Python in Excel を軽く試した

使ったデータ

まずは、グーグルコラボで以下の藤浪投手のデータを準備

!pip install pybaseball

import pandas as pd
from pybaseball import statcast

dates = [
    '2023-04-01', '2023-04-08', '2023-04-15', '2023-04-22',
    '2023-04-26', '2023-04-28', '2023-05-02', '2023-05-05',
    '2023-05-07', '2023-05-10', '2023-05-12', '2023-05-16',
    '2023-05-17', '2023-05-22', '2023-05-27', '2023-05-29',
    '2023-05-30', '2023-06-02', '2023-06-05', '2023-06-10',
    '2023-06-11', '2023-06-13', '2023-06-18', '2023-06-20',
    '2023-06-24', '2023-06-28', '2023-06-30', '2023-07-01',
    '2023-07-04', '2023-07-08', '2023-07-09', '2023-07-14',
    '2023-07-16', '2023-07-18', '2023-07-21', '2023-07-22',
    '2023-07-25', '2023-07-28', '2023-07-30', '2023-08-02',
    '2023-08-04', '2023-08-06', '2023-08-09', '2023-08-13',
    '2023-08-15', '2023-08-16', '2023-08-19', '2023-08-20',
    '2023-08-23', '2023-08-25', '2023-08-28', '2023-08-29',
    '2023-09-01', '2023-09-05', '2023-09-06'
]


# Create an empty DataFrame to store the data
df_660261_all_dates = pd.DataFrame()

# Fetch data for each date and concatenate
for date in dates:
    df_single_day = statcast(start_dt=date, end_dt=date)
    df_660261_single_day = df_single_day[df_single_day['pitcher'] == 660261]
    df_660261_all_dates = pd.concat([df_660261_all_dates, df_660261_single_day])

# Reset the index of the final DataFrame
df_660261_all_dates.reset_index(drop=True, inplace=True)

グーグルドライブへ保存

from google.colab import drive
drive.mount('/content/drive')

df_660261_all_dates.to_excel("/content/drive/My Drive/Fujinami_230909.xlsx", index=False)

こんなデータ

4/1 投球カウント

このデータをdfとして、python in Excel でグラフ表示をしてみた

import pandas as pd
import matplotlib.pyplot as plt

def pitch_counts(df):
    df_L = df[df['stand'] == 'L']
    df_R = df[df['stand'] == 'R']
    
    total_counts = df['pitch_type'].value_counts()
    left_counts = df_L['pitch_type'].value_counts()
    right_counts = df_R['pitch_type'].value_counts()
    
    pitch_counts_table = pd.DataFrame({'Total': total_counts, 'Left Batter': left_counts, 'Right Batter': right_counts})
    
    pitch_counts_table.fillna(0, inplace=True)
    pitch_counts_table = pitch_counts_table.astype(int)
    
    return pitch_counts_table

# 仮のデータフレームdf。実際にはpybaseballから取得
# df = ...

# 指定の日付を選択。'2023/4/1 0:00:00'が指定の日付だと仮定
specified_date = '2023-04-01 0:00:00'

# 指定された日付のデータだけ抽出
df_date = df[df['game_date'] == specified_date]

# ピッチカウントを取得
pitch_counts_date = pitch_counts(df_date)

# 時間部分を削除
date_str = pd.Timestamp(specified_date).strftime('%Y-%m-%d')

# 円グラフを描画
plt.figure(figsize=(10, 6))
plt.pie(pitch_counts_date['Total'], labels = pitch_counts_date.index, autopct='%1.1f%%')
plt.title(f'Pitch Type Counts for {date_str}')
plt.show()

複数日のグラフ化

最新のグラフしか出ない。複数日のグラフが表示されず。

import pandas as pd
import matplotlib.pyplot as plt

# ピッチカウントの関数
def pitch_counts(df):
    total_counts = df['pitch_type'].value_counts()
    pitch_counts_table = pd.DataFrame({'Total': total_counts})
    pitch_counts_table.fillna(0, inplace=True)
    pitch_counts_table = pitch_counts_table.astype(int)
    return pitch_counts_table

# 仮のデータフレームdf。実際にはpybaseballから取得
# df = ...

# 一意な日付を取得
unique_dates = df['game_date'].unique()

# 各日付に対して円グラフを作成
for specified_date in unique_dates:
    df_date = df[df['game_date'] == specified_date]
    pitch_counts_date = pitch_counts(df_date)
    
    # 時間部分を削除
    date_str = pd.Timestamp(specified_date).strftime('%Y-%m-%d')

    # 円グラフを描画
    plt.figure(figsize=(10, 6))
    plt.pie(pitch_counts_date['Total'], labels=pitch_counts_date.index, autopct='%1.1f%%')
    plt.title(f'Pitch Type Counts for {date_str}')
    plt.show()

各日付 vs 左右

こういう複数グラフは表示できるんだけど、他の日の分は出てこない

import pandas as pd
import matplotlib.pyplot as plt

def plot_pitch_distribution(df, date):
    # 時間部分を削除
    date_str = pd.Timestamp(date).strftime('%Y-%m-%d')

    df_L = df[df['stand'] == 'L']
    df_R = df[df['stand'] == 'R']

    fig, axs = plt.subplots(1, 3, figsize=(18, 6))
    plt.suptitle(f'Pitch Distribution on {date_str}')

    # Total
    if not df['pitch_type'].value_counts().empty:
        df['pitch_type'].value_counts().plot(kind='pie', ax=axs[0], autopct='%.1f%%')
        axs[0].set_title('Total')
        axs[0].set_ylabel('')

    # vs Left batter
    if not df_L['pitch_type'].value_counts().empty:
        df_L['pitch_type'].value_counts().plot(kind='pie', ax=axs[1], autopct='%.1f%%')
        axs[1].set_title('vs Left batter')
        axs[1].set_ylabel('')

    # vs Right batter
    if not df_R['pitch_type'].value_counts().empty:
        df_R['pitch_type'].value_counts().plot(kind='pie', ax=axs[2], autopct='%.1f%%')
        axs[2].set_title('vs Right batter')
        axs[2].set_ylabel('')

    plt.show()

# 仮のデータフレームdf。実際にはpybaseballから取得
# df = ...

unique_dates = df['game_date'].unique()

for specified_date in unique_dates:
    df_date = df[df['game_date'] == specified_date]
    if df_date.empty:
        print(f"No data for {specified_date}")
        continue
    plot_pitch_distribution(df_date, specified_date)

また触ってみよ