diff --git a/pyzebra/app/panel_ccl_integrate.py b/pyzebra/app/panel_ccl_integrate.py
index 808f144..c46b7ac 100644
--- a/pyzebra/app/panel_ccl_integrate.py
+++ b/pyzebra/app/panel_ccl_integrate.py
@@ -135,7 +135,7 @@ def create():
     append_upload_button.on_change("value", append_upload_button_callback)
 
     def _update_table():
-        num_of_peaks = [scan.get("num_of_peaks", 0) for scan in det_data["scan"].values()]
+        num_of_peaks = [len(scan.get("peak_indexes", [])) for scan in det_data["scan"].values()]
         fit_ok = [(1 if "fit" in scan else 0) for scan in det_data["scan"].values()]
         scan_table_source.data.update(peaks=num_of_peaks, fit=fit_ok)
 
@@ -148,7 +148,7 @@ def create():
 
         plot_scatter_source.data.update(x=x, y=y, y_upper=y + np.sqrt(y), y_lower=y - np.sqrt(y))
 
-        num_of_peaks = scan.get("num_of_peaks")
+        num_of_peaks = len(scan.get("peak_indexes", []))
         if num_of_peaks is not None and num_of_peaks > 0:
             peak_indexes = scan["peak_indexes"]
             if len(peak_indexes) == 1:
@@ -288,7 +288,6 @@ def create():
         if new is not None and not peak_pos_textinput_lock:
             scan = _get_selected_scan()
 
-            scan["num_of_peaks"] = 1
             peak_ind = (np.abs(scan["om"] - float(new))).argmin()
             scan["peak_indexes"] = np.array([peak_ind], dtype=np.int64)
             scan["peak_heights"] = np.array([scan["smooth_peaks"][peak_ind]])
diff --git a/pyzebra/ccl_findpeaks.py b/pyzebra/ccl_findpeaks.py
index aecb85d..43054ee 100644
--- a/pyzebra/ccl_findpeaks.py
+++ b/pyzebra/ccl_findpeaks.py
@@ -29,11 +29,6 @@ def ccl_findpeaks(
             window_size - window size for savgol filter, must be odd positive integer
 
             poly_order =  order of the polynomial used in savgol filter, must be positive integer smaller than
-            window_size returns: dictionary with following structure:
-                                D{M34{  'num_of_peaks': 1,              #num of peaks
-                                        'peak_indexes': [20],           # index of peaks in omega array
-                                        'peak_heights': [90.],          # height of the peaks (if data vere smoothed
-                                                                        its the heigh of the peaks in smoothed data)
     """
     if not 0 <= int_threshold <= 1:
         int_threshold = 0.8
@@ -75,7 +70,6 @@ def ccl_findpeaks(
     peaks, properties = sc.signal.find_peaks(
         smooth_peaks, height=int_threshold * max(smooth_peaks), prominence=prominence
     )
-    scan["num_of_peaks"] = len(peaks)
     scan["peak_indexes"] = peaks
     scan["peak_heights"] = properties["peak_heights"]
     scan["smooth_peaks"] = smooth_peaks  # smoothed curve