Marathon Data¶

In [1]:

data_url = '../data/NYCM2008.csv'

import pandas as pd
df = pd.read_csv(data_url)
df.head()

Out[1]:

	age	gender	split	final
0	31	M	1:06:07	2:08:43
1	32	M	1:06:06	2:09:07
2	30	M	1:06:06	2:11:22
3	39	M	1:06:06	2:13:10
4	30	M	1:06:06	2:13:33

In [2]:

df['split_sec'] = pd.to_timedelta(df.split).apply(lambda x: x.seconds)
df['final_sec'] = pd.to_timedelta(df.final).apply(lambda x: x.seconds)
df.head()

Out[2]:

	age	gender	split	final	split_sec	final_sec
0	31	M	1:06:07	2:08:43	3967	7723
1	32	M	1:06:06	2:09:07	3966	7747
2	30	M	1:06:06	2:11:22	3966	7882
3	39	M	1:06:06	2:13:10	3966	7990
4	30	M	1:06:06	2:13:33	3966	8013

In [3]:

from altair import expr

data = expr.DataFrame(data_url)

def seconds(val):
    return (3600 * expr.parseInt(expr.slice(val, 0, 1)) +
            60 * expr.parseInt(expr.slice(val, 2, 4)) +
            expr.parseInt(expr.slice(val, 5, 7)))

data['split_sec'] = seconds(data.split)
data['final_sec'] = seconds(data.final)

In [4]:

from altair import *

gender_color = Color('gender:N',
                     scale=Scale(domain=["W", "M"],
                                 range=['#EA98D2', '#659CCA']))

Chart(data).mark_circle(opacity=0.1, size=4).encode(
    x='split_sec',
    y='final_sec',
    color=gender_color
).configure_cell(width=400, height=400)

In [5]:

data['split_frac'] = (data.final_sec - data.split_sec) // data.split_sec - 1

Chart(data).mark_circle(opacity=0.1, size=4).encode(
    x='final_sec',
    y='split_frac',
    color=gender_color,
    column='gender:N',
).configure_cell(height=300, width=300)

In [6]:

# filter the data so that split_frac is in this range
data = data[(data.split_frac < 1.2) & (data.split_frac > -0.2)]

Chart(data).mark_bar().encode(
    x=X('split_frac', bin=Bin(maxbins=50)),
    y='count(*):Q',
    color=gender_color,
    column='gender',
).configure_cell(width=200)

In [7]:

Chart(data).mark_area(
    stacked='center'
).encode(
    x=X('count(*):Q', axis=Axis(grid=False)),
    y=Y('split_frac', bin=Bin(maxbins=100)),
    column='gender',
    color=gender_color,
).configure_cell(width=150)

In [10]:

data = data[(data.age > 10) & (data.age < 70)]

Chart(data).mark_area(
    stacked='center'
).encode(
    x=X('count(*):Q', axis=Axis(grid=False, labels=False, title=' ')),
    y=Y('split_frac', bin=Bin(maxbins=50)),
    column=Column('age', bin=Bin(step=10, min=10, max=70),
                  axis=Axis(title='age range')),
    color=gender_color,
).configure_cell(width=80, height=200)

In [ ]: