btabibian

/*
This file is Implementation of OpenCV SVM tutorial program.

Implementation of OpenCV SVM tutorial is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

Implementation of ARFL is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of

btabibian

#!/usr/bin/env python
# coding: utf-8

# You need PIL <http://www.pythonware.com/products/pil/> to run this script
# Download unifont.ttf from <http://unifoundry.com/unifont.html> (or use
# any TTF you have)
# Copyright 2011 Álvaro Justen [alvarojusten at gmail dot com]
# License: GPL <http://www.gnu.org/copyleft/gpl.html>

# You need arabic_reshaper <https://github.com/edx/edx-certificates/blob/master/arabic_reshaper.py>

btabibian

import numpy as np
import pandas as pd

def category_to_int(data,default=-1):
    new_data=pd.Series(np.zeros(data.shape)-1,index=data.index,name=data.name+"_int")
    uniques=data.unique()
    for i in zip(uniques,xrange(uniques.shape[-1])):
        new_data[data==i[0]]=i[1]
    return new_data

btabibian

# -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>

# <markdowncell>

# Reading Data from text and store in MongoDB
# ==========================================
# 
# + Set the name of database to _movies_.
# + ensure indecies are placed.