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data_manipulation
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data_manipulation
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from pprint import pprint"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"us_state_abbrev = {\n",
" 'Alabama': 'AL',\n",
" 'Alaska': 'AK',\n",
" 'American Samoa': 'AS',\n",
" 'Arizona': 'AZ',\n",
" 'Arkansas': 'AR',\n",
" 'California': 'CA',\n",
" 'Colorado': 'CO',\n",
" 'Connecticut': 'CT',\n",
" 'Delaware': 'DE',\n",
" 'District of Columbia': 'DC',\n",
" 'Florida': 'FL',\n",
" 'Georgia': 'GA',\n",
" 'Guam': 'GU',\n",
" 'Hawaii': 'HI',\n",
" 'Idaho': 'ID',\n",
" 'Illinois': 'IL',\n",
" 'Indiana': 'IN',\n",
" 'Iowa': 'IA',\n",
" 'Kansas': 'KS',\n",
" 'Kentucky': 'KY',\n",
" 'Louisiana': 'LA',\n",
" 'Maine': 'ME',\n",
" 'Maryland': 'MD',\n",
" 'Massachusetts': 'MA',\n",
" 'Michigan': 'MI',\n",
" 'Minnesota': 'MN',\n",
" 'Mississippi': 'MS',\n",
" 'Missouri': 'MO',\n",
" 'Montana': 'MT',\n",
" 'Nebraska': 'NE',\n",
" 'Nevada': 'NV',\n",
" 'New Hampshire': 'NH',\n",
" 'New Jersey': 'NJ',\n",
" 'New Mexico': 'NM',\n",
" 'New York': 'NY',\n",
" 'North Carolina': 'NC',\n",
" 'North Dakota': 'ND',\n",
" 'Northern Mariana Islands':'MP',\n",
" 'Ohio': 'OH',\n",
" 'Oklahoma': 'OK',\n",
" 'Oregon': 'OR',\n",
" 'Pennsylvania': 'PA',\n",
" 'Puerto Rico': 'PR',\n",
" 'Rhode Island': 'RI',\n",
" 'South Carolina': 'SC',\n",
" 'South Dakota': 'SD',\n",
" 'Tennessee': 'TN',\n",
" 'Texas': 'TX',\n",
" 'Utah': 'UT',\n",
" 'Vermont': 'VT',\n",
" 'Virgin Islands': 'VI',\n",
" 'Virginia': 'VA',\n",
" 'Washington': 'WA',\n",
" 'West Virginia': 'WV',\n",
" 'Wisconsin': 'WI',\n",
" 'Wyoming': 'WY'\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [],
"source": [
"gun_df = pd.read_csv(\"data/data_v2.csv\")\n",
"gun_df['STATE'] = gun_df['STATE'].map(us_state_abbrev).fillna(gun_df['STATE'])"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"gun_df.rename(columns={\"Cause of death\": \"cause_of_death\", \"Cause of death Code\": \"cod_code\"}, inplace=True)\n",
"df_rounded = gun_df.round(2)\n",
"df_rounded.to_csv('data/gun_data_v2.csv', index=False)\n"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" vertical-align: top;\n",
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" .dataframe thead th {\n",
" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>YEAR</th>\n",
" <th>STATE</th>\n",
" <th>HFR</th>\n",
" <th>HFR_se</th>\n",
" <th>universl</th>\n",
" <th>permit</th>\n",
" <th>Fem_FS_S</th>\n",
" <th>Male_FS_S</th>\n",
" <th>cause_of_death</th>\n",
" <th>cod_code</th>\n",
" <th>DEATHS</th>\n",
" <th>POPULATION</th>\n",
" <th>Crude Rate</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1999.0</td>\n",
" <td>AL</td>\n",
" <td>0.54</td>\n",
" <td>0.04</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>Discharge from other and unspecified firearms</td>\n",
" <td>W34</td>\n",
" <td>47.0</td>\n",
" <td>4430141.0</td>\n",
" <td>1.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1999.0</td>\n",
" <td>AL</td>\n",
" <td>0.54</td>\n",
" <td>0.04</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>Intentional self-harm by handgun discharge</td>\n",
" <td>X72</td>\n",
" <td>94.0</td>\n",
" <td>4430141.0</td>\n",
" <td>2.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1999.0</td>\n",
" <td>AL</td>\n",
" <td>0.54</td>\n",
" <td>0.04</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>Intentional self-harm by rifle, shotgun and la...</td>\n",
" <td>X73</td>\n",
" <td>63.0</td>\n",
" <td>4430141.0</td>\n",
" <td>1.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1999.0</td>\n",
" <td>AL</td>\n",
" <td>0.54</td>\n",
" <td>0.04</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>Intentional self-harm by other and unspecified...</td>\n",
" <td>X74</td>\n",
" <td>278.0</td>\n",
" <td>4430141.0</td>\n",
" <td>6.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1999.0</td>\n",
" <td>AL</td>\n",
" <td>0.54</td>\n",
" <td>0.04</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>Assault by handgun discharge</td>\n",
" <td>X93</td>\n",
" <td>37.0</td>\n",
" <td>4430141.0</td>\n",
" <td>0.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5127</th>\n",
" <td>2017.0</td>\n",
" <td>WY</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Intentional self-harm by rifle, shotgun and la...</td>\n",
" <td>X73</td>\n",
" <td>11.0</td>\n",
" <td>579315.0</td>\n",
" <td>Unreliable</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5128</th>\n",
" <td>2017.0</td>\n",
" <td>WY</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Intentional self-harm by other and unspecified...</td>\n",
" <td>X74</td>\n",
" <td>49.0</td>\n",
" <td>579315.0</td>\n",
" <td>8.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5129</th>\n",
" <td>2018.0</td>\n",
" <td>WY</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Intentional self-harm by handgun discharge</td>\n",
" <td>X72</td>\n",
" <td>37.0</td>\n",
" <td>577737.0</td>\n",
" <td>6.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5130</th>\n",
" <td>2018.0</td>\n",
" <td>WY</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Intentional self-harm by rifle, shotgun and la...</td>\n",
" <td>X73</td>\n",
" <td>12.0</td>\n",
" <td>577737.0</td>\n",
" <td>Unreliable</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5131</th>\n",
" <td>2018.0</td>\n",
" <td>WY</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Intentional self-harm by other and unspecified...</td>\n",
" <td>X74</td>\n",
" <td>59.0</td>\n",
" <td>577737.0</td>\n",
" <td>10.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5132 rows × 13 columns</p>\n",
"</div>"
],
"text/plain": [
" YEAR STATE HFR HFR_se universl permit Fem_FS_S Male_FS_S \\\n",
"0 1999.0 AL 0.54 0.04 0.0 0.0 0.7 0.8 \n",
"1 1999.0 AL 0.54 0.04 0.0 0.0 0.7 0.8 \n",
"2 1999.0 AL 0.54 0.04 0.0 0.0 0.7 0.8 \n",
"3 1999.0 AL 0.54 0.04 0.0 0.0 0.7 0.8 \n",
"4 1999.0 AL 0.54 0.04 0.0 0.0 0.7 0.8 \n",
"... ... ... ... ... ... ... ... ... \n",
"5127 2017.0 WY NaN NaN NaN NaN NaN NaN \n",
"5128 2017.0 WY NaN NaN NaN NaN NaN NaN \n",
"5129 2018.0 WY NaN NaN NaN NaN NaN NaN \n",
"5130 2018.0 WY NaN NaN NaN NaN NaN NaN \n",
"5131 2018.0 WY NaN NaN NaN NaN NaN NaN \n",
"\n",
" cause_of_death cod_code DEATHS \\\n",
"0 Discharge from other and unspecified firearms W34 47.0 \n",
"1 Intentional self-harm by handgun discharge X72 94.0 \n",
"2 Intentional self-harm by rifle, shotgun and la... X73 63.0 \n",
"3 Intentional self-harm by other and unspecified... X74 278.0 \n",
"4 Assault by handgun discharge X93 37.0 \n",
"... ... ... ... \n",
"5127 Intentional self-harm by rifle, shotgun and la... X73 11.0 \n",
"5128 Intentional self-harm by other and unspecified... X74 49.0 \n",
"5129 Intentional self-harm by handgun discharge X72 37.0 \n",
"5130 Intentional self-harm by rifle, shotgun and la... X73 12.0 \n",
"5131 Intentional self-harm by other and unspecified... X74 59.0 \n",
"\n",
" POPULATION Crude Rate \n",
"0 4430141.0 1.1 \n",
"1 4430141.0 2.1 \n",
"2 4430141.0 1.4 \n",
"3 4430141.0 6.3 \n",
"4 4430141.0 0.8 \n",
"... ... ... \n",
"5127 579315.0 Unreliable \n",
"5128 579315.0 8.5 \n",
"5129 577737.0 6.4 \n",
"5130 577737.0 Unreliable \n",
"5131 577737.0 10.2 \n",
"\n",
"[5132 rows x 13 columns]"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_rounded"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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