diff --git a/docker-compose.yml b/docker-compose.yml
index 3d2182b..a8c955c 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -27,7 +27,7 @@ services:
     environment:
       PASSWORD: secret
     volumes:
-      - ./rstudio:/home/rstudio
+      - ./rstudio:/home/rstudio/smartmeter
     ports:
       - 8787:8787
 
diff --git a/rstudio/Dockerfile b/rstudio/Dockerfile
index 1d603f9..8dc41f7 100644
--- a/rstudio/Dockerfile
+++ b/rstudio/Dockerfile
@@ -2,6 +2,8 @@ FROM rocker/tidyverse:latest
 
 RUN apt-get update \
         && apt-get install -y libmariadb-dev \
+		libicu-dev liblzma-dev libpcre3-dev libpng-dev \
+                libv8-dev libbz2-dev libxml2-dev \
         && apt-get clean \ 
         && rm -rf /var/lib/apt/lists/ \ 
         && rm -rf /tmp/downloaded_packages/ /tmp/*.rds
@@ -10,6 +12,8 @@ RUN apt-get update \
 RUN Rscript -e "install.packages(c('tidyverse','purr','psych','lme4','lmerTest','broom','doBy','reshape','emmeans','effects','mlr','randomForest','glmnet','foreign'), repos='https://cran.rstudio.com/')" \
     && rm -rf /tmp/downloaded_packages/ /tmp/*.rds
 
+RUN mkdir /home/rstudio/smartmeter
+VOLUME /home/rstudio/smartmeter
 
 EXPOSE 8787
 
diff --git a/rstudio/Energy.Rmd b/rstudio/Energy.Rmd
new file mode 100755
index 0000000..a2bee3a
--- /dev/null
+++ b/rstudio/Energy.Rmd
@@ -0,0 +1,77 @@
+library(dplyr)
+library(dbplyr)
+library(ggplot2)
+library(lubridate)
+library(tidyr)
+
+# Access to our smartmeter DB
+con <- DBI::dbConnect(RMariaDB::MariaDB(), host="db", dbname="smartmeter", user="root", password="rootme")
+
+DBI::dbListTables(con)
+
+# get some records
+res <- DBI::dbSendQuery(con, "SELECT * FROM readings LIMIT 10")
+DBI::dbFetch(res)
+
+# dplyr style of reading data from mysql
+# con %>% tbl("readings") %>% show_query()
+
+# get all records from 2022
+energy <- con %>% tbl("readings") %>% 
+        select(total_m3_gas_consumed, total_kwh_consumed_high, total_kwh_consumed_low, 
+                total_kwh_produced_high, total_kwh_produced_low, high_tarif, created_at) %>% 
+        filter(created_at > "2021-09-01", created_at < "2021-12-31") %>%
+        mutate(date = as.Date(created_at)) %>%
+        collect()
+
+# add hour column
+energy <- energy %>% mutate(hour = format(strptime(created_at,"%Y-%m-%d %H:%M:%S"),'%H'))
+
+# group by hour
+energy_per_hour <- energy %>% 
+                mutate(total_usage_kwh = (total_kwh_consumed_high+total_kwh_consumed_low)) %>%
+                mutate(total_return_kwh = (total_kwh_produced_high+total_kwh_produced_low)) %>%
+                group_by(date,hour) %>% 
+                summarize(max_m3_gas_consumed = max(total_m3_gas_consumed), 
+                            min_m3_gas_consumed = min(total_m3_gas_consumed), 
+                            max_usage_kwh = max(total_usage_kwh), 
+                            min_usage_kwh = min(total_usage_kwh), 
+                            max_return_kwh = max(total_return_kwh), 
+                            min_return_kwh = min(total_return_kwh)) %>%
+                mutate(usage_m3 = max_m3_gas_consumed-min_m3_gas_consumed) %>%
+                mutate(usage_kwh = max_usage_kwh-min_usage_kwh) %>%
+                mutate(return_kwh = max_return_kwh-min_return_kwh) %>%
+                select(-max_m3_gas_consumed, -min_m3_gas_consumed, -max_usage_kwh, -min_usage_kwh, -max_return_kwh, -min_return_kwh )
+
+# mutate(usage_kwh = round(usage_kwh,1), return_kwh = round(return_kwh,1)) %>%
+# and again, group by day
+energy_per_day <- energy_per_hour %>% 
+                  group_by(date) %>% 
+                  summarize(usage_m3=round(sum(usage_m3),2), 
+                            usage_kwh=round(sum(usage_kwh),2),
+                            return_kwh=round(sum(return_kwh),2))
+
+# some plots
+energy_per_hour %>% 
+            mutate(usage_kwh = round(usage_kwh,1), return_kwh = round(return_kwh,1)) %>%
+            ggplot( aes(x=date, fill=hour, y=usage_kwh, text=as.character(date))) +
+            geom_bar(stat="identity") +
+            theme_bw() +  
+            labs(x="Date", y="kwh") 
+
+# daily usage/return of electricity
+energy_per_day %>% pivot_longer(cols = usage_kwh:return_kwh) %>%
+            ggplot( aes(x=date, y=value, fill=name, text=as.character(date))) +
+            geom_bar(position="dodge", stat="identity") +
+            geom_text(aes(label=value), vjust=-0.3, hjust=1.2, size=2.5) +
+            theme_bw() +  
+            labs(x="Date", y="kwh") 
+
+# daily usage/return of gas
+energy_per_day %>% pivot_longer(cols = usage_m3) %>%
+            ggplot( aes(x=date, y=value, fill=name, text=as.character(date))) +
+            geom_bar(position="dodge", stat="identity") +
+            geom_text(aes(label=value), vjust=-0.3, hjust=1.2, size=2.5) +
+            theme_bw() +  
+            labs(x="Date", y="m3") 
+