From 401660956ddde51cd33ab20032c0fb517240975c Mon Sep 17 00:00:00 2001
From: Dan Wallace <69432266+wallacewd@users.noreply.github.com>
Date: Tue, 29 Sep 2020 12:49:47 -0400
Subject: [PATCH] Delete cdc_total_us_deaths_analysis.py

---
 cdc_total_us_deaths_analysis.py | 78 ---------------------------------
 1 file changed, 78 deletions(-)
 delete mode 100644 cdc_total_us_deaths_analysis.py

diff --git a/cdc_total_us_deaths_analysis.py b/cdc_total_us_deaths_analysis.py
deleted file mode 100644
index edcc21b..0000000
--- a/cdc_total_us_deaths_analysis.py
+++ /dev/null
@@ -1,78 +0,0 @@
-"""
-CDC Total United States Yearly Deaths - Visualized by week
-Author: Dan Wallace
-Date: 09/29/2020
-Download 'Weekly Deaths by State and Age' from this CDC Link (csv format): https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm
-Save to a folder, copy the file path and paste inside path='____" below (example included, will not work until you a provide propper file path)
-"""
-import numpy as np
-import pandas as pd # Imports Panda's Library
-import matplotlib.pyplot as plt
-from matplotlib.pyplot import axes  # Imports matplotlib.pyplot and renames it to plt  # from matplot 
-import matplotlib as mpl # Imports matplotlib and renames it to mp1
-from matplotlib import style # In the matplotlib library, import style 
-
-#-------------------------------------------------
-# Paste csv file path here
-#-------------------------------------------------
-
-path = 'C:/Users/Dan/Documents/cdcData/updatadata.csv'
-
-#-------------------------------------------------
-# Create dataFrame
-#-------------------------------------------------
-
-# Creates a dataFrame named 'df' and used pd(pandas) to read the csv file above, and sets the index column to 'Week Ending Date'
-df = pd.read_csv(path, index_col=['Week Ending Date']) 
-
-# Displays the Column Names/Data Count/Object Type contained in the dataframe
-df.info() 
-
-#-------------------------------------------------
-# dataFrame collection/organization 
-#-------------------------------------------------
-
-us_note = df['Week'] <= 30
-print(us_note)
-
-final_note = df[us_note]
-print(final_note)
-
-us_unweighted = final_note['Type']=='Unweighted'
-print(us_unweighted) 
-
-final = final_note[us_unweighted]
-print(final) 
-
-df_us = final['Jurisdiction']=='United States'      
-print(df_us) 
-
-final_us = final[df_us]                             
-print(final_us.info())
-
-# ct_deaths calls the pandas library and uses the crosstab() function to arrange the data
-# in a way that we can plot the total deaths in the US by year against the weeks in the year
-ct_deaths = pd.crosstab(final_us['Week'],final_us['Year'],values=final_us['Number of Deaths'],aggfunc="sum")
-
-#-------------------------------------------------
-# Begin Plotting
-#-------------------------------------------------
-
-mpl.rc('figure', figsize=(8, 6))                                                                                        # Sets the figure size width and height
-mpl.__version__                                                                                                         # Outputs MatPlotLib version number in terminal 
-style.use('seaborn-muted')                                                                                              # Graph theme 
-mpl.rc('lines', linewidth=3)                                                                                            # Style of graph to use
-                                  
-ct_deaths.plot(label='Number of Deaths').grid(color='lightgrey', linestyle='solid')                                     # Plots the Number of deaths to the graph
-
-plt.title('United States 2015-2020: Total Deaths by Week \n (All Age Groups Through First 15 Weeks)', fontsize=14)
-plt.ylabel('Number of Deaths', fontsize=13)                                                                             # Changes the y-axis label to 'Number of Deaths'
-plt.xlabel('Week', fontsize=13)                                                                                         # Changes the x-axis label to 'Deaths Reported by Week'
-plt.subplot(111).set_xlim(1, 30)
-dim=np.arange(1,31,1)
-dim2=np.arange(45000,90000,5000)
-plt.xticks(dim, fontsize=11)
-plt.yticks(dim2, fontsize=11)
-
-plt.show()                                                                                                              # Opens a window with the resulting graph
-