August 2017
Intermediate to advanced
500 pages
12h 3m
Japanese
Content preview from PythonとJavaScriptではじめるデータビジュアライゼーション
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270
11 章 pandas を使ったデータ探索
11.5.2
受賞者の没年齢
ここでは、出生日から死亡日を引いて受賞者の没年齢を調べましょう。このデータを新しい
'age_at_death'
列に保存します。
df['age_at_death'] = (df.date_of_death - df.date_of_birth)\
.dt.days/365 #
❶
❶
datetime64
データは適切に加算や減算を実行し、
pandas
の
timedelta
列を作成する。
timedelta
の
dt
メソッドを使って間隔の日数を取得し、それを
365
で割って死亡時の年齢を浮動小数点数で入手
する。
'age_at_death'
列のコピーを作成し
†
、空の
NaN
行をすべて削除します。すると、そのデータを
使って図
11-21
に示すヒストグラムと
KDE
を作成できます。
† 日数から年数を求める計算が面倒になる原因のうるう年やその他の細かい点は無視します。
女性 男性
性別
図
11-19
性別ごとの受賞年齢
女性 男性
性別
図
11-20
性別ごとの受賞年齢分布のバイオリンプロット
271
11.5 受賞者の年齢と没年齢
age_at_death = df[df.age_at_death.notnull()].age_at_death #
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