#!/usr/bin/env python
# coding: utf-8

# # *Exploring Gun Deaths in US*
# 
# ### The Dataset
# > The dataset for Gun Deaths in US came from [**FiveThirtyEight**](https://fivethirtyeight.com).<br>It contains information on gun deaths in the US from 2012 to 2014, which can be read [here](https://github.com/fivethirtyeight/guns-data).
# 
# ***This Project covers topics like reading Data from `CSV Module` and `Datetime Module`.<br>Here, we will find Gun Deaths per Month, Gender, Ethnicity and Intent.***

# ### Exploring Data

# In[1]:


import csv
data = list(csv.reader(open("guns.csv", "r")))
data[:5]


# ### Sepearting Data and Header

# In[2]:


headers = data[0]
data = data[1:]
print(headers)
data[:5]


# ### Death Rate Per Year

# In[3]:


year_counts = {}
for i in data:
    years = i[1]
    if years in year_counts:
        year_counts[years] += 1
    else:
        year_counts[years] = 1

year_counts


# ### Converting Date's Data type from String  to Datetime. <br><br> Death Rate Per Date

# In[4]:


import datetime
dates = [datetime.datetime(year = int(i[1]), month = int(i[2]), day = 1) for i in data]
# print(dates[:5])

date_counts = {}
for i in dates:
    if i in date_counts:
        date_counts[i] += 1
    else:
        date_counts[i] = 1

date_counts    


# ### Death Rate Per Gender

# In[9]:


sex_counts = {}

sex = [i[5] for i in data]
for i in sex:
    if i in sex_counts:
        sex_counts[i] += 1
    else:
        sex_counts[i] = 1

sex_counts 


# ### Death Rate Per Race

# In[6]:


race_counts = {}

race = [i[7] for i in data]
for i in race:
    if i in race_counts:
        race_counts[i] += 1
    else:
        race_counts[i] = 1

race_counts


# ### Death Rate Per Intent

# In[5]:


intent_counts = {}

intent_data = [i[3] for i in data]
for i in intent_data:
    if i in intent_counts:
        intent_counts[i] += 1
    else:
        intent_counts[i] = 1

intent_counts


# ### Exploring Data from Census.csv

# In[13]:


census = list(csv.reader(open("census.csv", "r")))
census


# ### Total Population per Race

# In[14]:


mapping = {'Asian/Pacific Islander': int(census[1][14]) + int(census[1][15]),
 'Black': int(census[1][12]),
 'Hispanic': int(census[1][11]),
 'Native American/Native Alaskan': int(census[1][13]),
 'White': int(census[1][10])}
mapping


# ### Death Rate Per Hundred Thousand Per Race

# In[9]:


race_per_hundredk = {}
for i in race_counts:
        race_per_hundredk[i] = round((race_counts[i]/mapping[i])*100000, 2)

race_per_hundredk


# ### Homicide Rate Per Hundred Thousand Per Race

# In[12]:


homicide_race_counts = {}
for i, race in enumerate(races):
    if intent_data[i] == "Homicide":
        if race in homicide_race_counts:
            homicide_race_counts[race] += 1
        else:
            homicide_race_counts[race] = 1

for i in homicide_race_counts:
    homicide_race_counts[i] = round((homicide_race_counts[i]/mapping[i]) * 100000, 2)
    
homicide_race_counts