Skip to content

Tool to visualize data quickly with no brain usage for plot creation

License

Notifications You must be signed in to change notification settings

eyadsibai/brute-force-plotter

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Brute Force Plotter

[Work in progress] Tool to visualize data quickly with no brain usage for plot creation

Installation

will be packaged soon

Example

It was tested on python3 only

$ git clone https://github.com/eyadsibai/brute_force_plotter.git
$ cd brute_force_plotter
$ pip3 install -r requirements.txt
$ python3 brute_force_plotter.py example/titanic.csv example/titanic_dtypes.json example/output
  • json.dump({k:v.name for k,v in df.dtypes.to_dict().items()},open('dtypes.json','w'))
  • the first argument is the input file (csv file with data) example/titanic.csv
  • second argument is a json file with the data types of each columns (c for category, n for numeric, i for ignore) example/titanic_dtypes.json
{
"Survived": "c",
"Pclass": "c",
"Sex": "c",
"Age": "n",
"SibSp": "n",
"Parch": "n",
"Fare": "n",
"Embarked": "c",
"PassengerId": "i",
"Ticket": "i",
"Cabin": "i",
"Name": "i"
}
  • third argument is the output directory
  • c stands for category, i stands for ignore, n for numeric

Age Distribution (Histogram with Kernel Density Estimation, Violin Plot)

Heatmap for Sex and Pclass

Pclass vs Survived

Survived vs Age

Age vs Fare

TODO

  • target variable support
  • Clean up part of the code
  • More documentation
  • Tests?
  • Support 3 variables (contour plots/ etc)
  • Fallback for large datasets
  • Figure out the data type or suggest some
  • Map visualization (if geocoordinates)
  • Minimize the number of plots
  • Support for Time Series

About

Tool to visualize data quickly with no brain usage for plot creation

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages