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  • 数据分析---《Python for Data Analysis》学习笔记【04】

    《Python for Data Analysis》一书由Wes Mckinney所著,中文译名是《利用Python进行数据分析》。这里记录一下学习过程,其中有些方法和书中不同,是按自己比较熟悉的方式实现的。

    第四个实例:USDA Food Database

    简介:美国农业部(USDA)制作了一份有关食物营养信息的数据

    数据下载地址: https://github.com/wesm/pydata-book/tree/2nd-edition/datasets/usda_food

    准备工作:导入pandas和matplotlib,因为需要读取JSON格式的文件,因此这里还需要导入json模块

    import pandas as pd
    import json
    import matplotlib.pyplot as plt
    fig,ax=plt.subplots()

    使用json模块打开database.json文件:

    with open (r"C:UsersccavDownloadsdatabase.json") as f:
        data=json.load(f)

    文件第一项就含有这么多内容:

    [{'id': 1008, 'description': 'Cheese, caraway', 'tags': [], 'manufacturer': '', 'group': 'Dairy and Egg Products', 'portions': [{'amount': 1, 'unit': 'oz', 'grams': 28.35}], 'nutrients': [{'value': 25.18, 'units': 'g', 'description': 'Protein', 'group': 'Composition'}, {'value': 29.2, 'units': 'g', 'description': 'Total lipid (fat)', 'group': 'Composition'}, {'value': 3.06, 'units': 'g', 'description': 'Carbohydrate, by difference', 'group': 'Composition'}, {'value': 3.28, 'units': 'g', 'description': 'Ash', 'group': 'Other'}, {'value': 376.0, 'units': 'kcal', 'description': 'Energy', 'group': 'Energy'}, {'value': 39.28, 'units': 'g', 'description': 'Water', 'group': 'Composition'}, {'value': 1573.0, 'units': 'kJ', 'description': 'Energy', 'group': 'Energy'}, {'value': 0.0, 'units': 'g', 'description': 'Fiber, total dietary', 'group': 'Composition'}, {'value': 673.0, 'units': 'mg', 'description': 'Calcium, Ca', 'group': 'Elements'}, {'value': 0.64, 'units': 'mg', 'description': 'Iron, Fe', 'group': 'Elements'}, {'value': 22.0, 'units': 'mg', 'description': 'Magnesium, Mg', 'group': 'Elements'}, {'value': 490.0, 'units': 'mg', 'description': 'Phosphorus, P', 'group': 'Elements'}, {'value': 93.0, 'units': 'mg', 'description': 'Potassium, K', 'group': 'Elements'}, {'value': 690.0, 'units': 'mg', 'description': 'Sodium, Na', 'group': 'Elements'}, {'value': 2.94, 'units': 'mg', 'description': 'Zinc, Zn', 'group': 'Elements'}, {'value': 0.024, 'units': 'mg', 'description': 'Copper, Cu', 'group': 'Elements'}, {'value': 0.021, 'units': 'mg', 'description': 'Manganese, Mn', 'group': 'Elements'}, {'value': 14.5, 'units': 'mcg', 'description': 'Selenium, Se', 'group': 'Elements'}, {'value': 1054.0, 'units': 'IU', 'description': 'Vitamin A, IU', 'group': 'Vitamins'}, {'value': 262.0, 'units': 'mcg', 'description': 'Retinol', 'group': 'Vitamins'}, {'value': 271.0, 'units': 'mcg_RAE', 'description': 'Vitamin A, RAE', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mg', 'description': 'Vitamin C, total ascorbic acid', 'group': 'Vitamins'}, {'value': 0.031, 'units': 'mg', 'description': 'Thiamin', 'group': 'Vitamins'}, {'value': 0.45, 'units': 'mg', 'description': 'Riboflavin', 'group': 'Vitamins'}, {'value': 0.18, 'units': 'mg', 'description': 'Niacin', 'group': 'Vitamins'}, {'value': 0.19, 'units': 'mg', 'description': 'Pantothenic acid', 'group': 'Vitamins'}, {'value': 0.074, 'units': 'mg', 'description': 'Vitamin B-6', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, total', 'group': 'Vitamins'}, {'value': 0.27, 'units': 'mcg', 'description': 'Vitamin B-12', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mcg', 'description': 'Folic acid', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, food', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg_DFE', 'description': 'Folate, DFE', 'group': 'Vitamins'}, {'value': 93.0, 'units': 'mg', 'description': 'Cholesterol', 'group': 'Other'}, {'value': 18.584, 'units': 'g', 'description': 'Fatty acids, total saturated', 'group': 'Other'}, {'value': 8.275, 'units': 'g', 'description': 'Fatty acids, total monounsaturated', 'group': 'Other'}, {'value': 0.83, 'units': 'g', 'description': 'Fatty acids, total polyunsaturated', 'group': 'Other'}, {'value': 0.324, 'units': 'g', 'description': 'Tryptophan', 'group': 'Amino Acids'}, {'value': 0.896, 'units': 'g', 'description': 'Threonine', 'group': 'Amino Acids'}, {'value': 1.563, 'units': 'g', 'description': 'Isoleucine', 'group': 'Amino Acids'}, {'value': 2.412, 'units': 'g', 'description': 'Leucine', 'group': 'Amino Acids'}, {'value': 2.095, 'units': 'g', 'description': 'Lysine', 'group': 'Amino Acids'}, {'value': 0.659, 'units': 'g', 'description': 'Methionine', 'group': 'Amino Acids'}, {'value': 0.126, 'units': 'g', 'description': 'Cystine', 'group': 'Amino Acids'}, {'value': 1.326, 'units': 'g', 'description': 'Phenylalanine', 'group': 'Amino Acids'}, {'value': 1.216, 'units': 'g', 'description': 'Tyrosine', 'group': 'Amino Acids'}, {'value': 1.682, 'units': 'g', 'description': 'Valine', 'group': 'Amino Acids'}, {'value': 0.952, 'units': 'g', 'description': 'Arginine', 'group': 'Amino Acids'}, {'value': 0.884, 'units': 'g', 'description': 'Histidine', 'group': 'Amino Acids'}, {'value': 0.711, 'units': 'g', 'description': 'Alanine', 'group': 'Amino Acids'}, {'value': 1.618, 'units': 'g', 'description': 'Aspartic acid', 'group': 'Amino Acids'}, {'value': 6.16, 'units': 'g', 'description': 'Glutamic acid', 'group': 'Amino Acids'}, {'value': 0.439, 'units': 'g', 'description': 'Glycine', 'group': 'Amino Acids'}, {'value': 2.838, 'units': 'g', 'description': 'Proline', 'group': 'Amino Acids'}, {'value': 1.472, 'units': 'g', 'description': 'Serine', 'group': 'Amino Acids'}, {'value': 25.18, 'units': 'g', 'description': 'Protein', 'group': 'Composition'}, {'value': 29.2, 'units': 'g', 'description': 'Total lipid (fat)', 'group': 'Composition'}, {'value': 3.06, 'units': 'g', 'description': 'Carbohydrate, by difference', 'group': 'Composition'}, {'value': 3.28, 'units': 'g', 'description': 'Ash', 'group': 'Other'}, {'value': 376.0, 'units': 'kcal', 'description': 'Energy', 'group': 'Energy'}, {'value': 39.28, 'units': 'g', 'description': 'Water', 'group': 'Composition'}, {'value': 1573.0, 'units': 'kJ', 'description': 'Energy', 'group': 'Energy'}, {'value': 0.0, 'units': 'g', 'description': 'Fiber, total dietary', 'group': 'Composition'}, {'value': 673.0, 'units': 'mg', 'description': 'Calcium, Ca', 'group': 'Elements'}, {'value': 0.64, 'units': 'mg', 'description': 'Iron, Fe', 'group': 'Elements'}, {'value': 22.0, 'units': 'mg', 'description': 'Magnesium, Mg', 'group': 'Elements'}, {'value': 490.0, 'units': 'mg', 'description': 'Phosphorus, P', 'group': 'Elements'}, {'value': 93.0, 'units': 'mg', 'description': 'Potassium, K', 'group': 'Elements'}, {'value': 690.0, 'units': 'mg', 'description': 'Sodium, Na', 'group': 'Elements'}, {'value': 2.94, 'units': 'mg', 'description': 'Zinc, Zn', 'group': 'Elements'}, {'value': 0.024, 'units': 'mg', 'description': 'Copper, Cu', 'group': 'Elements'}, {'value': 0.021, 'units': 'mg', 'description': 'Manganese, Mn', 'group': 'Elements'}, {'value': 14.5, 'units': 'mcg', 'description': 'Selenium, Se', 'group': 'Elements'}, {'value': 1054.0, 'units': 'IU', 'description': 'Vitamin A, IU', 'group': 'Vitamins'}, {'value': 262.0, 'units': 'mcg', 'description': 'Retinol', 'group': 'Vitamins'}, {'value': 271.0, 'units': 'mcg_RAE', 'description': 'Vitamin A, RAE', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mg', 'description': 'Vitamin C, total ascorbic acid', 'group': 'Vitamins'}, {'value': 0.031, 'units': 'mg', 'description': 'Thiamin', 'group': 'Vitamins'}, {'value': 0.45, 'units': 'mg', 'description': 'Riboflavin', 'group': 'Vitamins'}, {'value': 0.18, 'units': 'mg', 'description': 'Niacin', 'group': 'Vitamins'}, {'value': 0.19, 'units': 'mg', 'description': 'Pantothenic acid', 'group': 'Vitamins'}, {'value': 0.074, 'units': 'mg', 'description': 'Vitamin B-6', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, total', 'group': 'Vitamins'}, {'value': 0.27, 'units': 'mcg', 'description': 'Vitamin B-12', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mcg', 'description': 'Folic acid', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, food', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg_DFE', 'description': 'Folate, DFE', 'group': 'Vitamins'}, {'value': 0.324, 'units': 'g', 'description': 'Tryptophan', 'group': 'Amino Acids'}, {'value': 0.896, 'units': 'g', 'description': 'Threonine', 'group': 'Amino Acids'}, {'value': 1.563, 'units': 'g', 'description': 'Isoleucine', 'group': 'Amino Acids'}, {'value': 2.412, 'units': 'g', 'description': 'Leucine', 'group': 'Amino Acids'}, {'value': 2.095, 'units': 'g', 'description': 'Lysine', 'group': 'Amino Acids'}, {'value': 0.659, 'units': 'g', 'description': 'Methionine', 'group': 'Amino Acids'}, {'value': 0.126, 'units': 'g', 'description': 'Cystine', 'group': 'Amino Acids'}, {'value': 1.326, 'units': 'g', 'description': 'Phenylalanine', 'group': 'Amino Acids'}, {'value': 1.216, 'units': 'g', 'description': 'Tyrosine', 'group': 'Amino Acids'}, {'value': 1.682, 'units': 'g', 'description': 'Valine', 'group': 'Amino Acids'}, {'value': 0.952, 'units': 'g', 'description': 'Arginine', 'group': 'Amino Acids'}, {'value': 0.884, 'units': 'g', 'description': 'Histidine', 'group': 'Amino Acids'}, {'value': 0.711, 'units': 'g', 'description': 'Alanine', 'group': 'Amino Acids'}, {'value': 1.618, 'units': 'g', 'description': 'Aspartic acid', 'group': 'Amino Acids'}, {'value': 6.16, 'units': 'g', 'description': 'Glutamic acid', 'group': 'Amino Acids'}, {'value': 0.439, 'units': 'g', 'description': 'Glycine', 'group': 'Amino Acids'}, {'value': 2.838, 'units': 'g', 'description': 'Proline', 'group': 'Amino Acids'}, {'value': 1.472, 'units': 'g', 'description': 'Serine', 'group': 'Amino Acids'}, {'value': 93.0, 'units': 'mg', 'description': 'Cholesterol', 'group': 'Other'}, {'value': 18.584, 'units': 'g', 'description': 'Fatty acids, total saturated', 'group': 'Other'}, {'value': 8.275, 'units': 'g', 'description': 'Fatty acids, total monounsaturated', 'group': 'Other'}, {'value': 0.83, 'units': 'g', 'description': 'Fatty acids, total polyunsaturated', 'group': 'Other'}, {'value': 25.18, 'units': 'g', 'description': 'Protein', 'group': 'Composition'}, {'value': 29.2, 'units': 'g', 'description': 'Total lipid (fat)', 'group': 'Composition'}, {'value': 3.06, 'units': 'g', 'description': 'Carbohydrate, by difference', 'group': 'Composition'}, {'value': 3.28, 'units': 'g', 'description': 'Ash', 'group': 'Other'}, {'value': 376.0, 'units': 'kcal', 'description': 'Energy', 'group': 'Energy'}, {'value': 39.28, 'units': 'g', 'description': 'Water', 'group': 'Composition'}, {'value': 1573.0, 'units': 'kJ', 'description': 'Energy', 'group': 'Energy'}, {'value': 0.0, 'units': 'g', 'description': 'Fiber, total dietary', 'group': 'Composition'}, {'value': 673.0, 'units': 'mg', 'description': 'Calcium, Ca', 'group': 'Elements'}, {'value': 0.64, 'units': 'mg', 'description': 'Iron, Fe', 'group': 'Elements'}, {'value': 22.0, 'units': 'mg', 'description': 'Magnesium, Mg', 'group': 'Elements'}, {'value': 490.0, 'units': 'mg', 'description': 'Phosphorus, P', 'group': 'Elements'}, {'value': 93.0, 'units': 'mg', 'description': 'Potassium, K', 'group': 'Elements'}, {'value': 690.0, 'units': 'mg', 'description': 'Sodium, Na', 'group': 'Elements'}, {'value': 2.94, 'units': 'mg', 'description': 'Zinc, Zn', 'group': 'Elements'}, {'value': 0.024, 'units': 'mg', 'description': 'Copper, Cu', 'group': 'Elements'}, {'value': 0.021, 'units': 'mg', 'description': 'Manganese, Mn', 'group': 'Elements'}, {'value': 14.5, 'units': 'mcg', 'description': 'Selenium, Se', 'group': 'Elements'}, {'value': 1054.0, 'units': 'IU', 'description': 'Vitamin A, IU', 'group': 'Vitamins'}, {'value': 262.0, 'units': 'mcg', 'description': 'Retinol', 'group': 'Vitamins'}, {'value': 271.0, 'units': 'mcg_RAE', 'description': 'Vitamin A, RAE', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mg', 'description': 'Vitamin C, total ascorbic acid', 'group': 'Vitamins'}, {'value': 0.031, 'units': 'mg', 'description': 'Thiamin', 'group': 'Vitamins'}, {'value': 0.45, 'units': 'mg', 'description': 'Riboflavin', 'group': 'Vitamins'}, {'value': 0.18, 'units': 'mg', 'description': 'Niacin', 'group': 'Vitamins'}, {'value': 0.19, 'units': 'mg', 'description': 'Pantothenic acid', 'group': 'Vitamins'}, {'value': 0.074, 'units': 'mg', 'description': 'Vitamin B-6', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, total', 'group': 'Vitamins'}, {'value': 0.27, 'units': 'mcg', 'description': 'Vitamin B-12', 'group': 'Vitamins'}, {'value': 0.0, 'units': 'mcg', 'description': 'Folic acid', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg', 'description': 'Folate, food', 'group': 'Vitamins'}, {'value': 18.0, 'units': 'mcg_DFE', 'description': 'Folate, DFE', 'group': 'Vitamins'}, {'value': 0.324, 'units': 'g', 'description': 'Tryptophan', 'group': 'Amino Acids'}, {'value': 0.896, 'units': 'g', 'description': 'Threonine', 'group': 'Amino Acids'}, {'value': 1.563, 'units': 'g', 'description': 'Isoleucine', 'group': 'Amino Acids'}, {'value': 2.412, 'units': 'g', 'description': 'Leucine', 'group': 'Amino Acids'}, {'value': 2.095, 'units': 'g', 'description': 'Lysine', 'group': 'Amino Acids'}, {'value': 0.659, 'units': 'g', 'description': 'Methionine', 'group': 'Amino Acids'}, {'value': 0.126, 'units': 'g', 'description': 'Cystine', 'group': 'Amino Acids'}, {'value': 1.326, 'units': 'g', 'description': 'Phenylalanine', 'group': 'Amino Acids'}, {'value': 1.216, 'units': 'g', 'description': 'Tyrosine', 'group': 'Amino Acids'}, {'value': 1.682, 'units': 'g', 'description': 'Valine', 'group': 'Amino Acids'}, {'value': 0.952, 'units': 'g', 'description': 'Arginine', 'group': 'Amino Acids'}, {'value': 0.884, 'units': 'g', 'description': 'Histidine', 'group': 'Amino Acids'}, {'value': 0.711, 'units': 'g', 'description': 'Alanine', 'group': 'Amino Acids'}, {'value': 1.618, 'units': 'g', 'description': 'Aspartic acid', 'group': 'Amino Acids'}, {'value': 6.16, 'units': 'g', 'description': 'Glutamic acid', 'group': 'Amino Acids'}, {'value': 0.439, 'units': 'g', 'description': 'Glycine', 'group': 'Amino Acids'}, {'value': 2.838, 'units': 'g', 'description': 'Proline', 'group': 'Amino Acids'}, {'value': 1.472, 'units': 'g', 'description': 'Serine', 'group': 'Amino Acids'}, {'value': 93.0, 'units': 'mg', 'description': 'Cholesterol', 'group': 'Other'}, {'value': 18.584, 'units': 'g', 'description': 'Fatty acids, total saturated', 'group': 'Other'}, {'value': 8.275, 'units': 'g', 'description': 'Fatty acids, total monounsaturated', 'group': 'Other'}, {'value': 0.83, 'units': 'g', 'description': 'Fatty acids, total polyunsaturated', 'group': 'Other'}]}]

    字典的键分别是'id', 'description', 'tags', 'manufacturer', 'group', 'portions', 'nutrients'。

    其中nutrients一栏就含有N多内容,我们把文件第一项的nutrients一栏变成DataFrame格式看一下:

    nutrients=pd.DataFrame(data[0]['nutrients'])

    nutrients的前5行显示如下:

                                description        group    units     value
    0                               Protein  Composition        g    25.180
    1                     Total lipid (fat)  Composition        g    29.200
    2           Carbohydrate, by difference  Composition        g     3.060
    3                                   Ash        Other        g     3.280
    4                                Energy       Energy     kcal   376.000

    可以看出,原文件包含的内容太多,而且现有的格式不方便做数据分析。因此,我们接下来提取需要的数据,并转换其格式。

    我们把'id', 'description', 'manufacturer', 'group'这四栏提取出来,并将其变为DataFrame格式:

    info=pd.DataFrame(data, columns=['id', 'description', 'manufacturer', 'group'])

    这是info的前5行:

         id                         description manufacturer  
    0  1008                     Cheese, caraway                
    1  1009                     Cheese, cheddar                
    2  1018                        Cheese, edam                
    3  1019                        Cheese, feta                
    4  1028  Cheese, mozzarella, part skim milk                
    
                        group  
    0  Dairy and Egg Products  
    1  Dairy and Egg Products  
    2  Dairy and Egg Products  
    3  Dairy and Egg Products  
    4  Dairy and Egg Products

    接下来让我们看一下每个食物类别分别包含多少数量的食物:

    group_count=info["group"].value_counts()

    这是group_count的前10行:

    Vegetables and Vegetable Products    812
    Beef Products                        618
    Baked Products                       496
    Breakfast Cereals                    403
    Fast Foods                           365
    Legumes and Legume Products          365
    Lamb, Veal, and Game Products        345
    Sweets                               341
    Fruits and Fruit Juices              328
    Pork Products                        328

    属于蔬菜和蔬菜制品一类的食物是最多的。

    但是info表没有包含营养成分这一栏(我们就是要分析食物的营养成分不是吗?),而nutrients表只有营养成分,却没有显示其对应的食物。因此,我们需要把这两张表结合起来。具体来说,就是先把每个食物的nutrients一栏提取出来,变成DataFrame格式,然后在上面添加对应的食物信息,最后把这些表用concat命令合并在一起。

    nutrients=[]
    
    for rec in data:
        nutrient=pd.DataFrame(rec["nutrients"])
        nutrient["id"]=rec["id"]
        nutrient["food"]=rec["description"]
        nutrient["food_group"]=rec["group"]
        nutrients.append(nutrient)
        
    nutri_data=pd.concat(nutrients, ignore_index=True)

    nutri_data的前10行显示如下:

                       description        group units    value    id  
    0                      Protein  Composition     g    25.18  1008   
    1            Total lipid (fat)  Composition     g    29.20  1008   
    2  Carbohydrate, by difference  Composition     g     3.06  1008   
    3                          Ash        Other     g     3.28  1008   
    4                       Energy       Energy  kcal   376.00  1008   
    5                        Water  Composition     g    39.28  1008   
    6                       Energy       Energy    kJ  1573.00  1008   
    7         Fiber, total dietary  Composition     g     0.00  1008   
    8                  Calcium, Ca     Elements    mg   673.00  1008   
    9                     Iron, Fe     Elements    mg     0.64  1008   
    
                  food              food_group  
    0  Cheese, caraway  Dairy and Egg Products  
    1  Cheese, caraway  Dairy and Egg Products  
    2  Cheese, caraway  Dairy and Egg Products  
    3  Cheese, caraway  Dairy and Egg Products  
    4  Cheese, caraway  Dairy and Egg Products  
    5  Cheese, caraway  Dairy and Egg Products  
    6  Cheese, caraway  Dairy and Egg Products  
    7  Cheese, caraway  Dairy and Egg Products  
    8  Cheese, caraway  Dairy and Egg Products  
    9  Cheese, caraway  Dairy and Egg Products 

    这份数据文件每一列分别是:营养成分的名称,营养成分的类别,营养成分的计量单位,营养成分的含量,营养成分所对应的食物id,食物名称,食物类别。

    接下来,我们先去除数据中的重复值和NA值,然后就可以开始进行分析了。

    nutri_data=nutri_data.drop_duplicates()
    nutri_data=nutri_data[nutri_data.notnull()]

    比如,我们想要知道每个食物类别中各营养成分的中位数是多少,并从大到小进行排序。我们首先制作一个透视表,以食物类别为行,以营养成分为列,聚合函数为计算中位数:

    nutrients_median=pd.pivot_table(nutri_data, values="value", index="food_group", columns="description", aggfunc="median")

    这里选取锌元素(Zinc)在各食物类别中的含量中位数进行排序:

    zinc_by_foodgroup=nutrients_median["Zinc, Zn"].sort_values(ascending=False)
    food_group
    Beef Products                        5.390
    Lamb, Veal, and Game Products        3.940
    Nut and Seed Products                3.290
    Breakfast Cereals                    2.885
    Spices and Herbs                     2.750
    Poultry Products                     2.500
    Pork Products                        2.320
    Sausages and Luncheon Meats          2.130
    Snacks                               1.470
    Dairy and Egg Products               1.390
    Fast Foods                           1.250
    Legumes and Legume Products          1.140
    Cereal Grains and Pasta              1.090
    Ethnic Foods                         1.045
    Restaurant Foods                     0.800
    Finfish and Shellfish Products       0.670
    Baked Products                       0.660
    Meals, Entrees, and Sidedishes       0.630
    Baby Foods                           0.590
    Sweets                               0.360
    Vegetables and Vegetable Products    0.330
    Soups, Sauces, and Gravies           0.200
    Fruits and Fruit Juices              0.100
    Beverages                            0.040
    Fats and Oils                        0.020
    Name: Zinc, Zn, dtype: float64

    将其画成柱形图:

    ax.barh(range(25),zinc_by_foodgroup.values[::-1])
    ax.set_yticks(range(25))
    ax.set_xticks([i for i in range(7)])
    ax.set_yticklabels(zinc_by_foodgroup.index.values[::-1])
    
    plt.show()

    牛肉制品的锌含量中位数是最高的。

    如果我们想知道各营养成分在哪种食物中含量最高呢?首先,我们以营养成分的类别和营养成分为行进行分组,并以食物为列,制作一个透视表。将此透视表转置,我们就可以轻松选取各营养成分的类别数据,在选中的营养成分的类别上使用idxmax()命令,就可以找出数值最大所对应的食物是哪个了。(注:idxmax()用于DataFrame,argmax()用于Series)

    table=pd.pivot_table(nutri_data, values="value", index=["group","description"], columns="food")
    max_amino_acids=table.T["Amino Acids"].idxmax()

    这里选取Amino Acids这一类别,可以看到第一行营养成分Alanine(丙氨酸)在Gelatins, dry powder, unsweetened食物内含量最高。

    description
    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
    Glycine                           Gelatins, dry powder, unsweetened
    Histidine                Whale, beluga, meat, dried (Alaska Native)
    Hydroxyproline    KENTUCKY FRIED CHICKEN, Fried Chicken, ORIGINA...
    Isoleucine        Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Leucine           Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Lysine            Seal, bearded (Oogruk), meat, dried (Alaska Na...
    Methionine                    Fish, cod, Atlantic, dried and salted
    Phenylalanine     Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Proline                           Gelatins, dry powder, unsweetened
    Serine            Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Threonine         Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Tryptophan         Sea lion, Steller, meat with fat (Alaska Native)
    Tyrosine          Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    Valine            Soy protein isolate, PROTEIN TECHNOLOGIES INTE...
    dtype: object
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  • 原文地址:https://www.cnblogs.com/HuZihu/p/10163341.html
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