Package: data-visualizer
V. 0.1.7Project DescriptionA python program that visualizes data from a.csvfile. It uses thePySimpleGuipython library for its GUI.At the moment, this program can only read data from.csvfiles, but in the future I plan on adding support for other filetypes, and an option to connect to a SQL or a MongoDb database.Table of ContentsFeaturesDisplay dataSearch dataFilter dataInstallationUsing pipFrom sourceUsagePipManuallyDependenciesPySimpleGuiTkinterPip installationFile SupportHeader bugBug exampleLicensePySimpleGuiFeaturesIf you want to test the program yourself, I recommend you visit the pagemockarooto get some sample data in.csvformat.Display dataSearch dataFilter dataInstallationUsing pipData visualizer can be installed with pip, along with all the program dependencies in the case they aren't installed. To do so, run the follow command:pipinstalldata-visualizerFrom sourceOn the other hand, if you want to, you can also download the program from the repo. If you want to do so, follow these steps to do so.Clone the repo into your local machine:Open the cloned folder and run the"data_visualizer"folder as a module with the following command:python3-mdata_visualizerUsageThere are several ways in which you can open the program.PipIf Data Visualizer was installed with pip, you can run the program in the terminal by simple writingdata-visualizerin the terminal. The program will then open.ManuallyAnother way you can run the program is by opening either the module folder installed by pip, or the cloned folder from the repo. Then, once inside the folder, simply run thedata_visualizerfolder as a python module with the following command:python3-mdata_visualizerDependenciesPySimpleGuiBy default, Data Visualizer'ssetup.pyfile was setup in a way that automatically downloads all the packages the program uses and depends of. However, if for some reason you want to install them yourself, Data Visualizer requires the PySimpleGui library to work.You can install them with pip using the following commands:pipinstallPySimpleGUIIn the case that you don't have pip, scroll down to thePip Instalationsection to see how to install it.TkinterData Visualizer is made using the PySimpleGui library, which uses Tkinter under the hood. So, it is very important to have Tkinter already setup to your Python version for Data Visualizer to work.If you don't have Tkinter already with your Python configuration, you will need to do that first.Windows:Follow this video guide.MacOs (Using Homebrew):brew install python-tkLinux (Ubuntu):sudo apt-get update && sudo apt-get install python3-tkPip installationDon't have pip? You can install it like this:Linux & MacOspython3-mensurepipWindowspy-mensurepipPlease note that the installation of pip in windows can sometimes be...complicated. If you are having problems making pip work, I recommend you thisvideo guideon how to install it.File SupportData visualizer supports the following types of files:File TypeSupport.csv✅.json❌SQL📅Mongodb❌Keywords:✅ Yes,❌ No,📅 work in progressHeader bugCurrently, there's a bug where the first row of header-less.csvfiles gets confused for the file's headers. This happens because Data Visualizer always takes the first row of a .csv file that comes with pre-defined headers, and uses it as the headers of the file. The usefulness of this feature can be seen with files that has its data pre-categorize in the forms of these headers. However, for files that don't do this , this feature becomes a problem.The nature of this bug makes it pretty difficult to fix, but with time, I think I'll be able to get it done. So, keep that in mind while working with files wihout a proper header for the time being.Bug exampleNote: The files used in this example were taken frommockaroo.File with pre-defined headersFile without pre-defined headersLicenseThis project makes use of the MIT license. To read more about it, you can check it outhere.PySimpleGuiThis project makes uses of the PySimpleGui python library, which makes use of the LGPL-3.0 license. Read more about this license in the project repohere.