#Similar to function 1 this function uses the pandas library to read in CVS data

#After reading in said data, this function also maps the data to a bar graph, however this bar graph is composed of crime data in St. Louis from the year 2019-2020

import pandas as pd

import matplotlib.pyplot as plt

year = [2019, 2020]

month = 0

months = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September','October', 'November', 'December']

url_prefix = 'https://raw.githubusercontent.com/genericlastname/hackhpc-urban-renewal/master/'

tempCrimesarr1 = []

tempCrimesarr2 = []

crimesByYear = []

for x in year:

for m in months:

if x < 2020 and x >= 2019:

tempCrimesarr1.append(pd.read_csv("{}{}{}.CSV".format(url_prefix, m, x),encoding="latin-1"))

elif x == 2020:

tempCrimesarr2.append(pd.read_csv("{}{}{}.CSV".format(url_prefix, m, x),encoding="latin-1"))

month = 0

crimesByYear = [tempCrimesarr1, tempCrimesarr2]

print("This is for 2019\n", crimesByYear[0])

#print("This is for 2020\n", crimesByYear[1])

plt.bar(year, [len(crimesByYear[0]), len(crimesByYear[1])], color ='maroon', width = .4)

plt.xlabel("Year")

plt.ylabel("Number of Reported Crimes")

plt.title("Crimes Reported In St. Louis 2019-2020")