## Relabel Plays Columns for Readability
plays.columns = [
'type', 'inning', 'team', 'player', 'count', 'pitches', 'event', 'game_id',
'year'
]
## Shift DataFrame to remove the same at bat
pa = plays.loc[plays['player'].shift() != plays['player'],
['year', 'game_id', 'inning', 'team', 'player']]
## Group Plate Appearances
pa = pa.groupby(['year', 'game_id', 'team']).size().reset_index(name='PA')
## Reshape Data by Event Type Per Plate Appearance by Setting Event Index and Unstacking the Resulting Frame
events = events.set_index(['year', 'game_id', 'team', 'event_type'])
events = events.unstack().fillna(0).reset_index()
## Clean Events Columns Labels
events.columns = events.columns.droplevel()
events.columns = [
'year', 'game_id', 'team', 'BB', 'E', 'H', 'HBP', 'HR', 'ROE', 'SO'
]
events = events.rename_axis(None, axis='columns')
## Merge Plate Appearances
events_plus_pa = pd.merge(events,
pa,
how='outer',
left_on=['year', 'game_id', 'team'],
right_on=['year', 'game_id', 'team'])
import pandas as pd
import matplotlib.pyplot as plt
from frames import games, info, events
plays = games.query("type == 'play' & event != 'NP'")
plays.columns = ["type", "inning", "team", "player", "count", "pitches", "event", "game_id", "year"]
pa = plays.loc[plays["player"].shift() != plays["player"], ["year", "game_id", "inning", "team", "player"]]
pa = pa.groupby(["year", "game_id", "team"]).size().reset_index(name="PA")
events = events.set_index(["year", "game_id", "team", "event_type"])
events = events.unstack().fillna(0).reset_index()
events.columns = events.columns.droplevel()
events.columns = ["year", "game_id", "team", "BB", "E", "H", "HBP", "HR", "ROE","SO"]
events = events.rename_axis("None", axis="columns")
events_plus_pa = pd.merge(events, pa, how="outer", left_on=["year", "game_id", "team"], right_on=["year", "game_id", "team"])
defense = pd.merge(events_plus_pa, info)
defense.loc[:, "DER"] = 1 - ((defense["H"] + defense["ROE"]) / (defense["PA"] - defense["BB"] - defense["SO"] - defense["HBP"] - defense["HR"]))
defense.loc[:, "year"] = pd.to_numeric(defense["year"])
der = defense.loc[defense["year"] >= 1978, ["year", "defense", "DER"]]
der = der.pivot(index="year", columns="defense", values="DER")
der.plot(x_compat=True, xticks=range(1978, 2018, 4), rot=45)
plt.savefig("defense.png")
plt.show()