diff --git a/src/data/assign_to_day_segment.R b/src/data/assign_to_day_segment.R
index d58cbdfa..ecf17973 100644
--- a/src/data/assign_to_day_segment.R
+++ b/src/data/assign_to_day_segment.R
@@ -59,7 +59,7 @@ assign_rows_to_segments_frequency <- function(nested_data, nested_timezone, day_
 
 assign_to_day_segment <- function(sensor_data, day_segments, day_segments_type, include_past_periodic_segments){
   
-  if(nrow(sensor_data) == 0)
+  if(nrow(sensor_data) == 0 || nrow(day_segments) == 0)
     return(sensor_data %>% mutate(assigned_segments = NA))
   
   if(day_segments_type == "FREQUENCY"){
@@ -134,7 +134,7 @@ assign_to_day_segment <- function(sensor_data, day_segments, day_segments_type,
       arrange(timestamp)
 
   } else if ( day_segments_type == "EVENT"){
-    
+
     sensor_data <- sensor_data %>% 
       group_by(local_timezone) %>% 
       nest() %>% 
diff --git a/src/data/compute_day_segments.py b/src/data/compute_day_segments.py
index bfdb493b..0b66593c 100644
--- a/src/data/compute_day_segments.py
+++ b/src/data/compute_day_segments.py
@@ -1,4 +1,5 @@
 import pandas as pd
+import warnings
 
 def is_valid_frequency_segments(day_segments, day_segments_file):
     """
@@ -200,5 +201,9 @@ def parse_day_segments(day_segments_file, segments_type, pid):
     return day_segments
 
 final_day_segments = parse_day_segments(snakemake.input[0], snakemake.params["day_segments_type"], snakemake.params["pid"])
+
+if snakemake.params["day_segments_type"] == "EVENT" and final_day_segments.shape[0] == 0:
+    warnings.warn("There are no event day segments for {}. Check your day segment file {}".format(snakemake.params["pid"], snakemake.input[0]))
+
 final_day_segments.to_csv(snakemake.output["segments_file"], index=False)
 pd.DataFrame({"label" : final_day_segments["label"].unique()}).to_csv(snakemake.output["segments_labels_file"], index=False)
\ No newline at end of file