July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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476
14
章 データ分析の実例
また少し工夫すれば、ある栄養素に対してどの食品が最も含有率が高いのかを計算することもでき
ます。
by_nutrient = ndata.groupby(['nutgroup', 'nutrient'])
get_maximum = lambda x: x.loc[x.value.idxmax()]
get_minimum = lambda x: x.loc[x.value.idxmin()]
max_foods = by_nutrient.apply(get_maximum)[['value', 'food']]
# food
を扱いやすいサイズに
max_foods.food = max_foods.food.str[:50]
得られたデータフレームオブジェクトは本文に掲載するには大きすぎるため、ここではアミノ酸
（
Amino Acids
）を例に取り上げます。
In [183]: max_foods.loc['Amino Acids']['food']
Out[183]:
nutrient
Alanine Gelatins, dry powder, unsweetened
Arginine Seeds, sesame flour, low-fat
Aspartic acid Soy protein isolate
Cystine Seeds, cottonseed flour, low fat (glandless)
Glutamic acid Soy protein isolate ...
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