diff --git a/proj2/mapka.R b/proj2/mapka.R
index e43fd27..7e51ac9 100644
--- a/proj2/mapka.R
+++ b/proj2/mapka.R
@@ -26,7 +26,7 @@ cov <- read.csv("proj2/max-covid.csv", header = TRUE)
 
 #df <- data.frame(as.Date(cov$date, format="%Y-%m-%d"), cov$iso_code, cov$total_cases)
 df <- data.frame(as.Date(cov$date), cov$iso_code, cov$total_cases)
-colnames(df) <- c('date', 'iso', 'total_cases')
+#colnames(df) <- c('date', 'iso', 'total_cases')
 
 #df$date = format(df$date, "%Y-%m") 
 
@@ -51,16 +51,17 @@ wmap_df <- left_join(wmap_df, df, by = c('id'='cov.iso_code'))
 
 ggplot(data=wmap_df, frame = date) +
   geom_polygon(aes(x = long, y = lat, group = group, fill=cov.total_cases), color="gray90") +
-  scale_fill_viridis(name="Cases", begin = 0, end = 1, limits = c(casesmin,casesmax), na.value="gray99") +
+  scale_fill_viridis(name="Zachorowania", na.value="white") +
   theme_void() +
   guides(fill = guide_colorbar(title.position = "top")) +
-  labs(title = "") +
-  theme( legend.position = c(.5, .08), 
-         legend.direction = "horizontal", 
-         legend.title.align = 0,
-         legend.key.size = unit(1.3, "cm"),
-         legend.title=element_text(size=17), 
-         legend.text=element_text(size=13) )
+  labs(title = "Liczba zachorowań w dniu 31.05.2021") 
+#+
+#  theme( legend.position = c(.5, .08), 
+#         legend.direction = "horizontal", 
+#         legend.title.align = 0,
+#         legend.key.size = unit(1.3, "cm"),
+#         legend.title=element_text(size=17), 
+#         legend.text=element_text(size=13) )
 #+
 #  transition_time(date)
 
diff --git a/proj2/trim.py b/proj2/trim.py
new file mode 100644
index 0000000..0fa2ba9
--- /dev/null
+++ b/proj2/trim.py
@@ -0,0 +1,23 @@
+import pandas as pd
+import numpy as np
+data = pd.read_csv('owid-covid-data.csv')
+df = data[['iso_code', 'date', 'total_cases']]
+df['date']=pd.to_datetime(df['date'], format='%Y-%m-%d')
+df.info()
+iso = df.iso_code.unique()
+df2 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
+df3 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
+for country in iso:
+	country_v = df.loc[df['iso_code'] == country]
+	months = country_v.set_index('date').groupby(pd.Grouper(freq='M')).max()
+	i=0
+	for index, month in months.iterrows():
+		#df2.append(month)
+		if i==months.shape[0]-1:
+			df3 = df3.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
+		
+		df2 = df2.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
+		i += 1
+df2.to_csv('month-covid.csv', sep=',')
+df3.to_csv('max-covid.csv', sep=',')
+	
\ No newline at end of file