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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253
11.3 男女間の格差
plots
）に記載されています。
調査を男女間格差に広げ、プロットに関するノウハウを増やしていきましょう。
11.3
男女間の格差
図
11-1
に示した性別ごとの受賞数を受賞分野ごとに分類してみましょう。
pandas
の
groupby()
メソッドはグループ化する列のリストを取り、各グループには複数のキーでアクセスできます。
by_cat_gen = df.groupby(['category','gender'])
by_cat_gen.get_group(('Physics', 'female'))[['name', 'year']] #
❶
Out:
name year
268 Maria Goeppert-Mayer 1963
613 Marie Sk?odowska-Curie 1903
❶
category
と
gender
キーを使ってグループを取得する。
size
メソッドを使ってグループのサイズを取得すると、分野と性別の両方で値にラベルを付け
る
MultiIndex
を持つ
Series
を返します。
by_cat_gen.size()
Out:
category gender
Chemistry female 4
male 167
Economics female 1
male 74
...
Physiology or Medicine female 11
male 191
dtype: int64
kind
引数に
barh
を使うと、このマルチインデックス化した
Series
を直接プロットすることが ...
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