Exploratory Data Analysis
Gun Violence Exploratory Data Analysis
Introduction
Gun violence in the United States is an, unfortunately, common topic of the news, with occurrences happening near daily. With the high frequency of events, many datasets tracking the violence exist.
This project uses one of those datasets[1] and aims to uncover any prevailing trends of gun violence in the U.S. To do so, I have used python with some supporting libraries to both explore and visualize the data.
My analysis is organized as follows:
- Imports and Data Cleaning
- Questions to Explore
- Time Related Gun Violence Trends
- Location Related Gun Violence Trends
- Demographic Related Gun Violence Trends
- Other Gun Violence Trends
- Concluding Remarks
- Notes and Resources
Imports and Data Cleaning
As with any project, the first thing to do is import all the libraries necessary to complete the analysis.
I have primarily chosen to use plotly[2] for making charts and visualization because I find it much easier and more expansive than the more traditional pyplot or seaborn libraries.
Furthermore, plotly graphs are automatically interactive.
import jovian
import pandas as pd
import numpy as np
import plotly.graph_objects as go
from plotly.offline import init_notebook_mode, iplot
import folium
import collections
import matplotlib.pyplot as plt
from PIL import Image
from wordcloud import WordCloud, STOPWORDS
init_notebook_mode(connected=True)