Samira Kumar samirak93

## index.html
<!DOCTYPE html>
<html>
  <head>
    <meta http-equiv="Content-Type" content="text/html;charset=utf-8">
    <title>Node-Link Tree</title>

	<link href="interactive_tree.css" rel="stylesheet" type="text/css" />
<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js?1.27.2"></script>
    <script type="text/javascript" src="http://mbostock.github.com/d3/d3.layout.js?1.27.2"></script>


## index.html
<!DOCTYPE html>
<html>
  <head>
    <meta http-equiv="Content-Type" content="text/html;charset=utf-10">
    <title>Node-Link Tree</title>

	<link href="interactive_tree.css" rel="stylesheet" type="text/css" />
<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js?1.27.2"></script>
    <script type="text/javascript" src="http://mbostock.github.com/d3/d3.layout.js?1.27.2"></script>


## index.html
	<!DOCTYPE html>
<meta charset="utf-8">
<title>Liverpool FC Chance Combinations (2016-17)</title>
<style>
body {
  font: 10px verdana;
}

svg text{
  fill:grey;

## plotly_football_pitch.py
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.offline as offline

offline.init_notebook_mode()

midpoint_trace = go.Scatter(
    x=[0],
    y=[0]
)

## CENSUS_INCOME.csv
Age,workclass,fnlwgt,Education,education-num,marital-status,occupation,relationship,race,sex,capital-gain,capital-loss,hours-per-week,native country,Census Income
39, State-gov,77516, Bachelors,13, Never-married, Adm-clerical, Not-in-family, White, Male,2174,0,40, United-States, <=50K
50, Self-emp-not-inc,83311, Bachelors,13, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,13, United-States, <=50K
38, Private,215646, HS-grad,9, Divorced, Handlers-cleaners, Not-in-family, White, Male,0,0,40, United-States, <=50K
53, Private,234721, 11th,7, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male,0,0,40, United-States, <=50K
28, Private,338409, Bachelors,13, Married-civ-spouse, Prof-specialty, Wife, Black, Female,0,0,40, Cuba, <=50K
37, Private,284582, Masters,14, Married-civ-spouse, Exec-managerial, Wife, White, Female,0,0,40, United-States, <=50K
49, Private,160187, 9th,5, Married-spouse-absent, Other-service, Not-in-family, Black, Female,0,0,16, Jamaica, <=50K
52, Self-emp-not-inc,209642, HS

## myfile.geojson

      
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                samirak93
                / myfile.geojson
            
            
              Created
              December 5, 2019 02:17
            
          
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## geojson.html
<!DOCTYPE html>
<head>
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS=false; L_NO_TOUCH=false; L_DISABLE_3D=false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>

## bokeh_plots.py
from bokeh.io import output_file, show, output_notebook, save
from bokeh.models import (
    ColumnDataSource, LabelSet, FactorRange, BasicTicker, ColorBar, LinearColorMapper, PrintfTickFormatter)
from bokeh.plotting import figure
from bokeh.palettes import Category20, Viridis256
from bokeh.layouts import column

import pandas as pd

import os
	<!DOCTYPE html>
	<html>
	<head>
	<meta http-equiv="Content-Type" content="text/html;charset=utf-8">
	<title>Node-Link Tree</title>

	<link href="interactive_tree.css" rel="stylesheet" type="text/css" />
	<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js?1.27.2"></script>
	<script type="text/javascript" src="http://mbostock.github.com/d3/d3.layout.js?1.27.2"></script>
	<!DOCTYPE html>
	<meta charset="utf-8">
	<title>Liverpool FC Chance Combinations (2016-17)</title>
	<style>
	body {
	font: 10px verdana;
	}

	svg text{
	fill:grey;
	import plotly.plotly as py
	import plotly.graph_objs as go
	import plotly.offline as offline

	offline.init_notebook_mode()

	midpoint_trace = go.Scatter(
	x=[0],
	y=[0]
	)
	Age,workclass,fnlwgt,Education,education-num,marital-status,occupation,relationship,race,sex,capital-gain,capital-loss,hours-per-week,native country,Census Income
	39, State-gov,77516, Bachelors,13, Never-married, Adm-clerical, Not-in-family, White, Male,2174,0,40, United-States, <=50K
	50, Self-emp-not-inc,83311, Bachelors,13, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,13, United-States, <=50K
	38, Private,215646, HS-grad,9, Divorced, Handlers-cleaners, Not-in-family, White, Male,0,0,40, United-States, <=50K
	53, Private,234721, 11th,7, Married-civ-spouse, Handlers-cleaners, Husband, Black, Male,0,0,40, United-States, <=50K
	28, Private,338409, Bachelors,13, Married-civ-spouse, Prof-specialty, Wife, Black, Female,0,0,40, Cuba, <=50K
	37, Private,284582, Masters,14, Married-civ-spouse, Exec-managerial, Wife, White, Female,0,0,40, United-States, <=50K
	49, Private,160187, 9th,5, Married-spouse-absent, Other-service, Not-in-family, Black, Female,0,0,16, Jamaica, <=50K
	52, Self-emp-not-inc,209642, HS
	from bokeh.io import output_file, show, output_notebook, save
	from bokeh.models import (
	ColumnDataSource, LabelSet, FactorRange, BasicTicker, ColorBar, LinearColorMapper, PrintfTickFormatter)
	from bokeh.plotting import figure
	from bokeh.palettes import Category20, Viridis256
	from bokeh.layouts import column

	import pandas as pd

	import os