diff --git a/plots.R b/plots.R
index adf8398..7940691 100644
--- a/plots.R
+++ b/plots.R
@@ -5,8 +5,10 @@
 
 source("survival.R")
 source("secmal.R")
+source("visualize.R")
 
 #
 # Make all plots and save to file
 sma_plot_file_surv()
 sma_plot_file_secmal()
+sma_plot_file_hist()
diff --git a/utils.R b/utils.R
index 5313b7a..635dc8e 100644
--- a/utils.R
+++ b/utils.R
@@ -81,6 +81,9 @@ sma_load_data <- function(file) {
 	# At this time only solid tumors are important
 	sma <- filter(sma, diagnosis_type == "solid")
 
+	# After filtering unused levels must be cleared from the data
+	sma <- droplevels(sma)
+
 	return(sma)
 }
 
diff --git a/visualize.R b/visualize.R
new file mode 100644
index 0000000..2b78a73
--- /dev/null
+++ b/visualize.R
@@ -0,0 +1,85 @@
+# Visualize basics from data
+#
+# License: GPL version 3
+# Jens Mathis Sauer (c) 2020
+
+source("utils.R")
+sma_init()
+
+sma_hist_asct_age <- function() {
+	data <- data.frame(asct_age = secmal$asct_age)
+	ggplot(data, aes(x = asct_age)) + geom_histogram(binwidth = 5)
+}
+
+i_asct_age_data <- function() {
+	return(data.frame(asct_age = secmal$asct_age, dx = secmal$diagnosis))
+}
+
+sma_hist_dx_age <- function() {
+	data <- i_asct_age_data()
+	ggplot(data, aes(x = asct_age, colour = dx, fill = dx)) +
+		geom_histogram(binwidth = 1)
+}
+
+sma_dens_dx_age <- function() {
+	data <- i_asct_age_data()
+	ggplot(data, aes(x = asct_age, colour = dx, fill = dx)) +
+		geom_density(alpha = 0.3)
+}
+sma_freq_dx_age <- function() {
+	data <- i_asct_age_data()
+	ggplot(data, aes(x = asct_age, colour = dx)) +
+		geom_freqpoly(binwidth = 1)
+}
+
+sma_jitt_dx_age <- function() {
+	data <- i_asct_age_data()
+	ggplot(data, aes(x = asct_age, y = dx, colour = dx, fill = dx)) +
+		geom_jitter(width = 0.4, height = 0.2)
+}
+
+sma_hist_asct_year <- function() {
+	data <- data.frame(asct_year = secmal$asct_year)
+	ggplot(data, aes(x = asct_year)) + geom_histogram(binwidth = 1)
+}
+
+i_dx_year_data <- function() {
+	return(data.frame(asct_year = secmal$asct_year, dx = secmal$diagnosis))
+}
+
+sma_hist_dx_year <- function() {
+	data <- i_dx_year_data()
+	ggplot(data, aes(x = asct_year, colour = dx, fill = dx)) +
+		geom_histogram(binwidth = 1)
+}
+
+sma_dens_dx_year <- function() {
+	data <- i_dx_year_data()
+	ggplot(data, aes(x = asct_year, colour = dx, fill = dx)) +
+		geom_density(alpha = 0.5)
+}
+
+sma_freq_dx_year <- function() {
+	data <- i_dx_year_data()
+	ggplot(data, aes(x = asct_year, colour = dx)) +
+		geom_freqpoly(binwidth = 1)
+}
+
+sma_jitt_dx_year <- function() {
+	data <- i_dx_year_data()
+	ggplot(data, aes(x = asct_year, y = dx, colour = dx, fill = dx)) +
+		geom_jitter(width = 0.4, height = 0.2)
+}
+
+sma_plot_file_hist <- function() {
+	sma_plot_file("hist_asct_age.png", png, sma_hist_asct_age)
+	sma_plot_file("hist_asct_year.png", png, sma_hist_asct_year)
+	sma_plot_file("dx_year_hist.png", png, sma_hist_dx_year)
+	sma_plot_file("dx_year_dens.png", png, sma_dens_dx_year)
+	sma_plot_file("dx_year_freq.png", png, sma_freq_dx_year)
+	sma_plot_file("dx_year_jitt.png", png, sma_jitt_dx_year)
+	sma_plot_file("dx_age_hist.png", png, sma_hist_dx_age)
+	sma_plot_file("dx_age_dens.png", png, sma_dens_dx_age)
+	sma_plot_file("dx_age_freq.png", png, sma_freq_dx_age)
+	sma_plot_file("dx_age_jitt.png", png, sma_jitt_dx_age)
+}