August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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173
173
12.2 プロット
これらのグループについて
GroupByDay
を繰り返します。これは、その日の平均価
格を計算して、新たな
DataFrame
を返します。
def GroupByDay(transactions, func=np.mean):
grouped = transactions[['date', 'ppg']].groupby('date')
daily = grouped.aggregate(func)
daily['date'] = daily.index
start = daily.date[0]
one_year = np.timedelta64(1, 'Y')
daily['years'] = (daily.date - start) / one_year
return daily
パラメータ
transactions
は、
date
と
ppg
とをカラムに持つ
DataFrame
です。こ
の
2
つのカラムを選んで、
date
でグループ分けします。
結果の
grouped
は、日付からその日に報告された価格を含む
DataFrame
への対応
付けです。
aggregate
は、
grouped
の各要素に、グループの各カラムに引数の関数を
繰り返し適用する
GroupBy
メソッドです。この場合には、
ppg
というカラムしかあり
ません。したがって、
aggregate
の結果は、各日付ごとに、
1
つのカラム
ppg
を持つ
1
つの行がある
DataFrame
です。
この
DataFrame
の日付は、
NumPy
の
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