12523-218v2.ipynb

{
	"cells": [{
			"cell_type": "code",
			"execution_count": 1,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"[['', 'year', 'month', 'intent', 'police', 'sex', 'age', 'race', 'hispanic', 'place', 'education'], ['1', '2012', '01', 'Suicide', '0', 'M', '34', 'Asian/Pacific Islander', '100', 'Home', '4'], ['2', '2012', '01', 'Suicide', '0', 'F', '21', 'White', '100', 'Street', '3'], ['3', '2012', '01', 'Suicide', '0', 'M', '60', 'White', '100', 'Other specified', '4'], ['4', '2012', '02', 'Suicide', '0', 'M', '64', 'White', '100', 'Home', '4']]\n"
				]
			}],
			"source": [
				"import csv\n",
				"f = open(\"guns.csv\", \"r\")\n",
				"csv_file = csv.reader(f)\n",
				"data = list(csv_file)\n",
				"print(data[:5])"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 2,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"['', 'year', 'month', 'intent', 'police', 'sex', 'age', 'race', 'hispanic', 'place', 'education']\n",
					"[['1', '2012', '01', 'Suicide', '0', 'M', '34', 'Asian/Pacific Islander', '100', 'Home', '4'], ['2', '2012', '01', 'Suicide', '0', 'F', '21', 'White', '100', 'Street', '3'], ['3', '2012', '01', 'Suicide', '0', 'M', '60', 'White', '100', 'Other specified', '4'], ['4', '2012', '02', 'Suicide', '0', 'M', '64', 'White', '100', 'Home', '4'], ['5', '2012', '02', 'Suicide', '0', 'M', '31', 'White', '100', 'Other specified', '2']]\n"
				]
			}],
			"source": [
				"headers=data[0]\n",
				"print(headers)\n",
				"data=data[1:len(data)]\n",
				"print(data[:5])"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 3,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"['2012', '2012', '2012', '2012']\n",
					"{'2012', '2013', '2014'}\n",
					"{'2012': 33563, '2013': 33636, '2014': 33599}\n"
				]
			}],
			"source": [
				"years=[i[1] for i in data]\n",
				"print(years[:4])\n",
				"years_set = set(years)\n",
				"print(years_set)\n",
				"year_counts={}\n",
				"for i in years:\n",
				"    if i in year_counts.keys():\n",
				"        year_counts[i] += 1\n",
				"    else:\n",
				"        year_counts[i] = 1\n",
				"print(year_counts)\n",
				" "
			]
		},
		{
			"cell_type": "code",
			"execution_count": 4,
			"metadata": {
				"collapsed": false,
				"scrolled": true
			},
			"outputs": [{
				"data": {
					"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAE4CAYAAACNEF64AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
					"text/plain": [
						"<matplotlib.figure.Figure at 0x7f7b4a30a978>"
					]
				},
				"metadata": {},
				"output_type": "display_data"
			}],
			"source": [
				"        \n",
				"from matplotlib import pyplot as plt\n",
				"%matplotlib inline\n",
				"\n",
				"year_counts_name = year_counts.keys()\n",
				"year_counts_values = year_counts.values()\n",
				"year_counts_range = range(len(year_counts))\n",
				"\n",
				"plt.bar(year_counts_range, year_counts_values, \n",
				"        tick_label=year_counts_name, align='center',\n",
				"       color=('seagreen', 'palevioletred'))\n",
				"plt.xticks(rotation=90)\n",
				"plt.title('Gun deaths grouped by year in % \\n')\n",
				"plt.xlabel('Years')\n",
				"plt.ylabel('Count of years \\n')\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
				"The gun deaths per year are nearly constant."
			]
		},
		{
			"cell_type": "code",
			"execution_count": 5,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"['01', '01', '01', '02', '02']\n",
					"{'12', '05', '04', '09', '10', '07', '11', '01', '06', '02', '03', '08'}\n",
					"{'05': 8669, '04': 8455, '10': 8406, '09': 8508, '12': 8413, '07': 8989, '01': 8273, '11': 8243, '06': 8677, '02': 7093, '03': 8289, '08': 8783}\n"
				]
			}],
			"source": [
				"# exploring variable month\n",
				"months = [i[2] for i in data]\n",
				"print(months[:5])\n",
				"# what are the unique values of the variable months\n",
				"months_set= set(months)\n",
				"print(months_set)\n",
				"# all months are included: okay\n",
				"# count gun deaths per months, meaning count row per month\n",
				"gundeaths_month = {}\n",
				"for i in data:\n",
				"    if i[2] in gundeaths_month.keys():\n",
				"        gundeaths_month[i[2]] += 1\n",
				"    else:\n",
				"        gundeaths_month[i[2]] = 1\n",
				"\n",
				"print(gundeaths_month)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 6,
			"metadata": {
				"collapsed": false,
				"scrolled": true
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"[('05', 8669), ('04', 8455), ('10', 8406), ('09', 8508), ('12', 8413), ('07', 8989), ('01', 8273), ('11', 8243), ('06', 8677), ('02', 7093), ('03', 8289), ('08', 8783)]\n",
					"[('01', 8273), ('02', 7093), ('03', 8289), ('04', 8455), ('05', 8669), ('06', 8677), ('07', 8989), ('08', 8783), ('09', 8508), ('10', 8406), ('11', 8243), ('12', 8413)]\n"
				]
			}],
			"source": [
				"gundeaths_month_list = [(k, v) for k,v in gundeaths_month.items()]\n",
				"print(gundeaths_month_list)\n",
				"gundeaths_month_list_sorted = sorted(gundeaths_month_list)\n",
				"print(gundeaths_month_list_sorted)\n",
				"\n",
				"    "
			]
		},
		{
			"cell_type": "code",
			"execution_count": 7,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
					"name": "stdout",
					"output_type": "stream",
					"text": [
						"['01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '11', '12']\n",
						"[8273, 7093, 8289, 8455, 8669, 8677, 8989, 8783, 8508, 8406, 8243, 8413]\n"
					]
				},
				{
					"data": {
						"image/png": "iVBORw0KGgoAAAANSUhEUgAAAaQAAAE+CAYAAADCsWQQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
						"text/plain": [
							"<matplotlib.figure.Figure at 0x7f7af2815828>"
						]
					},
					"metadata": {},
					"output_type": "display_data"
				}
			],
			"source": [
				"x_gundeaths_month = []\n",
				"y_gundeaths_month = []\n",
				"for row in gundeaths_month_list_sorted:\n",
				"    x_gundeaths_month.append(row[0])\n",
				"    y_gundeaths_month.append(row[1])\n",
				"\n",
				"print(x_gundeaths_month)\n",
				"print(y_gundeaths_month)\n",
				"\n",
				"plt.plot(x_gundeaths_month, y_gundeaths_month, linestyle='solid', linewidth=3.0, color=\"red\")\n",
				"plt.title(\"Gundeaths by months \\n\", fontsize=14, color='black', weight = 'bold')\n",
				"plt.xlabel(\"Months \\n\",  fontsize=14, color='blue')\n",
				"plt.ylabel(\"Absolute number of gun deaths \\n\", fontsize=14, color='blue')\n",
				"plt.show()\n"
			]
		},
		{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
				"The gun death by mont has a low in February and peaks in July. Speculation: because it is cold in Feburary people are less outside and are less likely to be killed outside. Further investigation: this makes sense for homicides to a degree but does it also for suicide? Also temperature for the southern region are in February also higher. A seperation by \"cold\" and \"hot\" southern region could help to understand this. The differentitation between northern and southern region is not in the data set and has to be constructed with other sources if possible.\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 8,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"[datetime.datetime(2012, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0), datetime.datetime(2012, 1, 1, 0, 0), datetime.datetime(2012, 2, 1, 0, 0), datetime.datetime(2012, 2, 1, 0, 0)]\n",
					"[datetime.datetime(2014, 9, 1, 0, 0), datetime.datetime(2014, 9, 1, 0, 0), datetime.datetime(2014, 9, 1, 0, 0), datetime.datetime(2014, 9, 1, 0, 0), datetime.datetime(2014, 9, 1, 0, 0)]\n",
					"36\n",
					"2013-06-01 00:00:00 2920\n",
					"2014-11-01 00:00:00 2756\n",
					"2014-02-01 00:00:00 2361\n",
					"2013-11-01 00:00:00 2758\n",
					"2012-01-01 00:00:00 2758\n",
					"2012-08-01 00:00:00 2954\n"
				]
			}],
			"source": [
				"import datetime\n",
				"dates = [datetime.datetime(year=int(i[1]), month=int(i[2]), day=1) for i in data]\n",
				"print(dates[:5])\n",
				"len(dates)\n",
				"print(dates[90000:90005])\n",
				"date_counts = {}\n",
				"for date in dates:\n",
				"    if date in date_counts.keys():\n",
				"        date_counts[date] += 1\n",
				"    else:\n",
				"        date_counts[date] = 1\n",
				"print(len(date_counts))\n",
				"\n",
				"counter_5=0\n",
				"for key, value in date_counts.items():\n",
				"    print(key, value)\n",
				"    counter_5+=1\n",
				"    if counter_5 > 5:\n",
				"        break"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"['', 'year', 'month', 'intent', 'police', 'sex', 'age', 'race', 'hispanic', 'place', 'education']\n"
				]
			}],
			"source": [
				"print(headers)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 10,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
					"name": "stdout",
					"output_type": "stream",
					"text": [
						"{'M', 'F'}\n",
						"['M', 'F', 'M', 'M', 'M']\n",
						"dict_items([('M', 86349), ('F', 14449)])\n",
						"{'Asian/Pacific Islander', 'White', 'Native American/Native Alaskan', 'Black', 'Hispanic'}\n",
						"{'Black': 23296, 'Asian/Pacific Islander': 1326, 'White': 66237, 'Native American/Native Alaskan': 917, 'Hispanic': 9022}\n",
						"['M', 'F']\n"
					]
				},
				{
					"data": {
						"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAEyCAYAAAAsi33eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nREQs9/8AM56VShwYqgIAAAAASUVORK5CYII=\n",
						"text/plain": [
							"<matplotlib.figure.Figure at 0x7f7af074a208>"
						]
					},
					"metadata": {},
					"output_type": "display_data"
				},
				{
					"data": {
						"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAHLCAYAAAAeFjUPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nR9kAAKz7C2ktruIDsM8UAAAAAElFTkSuQmCC\n",
						"text/plain": [
							"<matplotlib.figure.Figure at 0x7f7af0271e80>"
						]
					},
					"metadata": {},
					"output_type": "display_data"
				}
			],
			"source": [
				"# sex: 5\n",
				"sex_column = []\n",
				"for i in data:\n",
				"    sex_column.append(i[5])\n",
				"    \n",
				"sex_column_set = set(sex_column)\n",
				"print(sex_column_set)\n",
				"\n",
				"sex_column_2 = [i[5] for i in data]\n",
				"print(sex_column_2[:5])\n",
				"\n",
				"sex_counts={}\n",
				"for sex in sex_column_2:\n",
				"    if sex in sex_counts.keys():\n",
				"        sex_counts[sex] += 1\n",
				"    else:\n",
				"        sex_counts[sex] = 1\n",
				"\n",
				"print(sex_counts.items())\n",
				"# race: 7 \n",
				"race_counts = {}\n",
				"race_column = [ i[7] for i in data]\n",
				"race_column_set = set(race_column)\n",
				"print(race_column_set)\n",
				"for race in race_column:\n",
				"    if race in race_counts.keys():\n",
				"        race_counts[race] += 1\n",
				"    else:\n",
				"        race_counts[race] = 1\n",
				"print(race_counts)\n",
				"        \n",
				"\n",
				"\n",
				"names_sex = list(sex_counts.keys())\n",
				"print(names_sex )\n",
				"values_sex = list(sex_counts.values())\n",
				"\n",
				"#tick_label does the some work as plt.xticks()\n",
				"plt.bar(range(len(sex_counts)),values_sex , tick_label=names_sex,  align='center', color=('green', 'red'))\n",
				"plt.xticks(rotation=90)\n",
				"plt.title(\"US gun deaths by gender \\n\")\n",
				"plt.xlabel(\"Gender \\n\")\n",
				"plt.ylabel(\"Number of deaths \\n\")\n",
				"plt.show()      \n",
				"\n",
				"name_race=race_counts.keys()\n",
				"values_race=race_counts.values()\n",
				"length_race=range(len(race_counts))\n",
				"\n",
				"plt.bar(length_race, values_race, tick_label=name_race, align=\"center\")\n",
				"plt.xticks(rotation=90)\n",
				"plt.title(\"US gun deaths by race \\n\")\n",
				"plt.xlabel(\"Races \\n\")\n",
				"plt.ylabel(\"Number of deaths \\n\")\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"[['Id', 'Year', 'Id', 'Sex', 'Id', 'Hispanic Origin', 'Id', 'Id2', 'Geography', 'Total', 'Race Alone - White', 'Race Alone - Hispanic', 'Race Alone - Black or African American', 'Race Alone - American Indian and Alaska Native', 'Race Alone - Asian', 'Race Alone - Native Hawaiian and Other Pacific Islander', 'Two or More Races'], ['cen42010', 'April 1, 2010 Census', 'totsex', 'Both Sexes', 'tothisp', 'Total', '0100000US', '', 'United States', '308745538', '197318956', '44618105', '40250635', '3739506', '15159516', '674625', '6984195']]\n"
				]
			}],
			"source": [
				"f = open(\"census.csv\", \"r\")\n",
				"csvfile = csv.reader(f)\n",
				"censusdata = list(csvfile)\n",
				"print(censusdata)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"dict_keys(['Black', 'Asian/Pacific Islander', 'White', 'Native American/Native Alaskan', 'Hispanic'])\n",
					"197318956\n",
					"44618105\n",
					"40250635\n",
					"3739506\n",
					"15159516\n",
					"674625\n",
					"15834141\n",
					"{'Native American/Native Alaskan': 3739506, 'Asian/Pacific Islander': 15834141, 'White': 197318956, 'Black': 40250635, 'Hispanic': 44618105}\n"
				]
			}],
			"source": [
				"mapping = {}\n",
				"\n",
				"print(race_counts.keys())\n",
				"\n",
				"censusdata_white = [ i[10] for i in censusdata]\n",
				"censusdata_white=int(censusdata_white[1])\n",
				"print(censusdata_white)\n",
				"censusdata_hispanic = [ i[11] for i in censusdata]\n",
				"censusdata_hispanic=int(censusdata_hispanic[1])\n",
				"print(censusdata_hispanic)\n",
				"censusdata_black = [ i[12] for i in censusdata]\n",
				"censusdata_black=int(censusdata_black[1])\n",
				"print(censusdata_black)\n",
				"censusdata_native = [ i[13] for i in censusdata]\n",
				"censusdata_native=int(censusdata_native[1])\n",
				"print(censusdata_native)\n",
				"censusdata_asian = [i[14] for i in censusdata]\n",
				"censusdata_asian=int(censusdata_asian[1])\n",
				"print(censusdata_asian)\n",
				"censusdata_hawai = [i[15] for i in censusdata]\n",
				"censusdata_hawai=int(censusdata_hawai[1])\n",
				"print(censusdata_hawai)\n",
				"asian_hawai = censusdata_hawai + censusdata_asian\n",
				"print(asian_hawai)\n",
				"\n",
				"mapping['White'] = censusdata_white\n",
				"mapping['Asian/Pacific Islander'] = asian_hawai\n",
				"mapping[ 'Black'] = censusdata_black \n",
				"mapping['Native American/Native Alaskan'] = censusdata_native\n",
				"mapping['Hispanic'] = censusdata_hispanic\n",
				"print(mapping)\n",
				"\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 13,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"{'Native American/Native Alaskan': 24.52, 'Asian/Pacific Islander': 8.37, 'White': 33.57, 'Black': 57.88, 'Hispanic': 20.22}\n"
				]
			}],
			"source": [
				"\n",
				"race_per_hundredk={}\n",
				"for i,v in race_counts.items():\n",
				"    for u,b in mapping.items():\n",
				"        if i == u:\n",
				"            rr=v/b*100000\n",
				"            race_per_hundredk[i]=round(rr,2)\n",
				"    \n",
				"print(race_per_hundredk)\n",
				"\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 14,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
					"name": "stdout",
					"output_type": "stream",
					"text": [
						"['Native American/Native Alaskan', 'Asian/Pacific Islander', 'White', 'Black', 'Hispanic']\n"
					]
				},
				{
					"data": {
						"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAHLCAYAAADSjw/kAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLFEQAABLFAQAwNJft6T9f5YYrmwAAAAASUVORK5CYII=\n",
						"text/plain": [
							"<matplotlib.figure.Figure at 0x7f7af07514e0>"
						]
					},
					"metadata": {},
					"output_type": "display_data"
				}
			],
			"source": [
				"\n",
				"from matplotlib import pyplot as plt\n",
				"%matplotlib inline\n",
				"\n",
				"names = list(race_per_hundredk.keys())\n",
				"print(names)\n",
				"values = list(race_per_hundredk.values())\n",
				"\n",
				"#tick_label does the some work as plt.xticks()\n",
				"plt.bar(range(len(race_per_hundredk)), values, tick_label=names,  align='center', color=('magenta', \"brown\"))\n",
				"plt.xticks(rotation=90)\n",
				"plt.title(\"US gun deaths grouped by race per 100.000 people \\n\")\n",
				"plt.xlabel(\"Races \\n\")\n",
				"plt.ylabel(\"Number of deaths per 100.000 \\n\")\n",
				"plt.show()\n",
				"\n",
				"    "
			]
		},
		{
			"cell_type": "code",
			"execution_count": 15,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"[['1', '2012', '01', 'Suicide', '0', 'M', '34', 'Asian/Pacific Islander', '100', 'Home', '4'], ['2', '2012', '01', 'Suicide', '0', 'F', '21', 'White', '100', 'Street', '3'], ['3', '2012', '01', 'Suicide', '0', 'M', '60', 'White', '100', 'Other specified', '4'], ['4', '2012', '02', 'Suicide', '0', 'M', '64', 'White', '100', 'Home', '4'], ['5', '2012', '02', 'Suicide', '0', 'M', '31', 'White', '100', 'Other specified', '2']]\n"
				]
			}],
			"source": [
				"print(data[:5])"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 16,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"Intents: ['Suicide', 'Suicide', 'Suicide', 'Suicide', 'Suicide', 'Suicide', 'Undetermined', 'Suicide', 'Accidental', 'Suicide', 'Suicide', 'Suicide', 'Suicide', 'Suicide', 'Homicide', 'Suicide', 'Suicide', 'Suicide', 'Homicide', 'Suicide']\n",
					"Length of intents: 100798\n",
					"[(0, 'Suicide'), (1, 'Suicide'), (2, 'Suicide'), (3, 'Suicide'), (4, 'Suicide'), (5, 'Suicide'), (6, 'Undetermined'), (7, 'Suicide'), (8, 'Accidental'), (9, 'Suicide')]\n"
				]
			}],
			"source": [
				"\n",
				"intents = [ i[3] for i in data]\n",
				"\n",
				"print(\"Intents: {}\".format(intents[:20]))\n",
				"print(\"Length of intents: {}\".format(len(intents)))\n",
				"\n",
				"intent_enumerate_list =[]\n",
				"for i,value in enumerate(intents):\n",
				"    intent_enumerate_list.append((i,value))\n",
				"print(intent_enumerate_list[:10])"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 17,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"DATA: ['1', '2012', '01', 'Suicide', '0', 'M', '34', 'Asian/Pacific Islander', '100', 'Home', '4']\n"
				]
			}],
			"source": [
				"print(\"DATA: {}\".format(data[0]))"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 18,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
					"name": "stdout",
					"output_type": "stream",
					"text": [
						"Count Death Types: {'Homicide': 35176, 'Undetermined': 807, 'Accidental': 1639, 'Suicide': 63175, 'NA': 1}\n"
					]
				},
				{
					"data": {
						"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAFxCAYAAAClRwUcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIpb7/wlyx1FtDQ7DAAAAAElFTkSuQmCC\n",
						"text/plain": [
							"<matplotlib.figure.Figure at 0x7f7af01c27b8>"
						]
					},
					"metadata": {},
					"output_type": "display_data"
				}
			],
			"source": [
				"count_death_types = {}\n",
				"\n",
				"for i in intents:\n",
				"    if i in count_death_types.keys():\n",
				"        count_death_types[i] += 1\n",
				"    else:\n",
				"        count_death_types[i] = 1\n",
				"\n",
				"print(\"Count Death Types: {}\".format(count_death_types))\n",
				"\n",
				"\n",
				"names_count_death_types = count_death_types.keys()\n",
				"values_count_death_types = count_death_types.values()\n",
				"range_count_death_types = range(len(count_death_types))\n",
				"\n",
				"plt.bar(range_count_death_types, values_count_death_types, \n",
				"        tick_label=names_count_death_types , align=\"center\" , \n",
				"        color=(\"black\", \"red\"))\n",
				"plt.title(\"Death types numbers \\n\")\n",
				"plt.xlabel(\"Death types \\n\")\n",
				"plt.ylabel(\"Numbers \\n\")\n",
				"plt.xticks(rotation=90)\n",
				"plt.show()\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"data": {
					"image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
					"text/plain": [
						"<matplotlib.figure.Figure at 0x7f7af0716470>"
					]
				},
				"metadata": {},
				"output_type": "display_data"
			}],
			"source": [
				"explode =  (0.1, 0, 0, 0, 0)\n",
				"plt.pie(list(values_count_death_types),  autopct='%1.1f%%', \n",
				"        shadow=True, startangle=140, explode=explode, pctdistance= 0.3, labeldistance=1.4)\n",
				"plt.title(\"Death types numbers \\n\")\n",
				"plt.legend(names_count_death_types , loc=1)\n",
				"plt.axis('equal')\n",
				"\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 20,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"Number of homicides: 35176\n"
				]
			}],
			"source": [
				"\n",
				"homicides= 0\n",
				"for i in intents:\n",
				"    if i == 'Homicide':\n",
				"        homicides += 1\n",
				"print(\"Number of homicides: {}\".format(homicides))"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"Races: ['Asian/Pacific Islander', 'White', 'White', 'White', 'White', 'Native American/Native Alaskan', 'White', 'Native American/Native Alaskan', 'White', 'Black']\n",
					"Count races_2: 100798\n",
					"Count intents: 100798\n"
				]
			}],
			"source": [
				"races_2=[ i[7]  for i in data]\n",
				"\n",
				"print(\"Races: {}\".format(races_2[:10]))\n",
				"print(\"Count races_2: {}\".format(len(races_2)))\n",
				"print(\"Count intents: {}\".format(len(intents)))\n",
				"\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"orangered #FF4500\n",
					"cyan #00FFFF\n",
					"salmon #FA8072\n",
					"springgreen #00FF7F\n",
					"darkolivegreen #556B2F\n",
					"tan #D2B48C\n",
					"darkcyan #008B8B\n",
					"hotpink #FF69B4\n",
					"skyblue #87CEEB\n",
					"darkblue #00008B\n",
					"grey #808080\n",
					"lightgoldenrodyellow #FAFAD2\n",
					"ghostwhite #F8F8FF\n",
					"lightslategrey #778899\n",
					"blanchedalmond #FFEBCD\n",
					"palegreen #98FB98\n",
					"sage #87AE73\n",
					"lavender #E6E6FA\n",
					"paleturquoise #AFEEEE\n",
					"darkviolet #9400D3\n",
					"red #FF0000\n",
					"dodgerblue #1E90FF\n",
					"indianred #CD5C5C\n",
					"seagreen #2E8B57\n",
					"sandybrown #FAA460\n",
					"bisque #FFE4C4\n",
					"orchid #DA70D6\n",
					"lemonchiffon #FFFACD\n",
					"silver #C0C0C0\n",
					"gainsboro #DCDCDC\n",
					"dimgrey #696969\n",
					"blueviolet #8A2BE2\n",
					"darksalmon #E9967A\n",
					"lightskyblue #87CEFA\n",
					"purple #800080\n",
					"darkslateblue #483D8B\n",
					"honeydew #F0FFF0\n",
					"darkorange #FF8C00\n",
					"violet #EE82EE\n",
					"aliceblue #F0F8FF\n",
					"darkslategray #2F4F4F\n",
					"plum #DDA0DD\n",
					"lime #00FF00\n",
					"aquamarine #7FFFD4\n",
					"darkkhaki #BDB76B\n",
					"lightseagreen #20B2AA\n",
					"blue #0000FF\n",
					"cadetblue #5F9EA0\n",
					"cornflowerblue #6495ED\n",
					"darksage #598556\n",
					"palegoldenrod #EEE8AA\n",
					"black #000000\n",
					"pink #FFC0CB\n",
					"darkgoldenrod #B8860B\n",
					"lightpink #FFB6C1\n",
					"thistle #D8BFD8\n",
					"darkgrey #A9A9A9\n",
					"darkgreen #006400\n",
					"mistyrose #FFE4E1\n",
					"ivory #FFFFF0\n",
					"deepskyblue #00BFFF\n",
					"darkslategrey #2F4F4F\n",
					"steelblue #4682B4\n",
					"deeppink #FF1493\n",
					"oldlace #FDF5E6\n",
					"lightsage #BCECAC\n",
					"chartreuse #7FFF00\n",
					"lightsteelblue #B0C4DE\n",
					"lightgrey #D3D3D3\n",
					"gold #FFD700\n",
					"yellow #FFFF00\n",
					"mintcream #F5FFFA\n",
					"mediumblue #0000CD\n",
					"darkturquoise #00CED1\n",
					"darkorchid #9932CC\n",
					"mediumpurple #9370DB\n",
					"lightyellow #FFFFE0\n",
					"khaki #F0E68C\n",
					"whitesmoke #F5F5F5\n",
					"green #008000\n",
					"moccasin #FFE4B5\n",
					"magenta #FF00FF\n",
					"turquoise #40E0D0\n",
					"mediumvioletred #C71585\n",
					"rosybrown #BC8F8F\n",
					"orange #FFA500\n",
					"lawngreen #7CFC00\n",
					"saddlebrown #8B4513\n",
					"teal #008080\n",
					"mediumspringgreen #00FA9A\n",
					"lightblue #ADD8E6\n",
					"slategray #708090\n",
					"peru #CD853F\n",
					"beige #F5F5DC\n",
					"tomato #FF6347\n",
					"darkmagenta #8B008B\n",
					"antiquewhite #FAEBD7\n",
					"white #FFFFFF\n",
					"mediumturquoise #48D1CC\n",
					"greenyellow #ADFF2F\n",
					"floralwhite #FFFAF0\n",
					"darkseagreen #8FBC8F\n",
					"linen #FAF0E6\n",
					"papayawhip #FFEFD5\n",
					"goldenrod #DAA520\n",
					"mediumslateblue #7B68EE\n",
					"lightgray #D3D3D3\n",
					"olive #808000\n",
					"navy #000080\n",
					"lightcyan #E0FFFF\n",
					"lavenderblush #FFF0F5\n",
					"powderblue #B0E0E6\n",
					"mediumorchid #BA55D3\n",
					"limegreen #32CD32\n",
					"indigo #4B0082\n",
					"palevioletred #DB7093\n",
					"lightslategray #778899\n",
					"slategrey #708090\n",
					"coral #FF7F50\n",
					"midnightblue #191970\n",
					"slateblue #6A5ACD\n",
					"firebrick #B22222\n",
					"lightgreen #90EE90\n",
					"lightsalmon #FFA07A\n",
					"darkgray #A9A9A9\n",
					"mediumseagreen #3CB371\n",
					"brown #A52A2A\n",
					"royalblue #4169E1\n",
					"dimgray #696969\n",
					"seashell #FFF5EE\n",
					"cornsilk #FFF8DC\n",
					"mediumaquamarine #66CDAA\n",
					"azure #F0FFFF\n",
					"lightcoral #F08080\n",
					"crimson #DC143C\n",
					"forestgreen #228B22\n",
					"yellowgreen #9ACD32\n",
					"gray #808080\n",
					"sienna #A0522D\n",
					"wheat #F5DEB3\n",
					"snow #FFFAFA\n",
					"peachpuff #FFDAB9\n",
					"aqua #00FFFF\n",
					"maroon #800000\n",
					"fuchsia #FF00FF\n",
					"darkred #8B0000\n",
					"olivedrab #6B8E23\n",
					"chocolate #D2691E\n",
					"navajowhite #FFDEAD\n",
					"burlywood #DEB887\n"
				]
			}],
			"source": [
				"import matplotlib\n",
				"for name, hex in matplotlib.colors.cnames.items():\n",
				"    print(name, hex)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 23,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"{'Native American/Native Alaskan': 326, 'Asian/Pacific Islander': 559, 'White': 9147, 'Black': 19510, 'Hispanic': 5634}\n"
				]
			}],
			"source": [
				"\n",
				"\n",
				"homicide_race_counts = {}\n",
				"\n",
				"\n",
				"for e,race in enumerate(races_2):\n",
				"    if intents[e] == \"Homicide\":\n",
				"        if race in homicide_race_counts.keys():\n",
				"            homicide_race_counts[race]+=1\n",
				"        else:\n",
				"            homicide_race_counts[race]=1\n",
				"\n",
				"print(homicide_race_counts)\n",
				"\n",
				"\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 24,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"data": {
					"image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAG/CAYAAACOpXrYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
					"text/plain": [
						"<matplotlib.figure.Figure at 0x7f7af0284c18>"
					]
				},
				"metadata": {},
				"output_type": "display_data"
			}],
			"source": [
				"homicide_race_counts_name = homicide_race_counts.keys()\n",
				"homicide_race_counts_values = homicide_race_counts.values()\n",
				"homicide_race_counts_range = range(len(homicide_race_counts))\n",
				"\n",
				"plt.bar(homicide_race_counts_range, homicide_race_counts_values, \n",
				"        tick_label=homicide_race_counts_name, align='center',\n",
				"       color=('darkgoldenrod', 'maroon'))\n",
				"plt.xticks(rotation=90)\n",
				"plt.title('Homicide counts absolute grouped by race \\n')\n",
				"plt.xlabel('Race')\n",
				"plt.ylabel('Absolute number \\n')\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 25,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"data": {
					"image/png": "iVBORw0KGgoAAAANSUhEUgAAAbEAAAD2CAYAAABY+rnRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n3NzZWAAAAABJRU5ErkJggg==\n",
					"text/plain": [
						"<matplotlib.figure.Figure at 0x7f7af07ad908>"
					]
				},
				"metadata": {},
				"output_type": "display_data"
			}],
			"source": [
				"explode =  (0, 0, 0.1, 0, 0)\n",
				"plt.pie(list(homicide_race_counts_values ), labels=homicide_race_counts_name,  autopct='%1.1f%%', \n",
				"        shadow=True, startangle=140, explode=explode)\n",
				"plt.axis('equal')\n",
				"\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 26,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"{'Native American/Native Alaskan': 3739506, 'Asian/Pacific Islander': 15834141, 'White': 197318956, 'Black': 40250635, 'Hispanic': 44618105}\n",
					"{'Native American/Native Alaskan': 326, 'Asian/Pacific Islander': 559, 'White': 9147, 'Black': 19510, 'Hispanic': 5634}\n"
				]
			}],
			"source": [
				"print(mapping)\n",
				"print(homicide_race_counts)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 27,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"{'Black': 48.47, 'Asian/Pacific Islander': 3.53, 'White': 4.64, 'Native American/Native Alaskan': 8.72, 'Hispanic': 12.63}\n"
				]
			}],
			"source": [
				"homicide_race_counts_per_hundredk={}\n",
				"\n",
				"for i,v in homicide_race_counts.items():\n",
				"    for u,b in mapping.items():\n",
				"        if i == u:\n",
				"            rr=v/b*100000\n",
				"            homicide_race_counts_per_hundredk[i]=round(rr,2)\n",
				"    \n",
				"print(homicide_race_counts_per_hundredk)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 28,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"data": {
					"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAG/CAYAAABCPEAzAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQUREGrEgiIhIo/8H/rH/HJbP4eYAAAAASUVORK5CYII=\n",
					"text/plain": [
						"<matplotlib.figure.Figure at 0x7f7aef8b4a58>"
					]
				},
				"metadata": {},
				"output_type": "display_data"
			}],
			"source": [
				"homicide_race_counts_per_hundredk_name = homicide_race_counts_per_hundredk.keys()\n",
				"homicide_race_counts_per_hundredk_values = homicide_race_counts_per_hundredk.values()\n",
				"homicide_race_counts_per_hundredk_range = range(len(homicide_race_counts_per_hundredk))\n",
				"\n",
				"plt.bar(homicide_race_counts_per_hundredk_range, homicide_race_counts_per_hundredk_values, \n",
				"        tick_label=homicide_race_counts_per_hundredk_name , align='center',\n",
				"       color=('seagreen', 'palevioletred'))\n",
				"plt.xticks(rotation=90)\n",
				"plt.title('Homicide per hundredk grouped by race in % \\n')\n",
				"plt.xlabel('Race')\n",
				"plt.ylabel('Relative number (%) \\n')\n",
				"plt.show()"
			]
		},
		{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
				"collapsed": true
			},
			"outputs": [],
			"source": []
		},
		{
			"cell_type": "code",
			"execution_count": 29,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"['', 'year', 'month', 'intent', 'police', 'sex', 'age', 'race', 'hispanic', 'place', 'education']\n"
				]
			}],
			"source": [
				"print(headers)"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 30,
			"metadata": {
				"collapsed": true
			},
			"outputs": [],
			"source": [
				"import numpy as np\n",
				"from sklearn import datasets, linear_model\n",
				"from sklearn.metrics import mean_squared_error, r2_score\n",
				"import pandas as pd"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 31,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"      year month   intent police sex age                    race hispanic  \\\n",
					"0  1  2012    01  Suicide      0   M  34  Asian/Pacific Islander      100   \n",
					"1  2  2012    01  Suicide      0   F  21                   White      100   \n",
					"2  3  2012    01  Suicide      0   M  60                   White      100   \n",
					"3  4  2012    02  Suicide      0   M  64                   White      100   \n",
					"4  5  2012    02  Suicide      0   M  31                   White      100   \n",
					"\n",
					"             place education  \n",
					"0             Home         4  \n",
					"1           Street         3  \n",
					"2  Other specified         4  \n",
					"3             Home         4  \n",
					"4  Other specified         2  \n",
					"                year month    intent police sex age      race hispanic  \\\n",
					"100793  100794  2014    12  Homicide      0   M  36     Black      100   \n",
					"100794  100795  2014    12  Homicide      0   M  19     Black      100   \n",
					"100795  100796  2014    12  Homicide      0   M  20     Black      100   \n",
					"100796  100797  2014    12  Homicide      0   M  22  Hispanic      260   \n",
					"100797  100798  2014    10  Homicide      0   M  43     Black      100   \n",
					"\n",
					"                    place education  \n",
					"100793               Home         2  \n",
					"100794             Street         2  \n",
					"100795             Street         2  \n",
					"100796             Street         1  \n",
					"100797  Other unspecified         2  \n",
					"                  year   month   intent  police     sex     age    race  \\\n",
					"count   100798  100798  100798   100798  100798  100798  100798  100798   \n",
					"unique  100798       3      12        5       2       2     105       5   \n",
					"top      50194    2013      07  Suicide       0       M      22   White   \n",
					"freq         1   33636    8989    63175   99396   86349    2712   66237   \n",
					"\n",
					"       hispanic   place education  \n",
					"count    100798  100798    100798  \n",
					"unique       39      11         6  \n",
					"top         100    Home         2  \n",
					"freq      91467   60486     42927  \n"
				]
			}],
			"source": [
				"df=pd.DataFrame(data, columns=headers)\n",
				"print(df.head())\n",
				"print(df.tail())\n",
				"print(df.describe())"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 32,
			"metadata": {
				"collapsed": false
			},
			"outputs": [],
			"source": [
				"df_itent_race=df.iloc[:,[3,7]]\n",
				"\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 33,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"    intent                    race\n",
					"0  Suicide  Asian/Pacific Islander\n",
					"1  Suicide                   White\n",
					"2  Suicide                   White\n",
					"3  Suicide                   White\n",
					"4  Suicide                   White\n"
				]
			}],
			"source": [
				"print(df_itent_race.head())"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 34,
			"metadata": {
				"collapsed": false
			},
			"outputs": [],
			"source": [
				"\n",
				"df_itent_race_2 = []\n",
				"for i, row in df_itent_race.iterrows():\n",
				"    if df_itent_race.loc[i, 'intent'] == \"Homicide\":\n",
				"        \n",
				"        df_itent_race_2.append(1) \n",
				"\n",
				"    else:\n",
				"        \n",
				"        df_itent_race_2.append(0) \n",
				"    \n",
				"    "
			]
		},
		{
			"cell_type": "code",
			"execution_count": 35,
			"metadata": {
				"collapsed": false
			},
			"outputs": [],
			"source": [
				"df_itent_race.is_copy = False\n",
				"df_itent_race[\"Dummy\"] = df_itent_race_2\n"
			]
		},
		{
			"cell_type": "code",
			"execution_count": 36,
			"metadata": {
				"collapsed": false
			},
			"outputs": [{
				"name": "stdout",
				"output_type": "stream",
				"text": [
					"          intent                            race  Dummy\n",
					"0        Suicide          Asian/Pacific Islander      0\n",
					"1        Suicide                           White      0\n",
					"2        Suicide                           White      0\n",
					"3        Suicide                           White      0\n",
					"4        Suicide                           White      0\n",
					"5        Suicide  Native American/Native Alaskan      0\n",
					"6   Undetermined                           White      0\n",
					"7        Suicide  Native American/Native Alaskan      0\n",
					"8     Accidental                           White      0\n",
					"9        Suicide                           Black      0\n",
					"10       Suicide                           White      0\n",
					"11       Suicide  Native American/Native Alaskan      0\n",
					"12       Suicide                           White      0\n",
					"13       Suicide  Native American/Native Alaskan      0\n",
					"14      Homicide                           White      1\n",
					"15       Suicide  Native American/Native Alaskan      0\n",
					"16       Suicide                           White      0\n",
					"17       Suicide  Native American/Native Alaskan      0\n",
					"18      Homicide          Asian/Pacific Islander      1\n",
					"19       Suicide                           White      0\n",
					"20       Suicide  Native American/Native Alaskan      0\n",
					"21       Suicide                           White      0\n",
					"22      Homicide                           Black      1\n",
					"23       Suicide                           White      0\n",
					"24      Homicide                           White      1\n",
					"25      Homicide                           White      1\n",
					"26       Suicide  Native American/Native Alaskan      0\n",
					"27       Suicide                           White      0\n",
					"28       Suicide                           White      0\n",
					"29      Homicide                           White      1\n",
					"30       Suicide  Native American/Native Alaskan      0\n",
					"31       Suicide                           White      0\n",
					"32       Suicide  Native American/Native Alaskan      0\n",
					"33       Suicide                           White      0\n",
					"34      Homicide                           White      1\n",
					"35  Undetermined                           White      0\n",
					"36       Suicide  Native American/Native Alaskan      0\n",
					"37       Suicide  Native American/Native Alaskan      0\n",
					"38       Suicide                           White      0\n",
					"39       Suicide                           White      0\n",
					"40       Suicide  Native American/Native Alaskan      0\n",
					"41      Homicide          Asian/Pacific Islander      1\n",
					"42       Suicide                           White      0\n",
					"43       Suicide  Native American/Native Alaskan      0\n",
					"44       Suicide  Native American/Native Alaskan      0\n",
					"45       Suicide                           White      0\n",
					"46       Suicide                           White      0\n",
					"47      Homicide                           White      1\n",
					"48      Homicide  Native American/Native Alaskan      1\n",
					"49      Homicide          Asian/Pacific Islander      1\n"
				]
			}],
			"source": [
				"print(df_itent_race[:50])  "
			]
		},
		{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {
				"collapsed": true
			},
			"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": "3.4.3"
		}
	},
	"nbformat": 4,
	"nbformat_minor": 0
}