store the dataset as DataFrame...
>>>df=kd.dataset
>>>dffullnameagesalary0RajShekhar456000001VencBell679000002RobertGrime8990000003ElenGoom558000004RitaOra3699000005SensoTomy547700000>>>
>>>type(df)<class'pandas.core.frame.DataFrame'>
>>>
>>>kd.rows6>>>
>>>kd.data_types{'fullname':'string','age':'numeric','salary':'numeric'}>>>Generating random stringsPython3.6.7(v3.6.7:6ec5cf24b7,Oct202018,03:02:14)[GCC4.2.1CompatibleAppleLLVM6.0(clang-600.0.57)]ondarwin
Type"help","copyright","credits"or"license"formoreinformation.
>>>>>>fromkaggle_dataset_creator.random_stringimportrandom_string
>>>>>>random_string()'VFdwQmVFOV'>>>>>>random_string()'TWpBeE9TMH'>>>>>>random_string()'=UDN0gDN54'>>>>>>random_string()'TWpBeE9TMH'>>>>>>random_string()'=ATM1UDMz4'>>>>>>random_string(11)'VFdwQmVFOVR'>>>>>>random_string(15)'5M2RW5kTUVVRxAT'>>>>>>random_string(15)'VFdwQmVFOVRNSGR'>>>>>>random_string(15)'5M2RS9kQUFVR5sW'>>>>>>random_string(15)'=AzN2MDMy4iNzoz'>>>>>>random_string(15)'MjAxOS0wNS0yMSA'>>>