another linting!
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@@ -6,8 +6,6 @@ from numpy import ma
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import plotly.graph_objects as go
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import plotly.graph_objects as go
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from plotly.subplots import make_subplots
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from plotly.subplots import make_subplots
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import plotly.io as pio
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import plotly.io as pio
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from datetime import timedelta, datetime
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from pathlib import Path
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import sqlite3
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import sqlite3
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from sqlite3 import Connection
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from sqlite3 import Connection
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import plotly.express as px
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import plotly.express as px
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@@ -171,7 +169,7 @@ top_N_species = (df5.value_counts()[:top_N])
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font_size = 15
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font_size = 15
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if daily == False:
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if daily is False:
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specie = st.selectbox(
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specie = st.selectbox(
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'Which bird would you like to explore for the dates '
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'Which bird would you like to explore for the dates '
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+ str(start_date) + ' to ' + str(end_date) + '?',
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+ str(start_date) + ' to ' + str(end_date) + '?',
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@@ -258,7 +256,6 @@ if daily == False:
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# # ' Confidence Max:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+
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# # ' Confidence Max:'+str('{:.2f}%'.format(max(df2[df2['Com_Name']==specie]['Confidence'])*100))+
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# # ' '+' Median:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100))
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# # ' '+' Median:'+str('{:.2f}%'.format(np.median(df2[df2['Com_Name']==specie]['Confidence'])*100))
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# # )
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# # )
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# )
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# fig.add_trace(go.Bar(y=top_N_species.index, x=top_N_species, orientation='h'), row=1,col=1)
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# fig.add_trace(go.Bar(y=top_N_species.index, x=top_N_species, orientation='h'), row=1,col=1)
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df4 = df2['Com_Name'][df2['Com_Name'] == specie].resample('15min').count()
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df4 = df2['Com_Name'][df2['Com_Name'] == specie].resample('15min').count()
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