#from scripts.draw_map import map_tab
from scripts.routes import route_tab
# Using included state data from Bokeh for map
from bokeh.sampledata.us_states import data as states
# Read data into dataframes
flights = pd.read_csv(join(dirname(__file__), 'data', 'flights.csv'),
index_col=0).dropna()
# Formatted Flight Delay Data for map
map_data = pd.read_csv(join(dirname(__file__), 'data', 'flights_map.csv'),
header=[0, 1],
index_col=0)
# Create each of the tabs
#tab1 = histogram_tab(flights)
tab2 = density_tab(flights)
#tab3 = table_tab(flights)
#tab4 = map_tab(map_data, states)
tab5 = route_tab(flights)
# Put all the tabs into one application
tabs = Tabs(tabs=[tab2, tab5])
# Put the tabs in the current document for display
curdoc().add_root(tabs)
if '__name__' == '__main__':
pass
from bokeh.io import curdoc
from bokeh.models.widgets import Tabs
from bokeh.plotting import output_file, show
# Each tab is drawn by one script
from scripts.histogram import histogram_tab
from scripts.density import density_tab
from scripts.table import table_tab
from scripts.plot import plot_tab
# Read data into dataframes
df_avgs_w_l = pd.read_pickle('df_avgs_w_l')
df_avgs_w_l['rpi'] = pd.to_numeric(df_avgs_w_l['rpi'], errors='coerce')
# Create each of the tabs
tab1 = histogram_tab(df_avgs_w_l)
tab2 = density_tab(df_avgs_w_l)
tab3 = table_tab(df_avgs_w_l)
tab4 = plot_tab(df_avgs_w_l)
# tab5 = route_tb(flights)
# Put all the tabs into one application
tabs = Tabs(tabs=[tab1, tab2, tab3, tab4])
# Put the tabs in the current document for display
curdoc().add_root(tabs)
output_file('plots.html')
show(tabs)
from scripts.density import density_tab
from scripts.table import table_tab
from scripts.draw_map import map_tab
from scripts.routes import route_tab
# Using included state data from Bokeh for map
from bokeh.sampledata.us_states import data as states
# Read data into dataframes
flights = pd.read_csv(join(dirname(__file__), 'data', 'flights.csv'),
index_col=0).dropna()
# Formatted Flight Delay Data for map
map_data = pd.read_csv(join(dirname(__file__), 'data', 'flights_map.csv'),
header=[0,1], index_col=0)
# Create each of the tabs
tab1 = histogram_tab(flights)
tab2 = density_tab(flights)
tab3 = table_tab(flights)
tab4 = map_tab(map_data, states)
tab5 = route_tab(flights)
# Put all the tabs into one application
tabs = Tabs(tabs = [tab1, tab2, tab3, tab4, tab5])
# Put the tabs in the current document for display
curdoc().add_root(tabs)
from bokeh.io import curdoc
from bokeh.models.widgets import Tabs
# Each tab is drawn by one script
from scripts.histogram import histogram_tab
from scripts.density import density_tab
from scripts.table import table_tab
from scripts.draw_map import map_tab
from scripts.routes import route_tab
# Using included state data from Bokeh for map
from bokeh.sampledata.us_states import data as states
# Read data into dataframes
flights = pd.read_csv(join(dirname(__file__), 'data', 'flights.csv'),
index_col=0).dropna()
# Formatted Flight Delay Data for map
map_data = pd.read_csv(join(dirname(__file__), 'data', 'flights_map.csv'),
header=[0, 1],
index_col=0)
# Create each of the tabs
tab2 = density_tab()
# Put all the tabs into one application
tabs = Tabs(tabs=[tab2])
# Put the tabs in the current document for display
curdoc().add_root(tabs)