Team04 Data Insights and Visualizations

TEAM04Files/Bar2Chart/Untitled.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv = pd.read_csv(\"military.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv = csv.sort_values('ST_NAME')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv.to_csv(\"military.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

TEAM04Files/Bar2Chart/javascript.js

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+var margin = {top: 40, right: 10, bottom: 180, left: 10},
+    width = 1000 - margin.left - margin.right,
+    height = 500 - margin.top - margin.bottom;
+
+var formatPercent = d3.format(".0%");
+
+var x = d3.scale.ordinal()
+    .rangeRoundBands([0, width], .1);
+
+var y = d3.scale.linear()
+    .range([height, 0]);
+
+var xAxis = d3.svg.axis()
+    .scale(x)
+    .orient("bottom");
+
+var yAxis = d3.svg.axis()
+    .scale(y)
+    .orient("left")
+    .tickFormat(formatPercent);
+
+var tip = d3.tip()
+    .attr('class', 'd3-tip')
+    .offset([-10, 0])
+    .html(function (d) {
+        return "<strong>STATE:</strong> <span style='color:red'>" + d.ST_NAME + "</span><br><strong>Military Base Count:</strong>  <span style='color:red'>" + d.count + "</span>";
+    })
+
+var svg = d3.select("body").append("svg")
+    .attr("width", width + margin.left + margin.right)
+    .attr("height", height + margin.top + margin.bottom)
+    .append("g")
+    .attr("transform", "translate(" + margin.left + "," + margin.top + ")");
+
+svg.call(tip);
+
+d3.csv("military.csv", type, function (error, data) {
+    x.domain(data.map(function (d) {
+        return d.ST_NAME.slice(0,2);
+    }));
+    y.domain([0, d3.max(data, function (d) {
+        return d.count;
+    })]);
+
+    svg.append("g")
+        .attr("class", "x axis")
+        .attr("transform", "translate(0," + height + ")")
+        .call(xAxis);
+    // .selectAll("text")
+    // .style("text-anchor","end")
+    // .attr("transform","rotate(-90)");
+
+    svg.append("g")
+        .attr("class", "y axis")
+        .call(yAxis)
+        .append("text")
+        .attr("transform", "rotate(-90)")
+        .attr("y", 6)
+        .attr("dy", ".71em")
+        .style("text-anchor", "end")
+        .text("Count");
+
+    svg.selectAll(".bar")
+        .data(data)
+        .enter().append("rect")
+        .attr("class", "bar")
+        .attr("x", function (d) {
+            return x(d.ST_NAME.slice(0,2));
+        })
+        .attr("width", x.rangeBand())
+        .attr("y", function (d) {
+            return y(d.count);
+        })
+        .attr("height", function (d) {
+            return height - y(d.count);
+        })
+        .on('mouseover', tip.show)
+        .on('mouseout', tip.hide)
+
+});
+
+function type(d) {
+    d.count = +d.count;
+    return d;
+}

TEAM04Files/Bar2Chart/military.csv

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+,Unnamed: 0,ST_NAME,count
+11,220,ALABAMA,10
+26,249,ALASKA,5
+12,71,ARIZONA,9
+23,204,ARKANSAS,6
+0,123,CALIFORNIA,68
+19,268,COLORADO,8
+46,61,CONNECTICUT,1
+48,278,DELAWARE,1
+32,312,DISTRICT OF COLUMBIA,4
+3,329,FLORIDA,17
+6,108,GEORGIA,14
+18,364,HAWAII,8
+35,83,IDAHO,3
+16,263,ILLINOIS,8
+9,179,INDIANA,10
+44,258,IOWA,1
+21,374,KANSAS,6
+29,80,KENTUCKY,5
+30,78,LOUISIANA,5
+33,197,MAINE,4
+5,282,MARYLAND,14
+14,250,MASSACHUSETTS,8
+27,223,MICHIGAN,5
+37,209,MINNESOTA,3
+15,177,MISSISSIPPI,8
+17,261,MISSOURI,8
+43,239,MONTANA,1
+36,389,NEBRASKA,3
+34,325,NEVADA,4
+25,241,NEW JERSEY,6
+28,192,NEW MEXICO,5
+7,196,NEW YORK,11
+20,400,NORTH CAROLINA,6
+41,339,NORTH DAKOTA,2
+31,328,OHIO,5
+24,193,OKLAHOMA,6
+39,277,OREGON,2
+8,102,PENNSYLVANIA,11
+42,349,PUERTO RICO,2
+40,89,RHODE ISLAND,2
+10,190,SOUTH CAROLINA,10
+47,207,SOUTH DAKOTA,1
+22,290,TENNESSEE,6
+2,56,TEXAS,26
+13,240,UTAH,8
+1,55,VIRGINIA,29
+4,47,WASHINGTON,16
+38,332,WISCONSIN,3
+45,292,WYOMING,1

TEAM04Files/Bar2Chart/military_bar.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <style>
+
+        body {
+            font: 10px sans-serif;
+        }
+
+        .axis path,
+        .axis line {
+            fill: none;
+            stroke: #000;
+            shape-rendering: crispEdges;
+        }
+
+        .bar {
+            fill: darkslateblue;
+        }
+
+        .bar:hover {
+            fill: orangered;
+        }
+
+        .x.axis path {
+            display: none;
+        }
+
+        .d3-tip {
+            line-height: 1;
+            font-weight: bold;
+            padding: 12px;
+            background: rgba(0, 0, 0, 0.8);
+            color: #fff;
+            border-radius: 2px;
+        }
+
+        /* Creates a small triangle extender for the tooltip */
+        .d3-tip:after {
+            box-sizing: border-box;
+            display: inline;
+            font-size: 10px;
+            width: 100%;
+            line-height: 1;
+            color: rgba(0, 0, 0, 0.8);
+            content: "\25BC";
+            position: absolute;
+            text-align: center;
+        }
+
+        /* Style northward tooltips differently */
+        .d3-tip.n:after {
+            margin: -1px 0 0 0;
+            top: 100%;
+            left: 0;
+        }
+    </style>
+    <title>Bar Chart</title>
+</head>
+<body>
+<h1>
+    Number of Military Bases per State.
+</h1>
+<h1>
+    Number of Military Bases per State.
+</h1>
+<div id="chart"></div>
+<script src="http://d3js.org/d3.v3.min.js"></script>
+<script src="http://labratrevenge.com/d3-tip/javascripts/d3.tip.v0.6.3.js"></script>
+<script type="text/javascript" src="javascript.js"></script>
+</body>
+</html>

TEAM04Files/BarChart/Population_bar.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv = pd.read_csv(\"city-pop.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv1 = csv.sort_values(by = [\"population\"], ascending = False).drop_duplicates().head(10)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv1 = csv1.sort_values(by = [\"city\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "csv1.to_csv(\"city-pop-top10.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

TEAM04Files/BarChart/Population_bar_script.py

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+
+# coding: utf-8
+
+# In[1]:
+
+
+import pandas as pd
+
+
+# In[12]:
+
+
+csv = pd.read_csv("city-pop.csv")
+
+
+# In[27]:
+
+
+csv1 = csv.sort_values(by = ["population"], ascending = False).drop_duplicates().head(10)
+
+
+# In[28]:
+
+
+csv1 = csv1.sort_values(by = ["city"])
+
+
+# In[30]:
+
+
+csv1.to_csv("city-pop-top10.csv")
+