rjj 0.1.5

rjj (read-joint-jet) is a simple cmd-based data analysis/transforming tool

rjj (read-joint-jet)

rjj is a simple cmd-based data transforming/analysis tool 🛠⚙

install it via pip/pip3

pip install rjj

update rjj

pip install rjj --upgrade

check current version

rjj -v

read user manual

rjj -h

convertor

convert json to csv; select a json file in the current directory, choose to enter another file name (don't need the extension) for output or not (Y/n); if not, the converted csv will be saved with the same name as the json♻

rjj c

reversor

reverse csv back to json; select a csv file in the current directory, choose to enter another file name for output or not (Y/n); if not, the converted json file will be saved with the same name; 🌀support any data type, even emoji🐷

rjj r

matcher

identify matched/repeated record(s) in the current directory and extend to its sub-directories; powerful massive record matching tool🔍

rjj m

provide a name to the output file (if not, the output file will be named as output.csv); source file (location) will be indicated in a newly created column Source_file

uniquer

identify unique/non-repeated record(s)🔍 in the current directory and extend to its sub-directories; powerful massive record uniqueness identifier

rjj u

give a name to the output file; source location will be indicated in a newly created column Source_file

filter

locate the input Keyword among all csv files in the current directory👁‍🗨 (and could opt to expand to its all sub-folder files; cool right?)🔍

rjj f

while executing the command above, give your searching keyword first, provide a name for the output file (if not, the output file will be named as output.csv), then opt to apply to all sub-folder(s) or just the csv file(s) in the current directory (Y/n); source file (location info) will be indicated in a newly created first column Source_file; the exact coordinate (x,y) will be given in the newly created second and third columns, named Column_y and Row_x; and the full record will be pasted behind for simplifying your auditing work📑

detector

detect the co-existing record(s) between two csv files🔍; select two csv files to execute the detection process, then give a name for the output file; co-existing record(s) will be indicated in a newly created column Coexist

rjj d

jointer and splitter

joint or split your data file(s)

jointer

joint all csv files in the current directory together; all file names will be stored in the first field of the newly created column File; when you execute the command you will be asked for assigning a name for the output file🖇

rjj j

splitter

split the selected csv file to different csv files and name it according to the value in the first field of that selected file📑

rjj s

xplit

split the selected excel (.xls or .xlsx) to pieces and name it according to the value in the first field of that selected excel

rjj x

joint

joint all excels (.xls and .xlsx) in the current directory together*; all file names will be stored in the first field of the newly created column File; when you execute the command you might be asked for assigning a name for the output file

rjj t

*differ from csv jointer, since both .xls and .xlsx is accepted, and the file extention will not be taken, it will be merged while two of them share the same file name (cannot be split by the command above); understand this condition, make good use of it!

kilter

locate the input Keyword among all excel files (.xls and .xlsx) in the current directory (and could expand to its sub-folders)👁‍🗨; give your searching Keyword first (extremely important🔑), opt to apply to all sub-folder(s) or just the excel(s) in the current directory (Y/n), then give a name for the output file (if not, the output file will be named as output.xlsx); source file (location info) will be indicated in a newly created first column Source_file

rjj k

since each excel file is possible to contain more than one sheet📄, the sheet number will be stored in the newly created second column Sheet_z, then the exact coordinate (x,y) will be given after it, in the third and fourth columns, named Column_y and Row_x; and the full data record will be pasted behind as well; super kooooo🍻