"""
# Daily COVID-19 Cases for LA County
The United States is struggling to control the coronavirus pandemic, with several counties reporting record high numbers of cases. Meanwhile, Europe has essentially brought it's cases down and passed its peak.  In this simple plotting exercises, we look at the cases for LA county to see if there are any trends in the upwards or downwards direction.  Charts from more counties will be added as the data is updated, as well as charts for daily deaths.  The code has been hidden for better readability.

"""
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib as mpl
import matplotlib.pyplot as plt

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session
#importing the data
filepath = "../input/us-counties-covid-19-dataset/us-counties.csv"
data = pd.read_csv(filepath, index_col = 'date')
print(data.state.unique())
%matplotlib inline 
#The .diff() command counts the daily increases, by subtracting the previous
# day's cumulative totals
lacounty = data.loc[data.county == 'Los Angeles']
lacounty['cases'].diff().plot(rot = 90)
plt.title('Daily COVID-19 Cases in LA County')
plt.show()
"""
So we see that unfortunately, daily cases have been trending upward on average, and they had never really dropped, despite national cases showing a dip in May and June. 
"""
orangecounty = data.loc[(data.county == 'Orange') & (data.state == 'California')]
orangecounty['cases'].diff().plot(rot = 90)
plt.title('Daily COVID-19 Cases in Orange County')
plt.show()
"""
Meanwhile, cases in Orange County (CA) only started to spike end of June, early July. 
"""