<jupyter_start><jupyter_text>A&W CANADA DATASET- author: <NAME> - toc: false- badges: false- comments: true- categories: [Matrix]- image: images/anw.png<jupyter_code>#IMPORTING EXTERNAL LIBRARIES AND SETTING THE DATE AND WEEK RANGE. 
import pandas as pd
import datetime
import numpy as np
from pivottablejs import pivot_ui
date=datetime.datetime.now().strftime("%Y-%m-%d")
print (date)
#SET 7 DAYS TIMEFRAME FROM TODAYS DATE
weekly=pd.date_range(end=date, periods=7).strftime("%Y-%m-%d")
biweekly=pd.date_range(end=date, periods=14)
print(weekly)
print (biweekly)
df_cl.columns
#IMPORTING DATASETS
from datetime import datetime
df_ca= pd.read_csv('../_data/Data_Sources/Canada/hrcases.csv')
df_cl=pd.read_csv('../_data/client_locations/anw_canada.csv')
#canada_Population=pd.read_csv('../_data/data_resources/canada/caCensus.csv')
df_cl=df_cl.set_index('province')

df_ca.rename(columns={'health_region':'region', 'date_report':'date'}, inplace=True)
df_ca['date'] = df_ca['date'].astype('datetime64')
df_ca.set_index('date', inplace=True)
df_ca

#MERGING DATASETS
print (df_ca.columns)
print(df_cl.columns)
print (df_cl.shape)
print(df_ca.shape)

#client locations and add population data to them. 
#merge clientCleaned with canada data
#sort the dataset by the culmulative and then the county
#print the dataset and save it the client/dataset folder with a datestamp
#EXPORTING WEEKLY REPORT
#FIGURE OUT HOW TO SOMEHOW MATCH THE DATING TO THE WEIRDNESS IN THE FILE. 
#SAVE THE FILE TO THE DATA FOLDER WITH A DATE STAMP
#EXPORTING DAILY REPORT
#SAVE THE DAILY REPORT TO DATA FOLDER WITH A DATE STAMP<jupyter_output><empty_output><jupyter_text>REPLACED SOME COUNTIES TO FILL DATA<jupyter_code>#REPLACED SOME LOCATIONS BUT THERE IS A COLUMN TO INDICATE IT.<jupyter_output><empty_output>
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