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Revision9c4265eca0143c2485d7fa8cf0b2deaa0644d4ae (tree)
Zeit2022-01-02 22:27:43
AutorLorenzo Isella <lorenzo.isella@gmai...>
CommiterLorenzo Isella

Log Message

I revised the plots and the statistics.

Ändern Zusammenfassung

Diff

diff -r b2eb0ca7a922 -r 9c4265eca014 R-codes/covid_process.R
--- a/R-codes/covid_process.R Thu Dec 30 23:48:37 2021 +0100
+++ b/R-codes/covid_process.R Sun Jan 02 14:27:43 2022 +0100
@@ -19,6 +19,8 @@
1919
2020 weekly_aver <- rollify(mean, window = 7)
2121
22+system("rm *csv")
23+system("rm *pdf")
2224
2325 system("wget https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-andamento-nazionale/dpc-covid19-ita-andamento-nazionale.csv")
2426
@@ -27,19 +29,21 @@
2729
2830
2931 df <- df_ini %>%
30- clean_names() %>%
32+ clean_data() %>%
3133 mutate(data=as_date(data)) %>%
3234 mutate(deceduti_giornalieri=diff_col2(deceduti)) %>%
33- mutate(deceduti_settimanali=weekly_aver(deceduti_giornalieri)) %>%
3435 mutate(anno=year(data)) %>%
3536 mutate(anno=as.factor(anno)) %>%
3637 mutate(giorno=yday(data)) %>%
3738 mutate(data_no_anno=as_date(giorno)-1) %>%
39+ mutate(positivi_progressione=cumsum(nuovi_positivi)) %>%
40+ ## group_by(anno) %>%
41+ mutate(deceduti_settimanali=weekly_aver(deceduti_giornalieri)) %>%
3842 mutate(ingressi_settimanali_terapia_intensiva=weekly_aver(ingressi_terapia_intensiva)) %>%
3943 mutate(terapia_intensiva_settimanale=weekly_aver(terapia_intensiva)) %>%
4044 mutate(ricoverati_settimanale=weekly_aver(ricoverati_con_sintomi)) %>%
41- mutate(ospedalizzati_settimanale=weekly_aver(totale_ospedalizzati))
42-
45+ mutate(ospedalizzati_settimanale=weekly_aver(totale_ospedalizzati)) ## %>%
46+ ## ungroup
4347
4448
4549 gpl <- ggplot(df, aes(x=data, y=deceduti_settimanali )) +
@@ -68,7 +72,7 @@
6872 guide = guide_axis(n.dodge = 2) ,
6973 expand=c(0.03,0.03)) +
7074 scale_color_scico_d(NULL, palette="hawaii" ,
71- labels=c("2020", "2021")
75+ labels=c("2020", "2021", "2022")
7276 )+
7377
7478 labs(title=NULL)+
@@ -81,13 +85,15 @@
8185
8286
8387 gpl2bis <- ggplot(df, aes(x=data_no_anno, y=deceduti_giornalieri, color=anno )) +
84- geom_line(size=1., alpha=1)+
88+ geom_line(size=.7, alpha=1)+
89+ geom_point(size=1., alpha=1)+
90+
8591 my_ggplot_theme2("top")+
8692 scale_x_date(breaks="1 months", date_labels = "%b",
8793 guide = guide_axis(n.dodge = 2) ,
8894 expand=c(0.03,0.03)) +
8995 scale_color_scico_d(NULL, palette="hawaii" ,
90- labels=c("2020", "2021")
96+ labels=c("2020", "2021", "2022")
9197 )+
9298
9399 labs(title=NULL)+
@@ -100,53 +106,62 @@
100106
101107
102108
103-gpl3 <- ggplot(df, aes(x=data_no_anno, y=ingressi_settimanali_terapia_intensiva, color=anno )) +
104- geom_line(size=1., alpha=1)+
109+gpl3 <- ggplot(df, aes(x=data_no_anno, y=ingressi_terapia_intensiva,
110+ color=anno )) +
111+ geom_line(size=.7, alpha=1)+
112+ geom_point(size=1, alpha=1)+
113+
105114 my_ggplot_theme2("top")+
106115 scale_x_date(breaks="1 months", date_labels = "%b",
107116 guide = guide_axis(n.dodge = 2) ,
108117 expand=c(0.03,0.03)) +
109118 scale_color_scico_d(NULL, palette="hawaii" ,
110- labels=c("2020", "2021")
119+ labels=c("2020", "2021", "2022")
111120 )+
112121
113122 labs(title=NULL)+
114123 xlab(NULL)+
115- ylab("Media Mobile Settimanale\nIngressi Terapia Intensiva")
124+ ylab("Ingressi Terapia Intensiva")
116125
117126
118-ggsave("ingressi_terapia_intensiva_ma_settimanali.pdf",gpl3, width=7*golden_ratio,height=7 , device = cairo_pdf )
127+ggsave("ingressi_terapia_intensiva.pdf",gpl3, width=7*golden_ratio,height=7 , device = cairo_pdf )
119128
120129
121130
122-gpl4 <- ggplot(df, aes(x=data_no_anno, y=terapia_intensiva_settimanale, color=anno )) +
123- geom_line(size=1., alpha=1)+
131+gpl4 <- ggplot(df, aes(x=data_no_anno, y=terapia_intensiva, color=anno )) +
132+ geom_line(size=.7, alpha=1)+
133+ geom_point(## aes(x=data_no_anno,y=terapia_intensiva,
134+ ## color=anno ),
135+ size=1, alpha=1)+
136+
124137 my_ggplot_theme2("top")+
125138 scale_x_date(breaks="1 months", date_labels = "%b",
126139 guide = guide_axis(n.dodge = 2) ,
127140 expand=c(0.03,0.03)) +
128141 scale_color_scico_d(NULL, palette="hawaii" ,
129- labels=c("2020", "2021")
142+ labels=c("2020", "2021", "2022")
130143 )+
131144
132145 labs(title=NULL)+
133146 xlab(NULL)+
134- ylab("Media Mobile Settimanale\nPazienti in Terapia Intensiva")
147+ ylab("Pazienti in Terapia Intensiva")
135148
136149
137-ggsave("occupazione_terapia_intensiva_ma_settimanali.pdf",gpl4, width=7*golden_ratio,height=7 , device = cairo_pdf )
150+ggsave("occupazione_terapia_intensiva_settimanali.pdf",gpl4, width=7*golden_ratio,height=7 , device = cairo_pdf )
138151
139152
140153
141154
142155 gpl5 <- ggplot(df, aes(x=data_no_anno, y=isolamento_domiciliare, color=anno )) +
143- geom_line(size=1., alpha=1)+
156+ geom_point(size=1., alpha=1)+
157+
158+ geom_line(size=.7, alpha=1)+
144159 my_ggplot_theme2("top")+
145160 scale_x_date(breaks="1 months", date_labels = "%b",
146161 guide = guide_axis(n.dodge = 2) ,
147162 expand=c(0.03,0.03)) +
148163 scale_color_scico_d(NULL, palette="hawaii" ,
149- labels=c("2020", "2021")
164+ labels=c("2020", "2021", "2022")
150165 )+
151166
152167 labs(title=NULL)+
@@ -158,55 +173,112 @@
158173
159174
160175
161-gpl6 <- ggplot(df, aes(x=data_no_anno, y=ricoverati_settimanale, color=anno )) +
162- geom_line(size=1., alpha=1)+
176+## gpl6 <- ggplot(df, aes(x=data_no_anno, y=ricoverati_settimanale, color=anno )) +
177+## geom_line(size=1., alpha=1)+
178+## my_ggplot_theme2("top")+
179+## scale_x_date(breaks="1 months", date_labels = "%b",
180+## guide = guide_axis(n.dodge = 2) ,
181+## expand=c(0.03,0.03)) +
182+## scale_color_scico_d(NULL, palette="hawaii" ,
183+## labels=c("2020", "2021", "2022")
184+## )+
185+
186+## labs(title=NULL)+
187+## xlab(NULL)+
188+## ylab("Ricoverati")
189+
190+
191+## ggsave("ricoverati.pdf",gpl6, width=7*golden_ratio,height=7 , device = cairo_pdf )
192+
193+
194+
195+
196+gpl7 <- ggplot(df, aes(x=data_no_anno, y=totale_ospedalizzati, color=anno )) +
197+ geom_line(size=.7, alpha=1)+
198+ geom_point(size=1, alpha=1)+
199+
163200 my_ggplot_theme2("top")+
164201 scale_x_date(breaks="1 months", date_labels = "%b",
165202 guide = guide_axis(n.dodge = 2) ,
166203 expand=c(0.03,0.03)) +
167204 scale_color_scico_d(NULL, palette="hawaii" ,
168- labels=c("2020", "2021")
205+ labels=c("2020", "2021", "2022")
169206 )+
170207
171208 labs(title=NULL)+
172209 xlab(NULL)+
173- ylab("Ricoverati Media Mobile Settimanale")
210+ ylab("Totale Ospedalizzati")
174211
175212
176-ggsave("ricoverati_media_mobile.pdf",gpl6, width=7*golden_ratio,height=7 , device = cairo_pdf )
213+ggsave("ospedalizzati.pdf",gpl7, width=7*golden_ratio,height=7 , device = cairo_pdf )
177214
178215
179216
180217
181-gpl7 <- ggplot(df, aes(x=data_no_anno, y=ospedalizzati_settimanale, color=anno )) +
182- geom_line(size=1., alpha=1)+
218+
219+
220+gpl8 <- ggplot(df, aes(x=data_no_anno, y=totale_positivi, color=anno )) +
221+ geom_line(size=.7, alpha=1)+
222+ geom_point(size=1., alpha=1)+
223+
183224 my_ggplot_theme2("top")+
184225 scale_x_date(breaks="1 months", date_labels = "%b",
185226 guide = guide_axis(n.dodge = 2) ,
186227 expand=c(0.03,0.03)) +
187228 scale_color_scico_d(NULL, palette="hawaii" ,
188- labels=c("2020", "2021")
229+ labels=c("2020", "2021", "2022")
189230 )+
190231
191232 labs(title=NULL)+
192233 xlab(NULL)+
193- ylab("Totale Ospedalizzati Media Mobile Settimanale")
234+ ylab("Totale Positivi")
194235
195236
196-ggsave("ospedalizzati_media_mobile.pdf",gpl7, width=7*golden_ratio,height=7 , device = cairo_pdf )
197-
198-
199-system("wget https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-regioni/dpc-covid19-ita-regioni.csv")
200-
201-
202-df_regio_ini <- read_csv("dpc-covid19-ita-regioni.csv")
237+ggsave("totale_positivi.pdf",gpl8, width=7*golden_ratio,height=7 , device = cairo_pdf )
203238
204239
205240
206-system("wget https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-province/dpc-covid19-ita-province.csv")
241+
242+gpl9 <- ggplot(df, aes(x=data, y=positivi_progressione## , color=anno
243+ )) +
244+ geom_line(size=.7, alpha=1)+
245+ geom_point(size=1., alpha=1)+
246+
247+ my_ggplot_theme2("top")+
248+ scale_x_date(breaks="1 months", date_labels = "%b\n%y",
249+ guide = guide_axis(n.dodge = 2) ,
250+ expand=c(0.03,0.03)) +
251+ ## scale_color_scico_d(NULL, palette="hawaii" ,
252+ ## labels=c("2020", "2021", "2022")
253+ ## )+
254+
255+ labs(title=NULL)+
256+ xlab(NULL)+
257+ ylab("Incidenza cumulativa")
207258
208259
209-df_pro_ini <- read_csv("dpc-covid19-ita-province.csv")
260+ggsave("incidenza.pdf",gpl9, width=7*golden_ratio,height=7 , device = cairo_pdf )
261+
262+
263+
264+
265+
266+
267+
268+
269+
270+
271+## system("wget https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-regioni/dpc-covid19-ita-regioni.csv")
272+
273+
274+## df_regio_ini <- read_csv("dpc-covid19-ita-regioni.csv")
275+
276+
277+
278+## system("wget https://raw.githubusercontent.com/pcm-dpc/COVID-19/master/dati-province/dpc-covid19-ita-province.csv")
279+
280+
281+## df_pro_ini <- read_csv("dpc-covid19-ita-province.csv")
210282
211283
212284 print("So far so good")