Cannot get Bokeh graph to show using Python











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I'm pretty new to Python and this is my first time using Bokeh. I've followed a tutorial using NFL data to show graphs and I cannot get the graph to show on my machine. The script runs without error, but nothing shows. I'm sure I'm missing something very simple... but I just don't know what that is... Can someone please help me? Below is my code:



import pandas as pd
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, FactorRange, FixedTicker
from bokeh.io import output_notebook
from collections import Counter
from bokeh.transform import factor_cmap
from bokeh.palettes import Paired, Spectral
import itertools
pd.set_option('display.max_columns', 150)
output_notebook()

filename = '/Users/ksilva/Downloads/NFL Play by Play 2009-2017 (v4).csv'
df = pd.read_csv(filename,dtype={25: object, 51: object})

# print(df.shape)

# df['down'].isnull().sum()
pd.to_numeric(df['down'], errors='coerce').isnull().sum()

# print(df.loc[51])

# filter by team if desired
team = 'all'
if team == 'all':
team_df = df
else:
team_df = df.loc[df['posteam'] == team]

# drop rows will null in the 'down' column
team_df = team_df.loc[df['down'].notnull()]

all_play_types = Counter(team_df['PlayType'])

# print(team_df)
# print(all_play_types)

# list of downs I care about
downs = ['1','2','3','4']

# list of plays I care about
plays = ['Pass', 'Run', 'Punt', 'Field Goal']

# define x-axis categories to be used in the vbar plot
x = list(itertools.product(downs, plays))
# x = [('1', 'Pass'), ('1', 'Run'), ('1', 'Punt'), ..., ('4', 'Punt'), ('4', 'Field Goal')]

# create a list of Counters for each down--will include ALL PlayTypes for each down
plays_on_down = [Counter(team_df.loc[team_df['down'] == int(down)]['PlayType']) for down in downs]

# create a list of counts for each play in plays for each down in downs
counts = [plays_on_down[int(down)-1][play] for down, play in x]

# load the into the ColumnDataSource
source = ColumnDataSource(data=dict(x=x, counts=counts))

# get the figure ready
p = figure(x_range=FactorRange(*x), plot_height=350, plot_width=750, title='Play by Down',
toolbar_location=None, tools='')

# create the vbar
p.vbar(x='x', top='counts', width=0.9, source=source, line_color='white',
fill_color=factor_cmap('x', palette=Spectral[4], factors=plays, start=1, end=2))
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xaxis.axis_label = 'Down'
p.yaxis.axis_label = 'Number of Plays'
p.xgrid.grid_line_color = None
show(p)


For whatever reason, nothing happens when executed from the terminal.



Any help is greatly appreciated!



Thanks.










share|improve this question






















  • Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
    – Kai
    Nov 21 at 18:17

















up vote
0
down vote

favorite












I'm pretty new to Python and this is my first time using Bokeh. I've followed a tutorial using NFL data to show graphs and I cannot get the graph to show on my machine. The script runs without error, but nothing shows. I'm sure I'm missing something very simple... but I just don't know what that is... Can someone please help me? Below is my code:



import pandas as pd
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, FactorRange, FixedTicker
from bokeh.io import output_notebook
from collections import Counter
from bokeh.transform import factor_cmap
from bokeh.palettes import Paired, Spectral
import itertools
pd.set_option('display.max_columns', 150)
output_notebook()

filename = '/Users/ksilva/Downloads/NFL Play by Play 2009-2017 (v4).csv'
df = pd.read_csv(filename,dtype={25: object, 51: object})

# print(df.shape)

# df['down'].isnull().sum()
pd.to_numeric(df['down'], errors='coerce').isnull().sum()

# print(df.loc[51])

# filter by team if desired
team = 'all'
if team == 'all':
team_df = df
else:
team_df = df.loc[df['posteam'] == team]

# drop rows will null in the 'down' column
team_df = team_df.loc[df['down'].notnull()]

all_play_types = Counter(team_df['PlayType'])

# print(team_df)
# print(all_play_types)

# list of downs I care about
downs = ['1','2','3','4']

# list of plays I care about
plays = ['Pass', 'Run', 'Punt', 'Field Goal']

# define x-axis categories to be used in the vbar plot
x = list(itertools.product(downs, plays))
# x = [('1', 'Pass'), ('1', 'Run'), ('1', 'Punt'), ..., ('4', 'Punt'), ('4', 'Field Goal')]

# create a list of Counters for each down--will include ALL PlayTypes for each down
plays_on_down = [Counter(team_df.loc[team_df['down'] == int(down)]['PlayType']) for down in downs]

# create a list of counts for each play in plays for each down in downs
counts = [plays_on_down[int(down)-1][play] for down, play in x]

# load the into the ColumnDataSource
source = ColumnDataSource(data=dict(x=x, counts=counts))

# get the figure ready
p = figure(x_range=FactorRange(*x), plot_height=350, plot_width=750, title='Play by Down',
toolbar_location=None, tools='')

# create the vbar
p.vbar(x='x', top='counts', width=0.9, source=source, line_color='white',
fill_color=factor_cmap('x', palette=Spectral[4], factors=plays, start=1, end=2))
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xaxis.axis_label = 'Down'
p.yaxis.axis_label = 'Number of Plays'
p.xgrid.grid_line_color = None
show(p)


For whatever reason, nothing happens when executed from the terminal.



Any help is greatly appreciated!



Thanks.










share|improve this question






















  • Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
    – Kai
    Nov 21 at 18:17















up vote
0
down vote

favorite









up vote
0
down vote

favorite











I'm pretty new to Python and this is my first time using Bokeh. I've followed a tutorial using NFL data to show graphs and I cannot get the graph to show on my machine. The script runs without error, but nothing shows. I'm sure I'm missing something very simple... but I just don't know what that is... Can someone please help me? Below is my code:



import pandas as pd
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, FactorRange, FixedTicker
from bokeh.io import output_notebook
from collections import Counter
from bokeh.transform import factor_cmap
from bokeh.palettes import Paired, Spectral
import itertools
pd.set_option('display.max_columns', 150)
output_notebook()

filename = '/Users/ksilva/Downloads/NFL Play by Play 2009-2017 (v4).csv'
df = pd.read_csv(filename,dtype={25: object, 51: object})

# print(df.shape)

# df['down'].isnull().sum()
pd.to_numeric(df['down'], errors='coerce').isnull().sum()

# print(df.loc[51])

# filter by team if desired
team = 'all'
if team == 'all':
team_df = df
else:
team_df = df.loc[df['posteam'] == team]

# drop rows will null in the 'down' column
team_df = team_df.loc[df['down'].notnull()]

all_play_types = Counter(team_df['PlayType'])

# print(team_df)
# print(all_play_types)

# list of downs I care about
downs = ['1','2','3','4']

# list of plays I care about
plays = ['Pass', 'Run', 'Punt', 'Field Goal']

# define x-axis categories to be used in the vbar plot
x = list(itertools.product(downs, plays))
# x = [('1', 'Pass'), ('1', 'Run'), ('1', 'Punt'), ..., ('4', 'Punt'), ('4', 'Field Goal')]

# create a list of Counters for each down--will include ALL PlayTypes for each down
plays_on_down = [Counter(team_df.loc[team_df['down'] == int(down)]['PlayType']) for down in downs]

# create a list of counts for each play in plays for each down in downs
counts = [plays_on_down[int(down)-1][play] for down, play in x]

# load the into the ColumnDataSource
source = ColumnDataSource(data=dict(x=x, counts=counts))

# get the figure ready
p = figure(x_range=FactorRange(*x), plot_height=350, plot_width=750, title='Play by Down',
toolbar_location=None, tools='')

# create the vbar
p.vbar(x='x', top='counts', width=0.9, source=source, line_color='white',
fill_color=factor_cmap('x', palette=Spectral[4], factors=plays, start=1, end=2))
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xaxis.axis_label = 'Down'
p.yaxis.axis_label = 'Number of Plays'
p.xgrid.grid_line_color = None
show(p)


For whatever reason, nothing happens when executed from the terminal.



Any help is greatly appreciated!



Thanks.










share|improve this question













I'm pretty new to Python and this is my first time using Bokeh. I've followed a tutorial using NFL data to show graphs and I cannot get the graph to show on my machine. The script runs without error, but nothing shows. I'm sure I'm missing something very simple... but I just don't know what that is... Can someone please help me? Below is my code:



import pandas as pd
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, FactorRange, FixedTicker
from bokeh.io import output_notebook
from collections import Counter
from bokeh.transform import factor_cmap
from bokeh.palettes import Paired, Spectral
import itertools
pd.set_option('display.max_columns', 150)
output_notebook()

filename = '/Users/ksilva/Downloads/NFL Play by Play 2009-2017 (v4).csv'
df = pd.read_csv(filename,dtype={25: object, 51: object})

# print(df.shape)

# df['down'].isnull().sum()
pd.to_numeric(df['down'], errors='coerce').isnull().sum()

# print(df.loc[51])

# filter by team if desired
team = 'all'
if team == 'all':
team_df = df
else:
team_df = df.loc[df['posteam'] == team]

# drop rows will null in the 'down' column
team_df = team_df.loc[df['down'].notnull()]

all_play_types = Counter(team_df['PlayType'])

# print(team_df)
# print(all_play_types)

# list of downs I care about
downs = ['1','2','3','4']

# list of plays I care about
plays = ['Pass', 'Run', 'Punt', 'Field Goal']

# define x-axis categories to be used in the vbar plot
x = list(itertools.product(downs, plays))
# x = [('1', 'Pass'), ('1', 'Run'), ('1', 'Punt'), ..., ('4', 'Punt'), ('4', 'Field Goal')]

# create a list of Counters for each down--will include ALL PlayTypes for each down
plays_on_down = [Counter(team_df.loc[team_df['down'] == int(down)]['PlayType']) for down in downs]

# create a list of counts for each play in plays for each down in downs
counts = [plays_on_down[int(down)-1][play] for down, play in x]

# load the into the ColumnDataSource
source = ColumnDataSource(data=dict(x=x, counts=counts))

# get the figure ready
p = figure(x_range=FactorRange(*x), plot_height=350, plot_width=750, title='Play by Down',
toolbar_location=None, tools='')

# create the vbar
p.vbar(x='x', top='counts', width=0.9, source=source, line_color='white',
fill_color=factor_cmap('x', palette=Spectral[4], factors=plays, start=1, end=2))
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xaxis.axis_label = 'Down'
p.yaxis.axis_label = 'Number of Plays'
p.xgrid.grid_line_color = None
show(p)


For whatever reason, nothing happens when executed from the terminal.



Any help is greatly appreciated!



Thanks.







python-3.x terminal bokeh






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 21 at 18:17









Kai

153




153












  • Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
    – Kai
    Nov 21 at 18:17




















  • Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
    – Kai
    Nov 21 at 18:17


















Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
– Kai
Nov 21 at 18:17






Here is the tutorial that I'm following: j253.github.io/blog/fun-with-nfl-stats.html
– Kai
Nov 21 at 18:17














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0
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You are setting calling output_notebook. This activates a mode that only diplays in a Jupyter notebook. If you want to execute plain python scripts to generate HTML file output, you should use output_file.






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    1 Answer
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    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

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    active

    oldest

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    up vote
    0
    down vote



    accepted










    You are setting calling output_notebook. This activates a mode that only diplays in a Jupyter notebook. If you want to execute plain python scripts to generate HTML file output, you should use output_file.






    share|improve this answer

























      up vote
      0
      down vote



      accepted










      You are setting calling output_notebook. This activates a mode that only diplays in a Jupyter notebook. If you want to execute plain python scripts to generate HTML file output, you should use output_file.






      share|improve this answer























        up vote
        0
        down vote



        accepted







        up vote
        0
        down vote



        accepted






        You are setting calling output_notebook. This activates a mode that only diplays in a Jupyter notebook. If you want to execute plain python scripts to generate HTML file output, you should use output_file.






        share|improve this answer












        You are setting calling output_notebook. This activates a mode that only diplays in a Jupyter notebook. If you want to execute plain python scripts to generate HTML file output, you should use output_file.







        share|improve this answer












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        share|improve this answer










        answered Nov 21 at 18:28









        bigreddot

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