diff --git a/scripts/daily_plot.py b/scripts/daily_plot.py
index 5674ab1..2240314 100755
--- a/scripts/daily_plot.py
+++ b/scripts/daily_plot.py
@@ -57,12 +57,28 @@ df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.ind
 pal = "Greens"
 
 #Set up plot axes and titles
-f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
+# f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
+
+f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]))
 plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
 
+#generate y-axis order for all figures based on frequency
+freq_order = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index
+
+#make color for max confidence --> this groups by name and calculates max conf
+confmax = df_plt_top10_today.groupby('Com_Name')['Confidence'].max()
+#reorder confmax to detection frequency order
+confmax = confmax.reindex(freq_order)
+
+# norm values for color palette
+norm = plt.Normalize(confmax.values.min(), confmax.values.max())
+colors = plt.cm.Greens(norm(confmax))
 
 #Generate frequency plot
-plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = pal+"_r",  order=pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index, ax=axs[0])
+plot=sns.countplot(y='Com_Name', data = df_plt_top10_today, palette = colors,  order=freq_order, ax=axs[0])
+
+
+
 
 #Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
 # plot.grid(True, axis='y')
@@ -71,16 +87,16 @@ plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for tick
 plot.set(ylabel=None)
 plot.set(xlabel="Detections")
 
-huw=df_plt_top10_today.groupby('Com_Name')['Confidence'].mean()
-plot = sns.boxenplot(x=df_plt_top10_today['Confidence']*100,color='Green',  y=df_plt_top10_today['Com_Name'], ax=axs[1],order=pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index)
-plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
+# huw=df_plt_top10_today.groupby('Com_Name')['Confidence'].mean()
+# plot = sns.boxenplot(x=df_plt_top10_today['Confidence']*100,color='Green',  y=df_plt_top10_today['Com_Name'], ax=axs[1],order=freq_order)
+# plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
 
 
 #Generate crosstab matrix for heatmap plot
 
 heat = pd.crosstab(df_plt_top10_today['Com_Name'],df_plt_top10_today['Hour of Day'])
 #Order heatmap Birds by frequency of occurrance
-heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_plt_top10_today['Com_Name']).iloc[:readings].index)
+heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
 heat.sort_index(level=0, inplace=True)
 
 
@@ -89,7 +105,8 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
 heat=(heat+heat_frame).fillna(0)
 
 #Generatie heatmap plot
-plot = sns.heatmap(heat, norm=LogNorm(), annot=True, fmt="g", annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[2], yticklabels = False)
+plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
+plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
 
 # Set heatmap border
 for _, spine in plot.spines.items():
@@ -100,28 +117,44 @@ plot.set(xlabel="Hour of Day")
 #Set combined plot layout and titles
 # plt.tight_layout()
 f.subplots_adjust(top=0.9)
-plt.suptitle("Last Updated: "+ str(now.strftime("%d %m %Y %H:%M")))
+plt.suptitle("Last Updated: "+ str(now.strftime("%d-%m-%Y %H:%M")))
 
 #Save combined plot
 savename='/home/pi/BirdSongs/Extracted/Charts/Combo-'+str(now.strftime("%d-%m-%Y"))+'.png'
 plt.savefig(savename)
-# plt.show()
+#plt.show()
 plt.close()
 
-#Get bottom 10 today
-plt_bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
-df_plt_bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_bot10_today.index)]
+
+# Get Bottom detection frequency
+plt_Bot10_today = (df_plt_today['Com_Name'].value_counts()[-readings:])
+df_plt_Bot10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_Bot10_today.index)]
 
 #Set Palette for graphics
 pal = "Reds"
 
 #Set up plot axes and titles
-f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
+# f, axs = plt.subplots(1, 3, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 2, 5]))
+
+f, axs = plt.subplots(1, 2, figsize = (10, 4), gridspec_kw=dict(width_ratios=[3, 6]))
 plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0, hspace=0)
 
+#generate y-axis order for all figures based on frequency
+freq_order = pd.value_counts(df_plt_Bot10_today['Com_Name']).iloc[-readings:].index
+
+#make color for max confidence --> this groups by name and calculates max conf
+confmax = df_plt_Bot10_today.groupby('Com_Name')['Confidence'].max()
+confmax = confmax.reindex(freq_order)
+# probably wrong order . . . how to sort by no. of detections ?
+# norm values for color palette
+norm = plt.Normalize(confmax.values.min(), confmax.values.max())
+colors = plt.cm.Reds(norm(confmax))
 
 #Generate frequency plot
-plot=sns.countplot(y='Com_Name', data = df_plt_bot10_today, palette = pal+"_r",  order=pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index, ax=axs[0])
+plot=sns.countplot(y='Com_Name', data = df_plt_Bot10_today, palette = colors,  order=freq_order, ax=axs[0])
+
+
+
 
 #Try plot grid lines between bars - problem at the moment plots grid lines on bars - want between bars
 # plot.grid(True, axis='y')
@@ -130,16 +163,16 @@ plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),15)) for tick
 plot.set(ylabel=None)
 plot.set(xlabel="Detections")
 
-huw=df_plt_bot10_today.groupby('Com_Name')['Confidence'].mean()
-plot = sns.boxenplot(x=df_plt_bot10_today['Confidence']*100,color='Red',  y=df_plt_bot10_today['Com_Name'], ax=axs[1],order=pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index)
-plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
+# huw=df_plt_Bot10_today.groupby('Com_Name')['Confidence'].mean()
+# plot = sns.boxenplot(x=df_plt_Bot10_today['Confidence']*100,color='Green',  y=df_plt_Bot10_today['Com_Name'], ax=axs[1],order=freq_order)
+# plot.set(xlabel="Confidence", ylabel=None,yticklabels=[])
 
 
 #Generate crosstab matrix for heatmap plot
 
-heat = pd.crosstab(df_plt_bot10_today['Com_Name'],df_plt_bot10_today['Hour of Day'])
+heat = pd.crosstab(df_plt_Bot10_today['Com_Name'],df_plt_Bot10_today['Hour of Day'])
 #Order heatmap Birds by frequency of occurrance
-heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_plt_bot10_today['Com_Name']).iloc[-readings:].index)
+heat.index = pd.CategoricalIndex(heat.index, categories = freq_order)
 heat.sort_index(level=0, inplace=True)
 
 
@@ -148,7 +181,8 @@ heat_frame = pd.DataFrame(data=0, index=heat.index, columns = hours_in_day)
 heat=(heat+heat_frame).fillna(0)
 
 #Generatie heatmap plot
-plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[2], yticklabels = False)
+plot = sns.heatmap(heat, norm=LogNorm(),  annot=True,  annot_kws={"fontsize":7}, cmap = pal , square = False, cbar=False, linewidths = 0.5, linecolor = "Grey", ax=axs[1], yticklabels = False)
+plot.set_xticklabels(plot.get_xticklabels(), rotation = 0, size = 7)
 
 # Set heatmap border
 for _, spine in plot.spines.items():
@@ -159,10 +193,10 @@ plot.set(xlabel="Hour of Day")
 #Set combined plot layout and titles
 # plt.tight_layout()
 f.subplots_adjust(top=0.9)
-plt.suptitle("Last Updated: "+ str(now.strftime("%d %m %Y %H:%M")))
+plt.suptitle("Last Updated: "+ str(now.strftime("%d-%m-%Y %H:%M")))
 
 #Save combined plot
 savename='/home/pi/BirdSongs/Extracted/Charts/Combo2-'+str(now.strftime("%d-%m-%Y"))+'.png'
 plt.savefig(savename)
-#plt.show()
+# plt.show()
 plt.close()