def find_national_drugs():
getAll = drugs.get_reports()
returnVal = { }
for year in range(2002, 2015, 1):
itemDict = {}
itemDict['Sums'] = { }
itemDict['Sums']['Marijuana'] = 0
itemDict['Sums']['Illicit Drugs'] = 0
itemDict['Sums']['Alcohol'] = 0
itemDict['Sums']['Population'] = 0
itemDict['Rates'] = { }
itemDict['Rates']['Marijuana'] = 0
itemDict['Rates']['Illicit Drugs'] = 0
itemDict['Rates']['Alcohol'] = 0
returnVal[ str(year) ] = itemDict
for item in getAll:
itemDict = returnVal[ str(item['Year']) ]
itemDict['Sums']['Marijuana'] += item['Totals']['Marijuana']['Used Past Year']['12-17']*10
itemDict['Sums']['Illicit Drugs'] += item['Totals']['Illicit Drugs']['Dependence Past Year']['12-17']*10
itemDict['Sums']['Alcohol'] += item['Totals']['Alcohol']['Dependence Past Year']['12-17']*10
itemDict['Sums']['Population'] += item['Population']['12-17']
for key in returnVal.keys():
itemDict = returnVal[key]
itemDict['Rates']['Marijuana'] = round( itemDict['Sums']['Marijuana'] * 10000.0 / itemDict['Sums']['Population'] ) / 100
itemDict['Rates']['Illicit Drugs'] = round( itemDict['Sums']['Illicit Drugs'] * 10000.0 / itemDict['Sums']['Population'] ) / 100
itemDict['Rates']['Alcohol'] = round( itemDict['Sums']['Alcohol'] * 10000.0 / itemDict['Sums']['Population'] ) / 100
return returnVal
def find_state_drugs( code ):
state = ""
for stateName, cde in state_codes.items():
if cde == code:
state = stateName
getAll = drugs.get_reports()
returnVal = { }
for year in range(2002, 2015, 1):
itemDict = {}
returnVal[ str(year) ] = itemDict
for item in getAll:
if item['State'] == state:
itemDict = returnVal[ str(item['Year']) ]
itemDict['Rates'] = {}
itemDict['Rates']['Marijuana'] = item['Rates']['Marijuana']['Used Past Year']['12-17']
itemDict['Rates']['Illicit Drugs'] = item['Rates']['Illicit Drugs']['Dependence Past Year']['12-17']
itemDict['Rates']['Alcohol'] = item['Rates']['Alcohol']['Dependence Past Year']['12-17']
return returnVal
'Washington': 'WA',
'North Carolina': 'NC',
'Maine': 'ME',
'New York': 'NY',
'Montana': 'MT',
'Nevada': 'NV',
'Delaware': 'DE',
'District of Columbia': 'DC'
}
def get_state_codes():
return state_codes
#---------------------------DRUG STUFF------------------------------------
states_drugs = drugs.get_reports()
def convert_drugs():
overall = {}
for state in states_drugs:
name = state_codes[state['State']]
if not name in overall.keys():
overall[name] = {}
weighted_data = [state['Totals']['Marijuana']['Used Past Year']['12-17']*1000,
state['Totals']['Pain Relievers Abuse Past Year']['12-17']*1000,
state['Totals']['Illicit Drugs']['Dependence Past Year']['12-17']*1000,
state['Totals']['Alcohol']['Dependence Past Year']['12-17']*1000]
overall[name][str(state['Year'])] = weighted_data
return overall
import drugs
import matplotlib.pyplot as plt
import math
import numpy as np
list_of_report = drugs.get_reports()
def makeAvg(list):
sum = 0
for x in range(len(list)):
sum += list[x]
average = sum / len(list)
return average
mari = []
ageRange26mari = []
for n in list_of_report:
ageRange26mari.append(n["Totals"]["Marijuana"]["Used Past Month"]["26+"])
avg1 = makeAvg(ageRange26mari)
mari.append(avg1)
ageRange1825mari = []
for n in list_of_report:
ageRange1825mari.append(
n["Totals"]["Marijuana"]["Used Past Month"]["18-25"])
avg2 = makeAvg(ageRange1825mari)
mari.append(avg2)
ageRange1217mari = []
import drugs
import matplotlib.pyplot as plt
plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt
listofreports = drugs.get_reports()
# based on age group, how many people have been dependent on alcohol in the past year?
for f in listofreports:
oldest_group = f["Totals"]["Alcohol"]["Dependence Past Year"]["26+"]
mid_group = f["Totals"]["Alcohol"]["Dependence Past Year"]["18-25"]
young_group = f["Totals"]["Alcohol"]["Dependence Past Year"]["12-17"]
objects = ['12-17 years old', '18-25 years old', '26+ years old']
x_pos = np.arange(len(objects))
values = [young_group, mid_group, oldest_group]
clr = '#F09D00'
labels = ['99', '400', '1200']
for i in range(len(x_pos)):
plt.text(x=x_pos[i] - 0.1, y=values[i], s=labels[i], size=9)
plt.bar(x_pos, values, align='center', color=clr)
plt.xticks(x_pos, objects)
plt.ylabel('# of people (in thousands)')
plt.xlabel('age group')
plt.title('Alcoholism in the Past Year')
plt.show()
from course import corgis
import drugs
data = drugs.get_reports()
data = corgis.data2frame(data)
data.to_csv('drugs.csv', index=False)