Football

작성일자 : 2024-05-09Ver 0.1.1  시간 구간별 선수 활동량 지표 집계 및 시각화¶In [1]: import os# directory 변경new_dir = '/Users/limjongjun/Desktop/JayJay/Growth/Python/soccer-analytics'os.chdir(new_dir)import numpy as npimport pandas as pdfrom tqdm import tqdmimport matplotlib.pyplot as pltfrom src.plot_utils import draw_pitch (1) 가공 데이터 불러오기¶In [3]: match_id = 1# file = f'data_metrica/Sample_Game_{match_id}..

작성일자 : 2024-05-08Ver 0.1.1 데이터 준비¶In [1]: import os# directory 변경new_dir = '/Users/limjongjun/Desktop/JayJay/Growth/Python/soccer-analytics'os.chdir(new_dir)import numpy as npimport pandas as pdfrom tqdm import tqdmimport matplotlib.pyplot as pltfrom src.plot_utils import draw_pitch (1) 가공 데이터 불러오기¶In [3]: match_id = 1file = f'data_metrica/data/Sample_Game_{match_id}/Sample_Game_{mat..

작성일자 : 2024-05-07Ver 0.1.1강의에서 소개된 파이썬 주요 기능¶ffmpeg: https://anaconda.org/conda-forge/ffmpeg터미널에서 conda install -c conda-forge ffmpeg 명령어 실행scipy.signal.savgol_filter: https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.savgol_filter.htmlmatplotlib.pyplot.quiver: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.quiver.htmlmatplotlib.animation.FFMpegWriter: https://matplo..

작성일자 : 2023-12-29 Ver 0.1.1 강의에서 소개된 파이썬 주요 기능¶ numpy.ndarray.flatten: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flatten.html matplotlib.pyplot.text: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.text.html 위치 추적 데이터 준비¶ In [1]: import os import numpy as np import pandas as pd import matplotlib.pyplot as plt new_dir = '/Users/limjongjun/Desktop/JayJay/Growth/Pyt..