def test_line_plot(self):
cd = covid_main.get_covid_data()
cd = cd.loc[cd["location"] == "United States"]
covid_main.line_plot("TEST",
cd,
"date",
"new_cases",
country="United States")
self.assertEqual(os.path.exists("United States TEST.png"), True)
def main():
cd = covid_main.get_covid_data()
covid_main.create_cases_death_plots(cd, args.for_country, args.month, args.year)
covid_main.create_pie_plot(cd, args.month, args.year)
dd = dow_main.get_file()
dow_main.plots(args.ticker)
merged = pd.merge(cd, dd, on=["date"])
merged['new_deaths'] = merged['new_deaths'].replace(np.nan, 0)
merged['new_cases'] = merged['new_cases'].replace(np.nan, 0)
merged["norm_deaths"] = (merged["new_deaths"] - merged["new_deaths"].mean()) / (
merged["new_deaths"].max() - merged["new_deaths"].min())
merged["norm_cases"] = (merged["new_cases"] - merged["new_cases"].mean()) / (
merged["new_cases"].max() - merged["new_cases"].min())
merged["norm_volume"] = (merged["Volume"] - merged["Volume"].mean()) / (
merged["Volume"].max() - merged["Volume"].min())
fig, ax = plt.subplots(figsize=(12, 8))
ax.plot("date", "norm_deaths", data=merged, label='Covid Deaths')
ax.plot("date", "norm_volume", data=merged, label='Volume of DJI')
ax.set_title('Covid deaths Vs Volume of DJI', fontsize=20)
plt.xticks(rotation=60)
plt.legend()
plt.savefig(f"Deaths to Volume")
fig, ax = plt.subplots(figsize=(12, 8))
ax.plot("date", "norm_cases", data=merged, label='Covid Cases')
ax.plot("date", "norm_volume", data=merged, label='Volume of DJI')
ax.set_title('Covid cases Vs Volume of DJI', fontsize=20)
plt.xticks(rotation=60)
plt.legend()
plt.savefig(f"Cases to Volume")
merged["norm_price"] = (merged["Adj Close"] - merged["Adj Close"].mean()) / (
merged["Adj Close"].max() - merged["Adj Close"].min())
df = merged[merged['location'] == 'United States']
df1 = df[0:55]
df2 = df[55: 110]
df3 = df[110: 165]
df4 = df[165:220]
A = [max(df1["norm_cases"]), max(df2["norm_cases"]), max(df3["norm_cases"]), max(df4["norm_cases"])]
B = [max(df1["norm_volume"]), max(df2["norm_volume"]), max(df3["norm_volume"]), max(df4["norm_volume"])]
width = 0.27
N = 4
ind = np.arange(N)
fig = plt.figure(figsize=(12, 10))
ax = fig.add_subplot(111)
ax.bar(ind, A, width, label='Covid cases')
ax.bar(ind + width, B, width, label='Price of DJI')
ax.set_xticks(ind + width)
ax.set_xticklabels(('2020 Quarter 1', '2020 Quarter 2', '2020 Quarter 3', '2020 Quarter 4'), fontsize=10)
ax.legend(fontsize=20)
ax.set_title('2020 Quarterly relation between covid cases and DJI Price', fontsize=20)
plt.savefig('Cases Vs DJI Price')
covid_main.write_csv(cd, "covid_data.csv", "covid")
covid_main.write_csv(dd, "dow_data.csv", "dow")
def test_get_covid_data(self):
cd = covid_main.get_covid_data()
self.assertEqual(len(cd) > 0, True)
def test_write_csv(self):
cd = covid_main.get_covid_data()
covid_main.write_csv(cd, "covid_data.csv", "covid")
number_of_lines = len(open("covid_data.csv").readlines())
self.assertEqual(number_of_lines > 10, True)
def test_create_pie_plot(self):
cd = covid_main.get_covid_data()
covid_main.create_pie_plot(cd, 11, 2020)
self.assertEqual(
os.path.exists("Top 10 new cases pie for 11-2020.png"), True)
def test_create_cases_death_plots(self):
cd = covid_main.get_covid_data()
covid_main.create_cases_death_plots(cd, "United States", 11, 2020)
self.assertEqual(os.path.exists("United States new_cases.png"), True)
self.assertEqual(os.path.exists("United States new_deaths.png"), True)
def test_list_counties(self):
cd = covid_main.get_covid_data()
c = covid_main.list_counties(cd)
self.assertEqual("United States" in c, True)