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import pandas as pd
import numpy as np
#attendance_data = pd.read_csv('AttendanceData.csv',index_col=2,
# parse_dates=True)
#attendance_data.columns = ['event_id', 'user_id']
event_data = pd.read_csv('EventData.csv',#skipfooter=1,
index_col=0)
event_data.columns = ['latitude', 'longitude']
@jaidevd
jaidevd / setup.md
Last active August 29, 2015 14:10
SciPy India 2014 Installation and Setup

SciPy India 2014 will feature a lot of hands-on, practical tutorial sessions that require the participants to have some software on their respective computers. Please follow the instructions here before you come to the conference, so that we may start the tutorials without any delay.

Installing Canopy

Canopy is the primary Python distribution that we will be using during the conference. You may use Anaconda, or the system Python distribution, or any other Python interpreter for the conference. However, please note that we may not be able to support any other distribution other than Canopy. This is because the Python packages we will be providing for the tutorials are customized for Canopy.

Please visit this link https://store.enthought.com/downloads/ and click on the "Download Canopy Express" button to download the Canopy installer. Run this installer to install Canopy.

@jaidevd
jaidevd / pyds.py
Last active August 29, 2015 14:19
View Python docstrings through $EDITOR
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2015 jaidev <jaidev@newton>
#
# Distributed under terms of the MIT license.
"""
@jaidevd
jaidevd / tree_widget_example.py
Last active August 29, 2015 14:20
Basic PySide layout example with TabWidget and TreeWidget
from PySide import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import datetime
IRIS_PATH = "/tmp/access"
@jaidevd
jaidevd / scipy_window_gallery.ipynb
Last active June 15, 2017 16:40
A gallery of window functions in SciPy
@jaidevd
jaidevd / cossim.py
Created June 5, 2015 11:40
Make sklearn.metrics.pairwise.cosine_similarity optionally return sparse output.
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2015 jaidev <jaidev@newton>
#
# Distributed under terms of the MIT license.
from sklearn.metrics.pairwise import check_pairwise_arrays
from sklearn.preprocessing import normalize
from traits.api import HasTraits, Property, Dict, cached_property, Any, Str, Int
class MyTraits(HasTraits):
a = Any
b = Property(Dict(key_trait=Str, value_trait=Int), depends_on=['a'])
@cached_property
Title Author Genre Height Publisher
Fundamentals of Wavelets Goswami, Jaideva signal_processing 228 Wiley
Data Smart Foreman, John data_science 235 Wiley
God Created the Integers Hawking, Stephen mathematics 197 Penguin
Superfreakonomics Dubner, Stephen economics 179 HarperCollins
Orientalism Said, Edward history 197 Penguin
Nature of Statistical Learning Theory, The Vapnik, Vladimir data_science 230 Springer
Integration of the Indian States Menon, V P history 217 Orient Blackswan
Drunkard's Walk, The Mlodinow, Leonard science 197 Penguin
Image Processing & Mathematical Morphology Shih, Frank signal_processing 241 CRC
@jaidevd
jaidevd / .vimrc
Last active March 23, 2017 15:23
" Powerline stuff
set rtp+=/Users/jaidevd/src/powerline/powerline/bindings/vim
set laststatus=2
execute pathogen#infect()
" Python stuff
syntax enable
filetype on
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