岩隈久志(SEA)のナイスピッチングをPythonで可視化(Jupyter,seaborn,pitchpx) ref: http://qiita.com/shinyorke/items/2c2e2c3976fc2d1ed051

const.py

# -*- coding: utf-8 -*-

class PitchPxConst(object):


    # 球種はこのリンクを参照 http://pitchfx.texasleaguers.com/
    PITCH_TYPES = {
        'FA': 'Fastball',
        'FF': 'four-seam Fastball',
        'FT': 'two-seam Fastball',
        'FC': 'Cut Fastball',
        'FS': 'Split-finger Fastball',
        'FO': 'Forkball',
        'SI': 'Sinker',
        'SL': 'Slider',
        'CU': 'Curveball',
        'KC': 'Knuckle Curve',
        'EP': 'Ephuus',
        'CH': 'Change-up',
        'SC': 'Screwball',
        'KN': 'Knuckleball',
        'UN': 'Unknown',
    }

    # markers(matplotlib)
    PITCH_TYPES_MARKERS = {
        'FA': '.',
        'FF': 'o',
        'FT': ',',
        'FC': 'p',
        'FS': 'v',
        'FO': 'v',
        'SI': '>',
        'SL': '<',
        'CU': '+',
        'KC': ',',
        'EP': 'D',
        'CH': 'o',
        'SC': 'H',
        'KN': '*',
        'UN': 'x',
    }

    # colors(matplotlib)
    PITCH_TYPES_COLORS = {
        'FA': 'red',
        'FF': 'red',
        'FT': 'red',
        'FC': 'red',
        'FS': 'red',
        'FO': 'blue',
        'SI': 'red',
        'SL': 'blue',
        'CU': 'green',
        'KC': 'yellow',
        'EP': 'green',
        'CH': 'green',
        'SC': 'yellow',
        'KN': 'white',
        'UN': 'black',
    }

file0.txt

$ pip install jupyter matplotlib pandas seaborn pitchpx

file1.txt

$ pitchpx --help

file2.txt

Options:
  -s, --start TEXT  Start Day(YYYYMMDD)  [required]
  -e, --end TEXT    End Day(YYYYMMDD)  [required]
  -o, --out TEXT    Output directory(default:".")  [required]
  --help            Show this message and exit.

file3.txt

$ pitchpx -s 20150807 -e 20150807 -o ./data
$ pitchpx -s 20150812 -e 20150812 -o ./data
$ pitchpx -s 20150818 -e 20150818 -o ./data

file4.txt

$ pitchpx -s 20150807 -e 20150818 -o ./data

file5.txt

$ Jupyter notebook

hisashi_iwakuma.py

from pitchpx.const import PitchPxConst

# 一試合の投球を可視化(pz:高さ, px:幅)
axarray = {day: None for day in iwakuma_pitch_data.keys()}
f, (axarray) = plt.subplots(1, len(iwakuma_pitch_data.keys()), sharey=True, figsize=(24,6))

# TODO ストライクゾーンを描きたかったが断念(誰かおしえて)
for i, day in enumerate(iwakuma_pitch_data.keys()):
    axarray[i].set_title('Hisashi Iwakuma({day})'.format(day=day))
    datasets = iwakuma_pitch_data[day]
    for k, v in PitchPxConst.PITCH_TYPES.items():
        ds = datasets.query('pitch_type=="{type}"'.format(type=k))
        if ds.empty:
            continue
        ds.plot(
            kind='scatter', 
            x='px', 
            y='pz', 
            label=PitchPxConst.PITCH_TYPES[k], 
            color=PitchPxConst.PITCH_TYPES_COLORS[k], 
            marker=PitchPxConst.PITCH_TYPES_MARKERS[k], 
            xlim=(-3.0, 3.0), 
            ylim=(-1.0, 6.0), 
            ax=axarray[i]
        )