python数据分析练习——FoodFacts.csv分析

python数据分析练习——FoodFacts.csv分析

导包

import numpy as np
import pandas as pd
import datetime
import matplotlib.pyplot as plt
import seaborn as sns

# 正常显示中文标签
plt.rcParams['font.sans-serif'] = ['SimHei']
# 自动适应布局
plt.rcParams.update({'figure.autolayout': True})
# 正常显示负号
plt.rcParams['axes.unicode_minus'] = False

获取数据：导入待分析数据：dataset\FoodFacts.csv，并显示显示前10行。

data = pd.read_csv('dataset\FoodFacts.csv')
data.head(10)

	code	url	creator	created_t	created_datetime	last_modified_t	last_modified_datetime	product_name	generic_name	quantity	...	caffeine_100g	taurine_100g	ph_100g	fruits_vegetables_nuts_100g	collagen_meat_protein_ratio_100g	cocoa_100g	chlorophyl_100g	carbon_footprint_100g	nutrition_score_fr_100g	nutrition_score_uk_100g
0	000000000000012866	http://world-en.openfoodfacts.org/product/0000...	date-limite-app	1447004364	2015-11-08T17:39:24Z	1447004364	2015-11-08T17:39:24Z	Poêlée à la sarladaise	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	0000000024600	http://world-en.openfoodfacts.org/product/0000...	date-limite-app	1434530704	2015-06-17T08:45:04Z	1434535914	2015-06-17T10:11:54Z	Filet de bœuf	NaN	2.46 kg	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	0000000036252	http://world-en.openfoodfacts.org/product/0000...	tacinte	1422221701	2015-01-25T21:35:01Z	1422221855	2015-01-25T21:37:35Z	Lion Peanut x2	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	0000000039259	http://world-en.openfoodfacts.org/product/0000...	tacinte	1422221773	2015-01-25T21:36:13Z	1422221926	2015-01-25T21:38:46Z	Twix x2	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	0000000039529	http://world-en.openfoodfacts.org/product/0000...	teolemon	1420147051	2015-01-01T21:17:31Z	1439141740	2015-08-09T17:35:40Z	Pack de 2 Twix	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5	0000001071894	http://world-en.openfoodfacts.org/product/0000...	bcatelin	1409411252	2014-08-30T15:07:32Z	1439141739	2015-08-09T17:35:39Z	Flute	Flute	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
6	0000005200016	http://world-en.openfoodfacts.org/product/0000...	sigoise	1441186657	2015-09-02T09:37:37Z	1442570752	2015-09-18T10:05:52Z	lentilles vertes	NaN	1 kg	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
7	0000007020254	http://world-en.openfoodfacts.org/product/0000...	teolemon	1420150193	2015-01-01T22:09:53Z	1420210373	2015-01-02T14:52:53Z	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8	0000010090206	http://world-en.openfoodfacts.org/product/0000...	sebleouf	1370977431	2013-06-11T19:03:51Z	1445083431	2015-10-17T12:03:51Z	Thé de Noël aromatisé orange-cannelle	NaN	75 g	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
9	0000020364373	http://world-en.openfoodfacts.org/product/0000...	openfoodfacts-contributors	1393970573	2014-03-04T22:02:53Z	1393970733	2014-03-04T22:05:33Z	Zumo de Piña	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

10 rows × 159 columns

查看文件大小，会发现文件列数过多，而我们只需要对’countries_en’和 'additives_n’这两列进行分析，因此，请处理数据只剩下这两列即可；然后判断有无缺失值，若有，直接删除缺失值。

data2 = data[['countries_en', 'additives_n']]
data2

	countries_en	additives_n
0	France	NaN
1	France	NaN
2	France	NaN
3	France	NaN
4	France	NaN
...	...	...
65498	Poland	NaN
65499	France	0.0
65500	France	NaN
65501	France	0.0
65502	China	NaN

65503 rows × 2 columns

data2.dropna(axis=0, how='any', inplace=True)
data2

	countries_en	additives_n
5	United Kingdom	0.0
6	France	0.0
8	France	0.0
10	United Kingdom	5.0
11	United Kingdom	5.0
...	...	...
65480	United States	4.0
65490	France	0.0
65494	France	0.0
65499	France	0.0
65501	France	0.0

43616 rows × 2 columns

将所有国家名称转换为小写

data2['countries_en'] = data2['countries_en'].str.lower()
data2

	countries_en	additives_n
5	united kingdom	0.0
6	france	0.0
8	france	0.0
10	united kingdom	5.0
11	united kingdom	5.0
...	...	...
65480	united states	4.0
65490	france	0.0
65494	france	0.0
65499	france	0.0
65501	france	0.0

43616 rows × 2 columns

按国家对additives_n列进行分组，并统计使用添加剂的平均数量，并对统计结果(均值)从大到小排序.

group = data2['additives_n'].groupby(data2['countries_en']).mean().sort_values(ascending=False)
group.head(10).index

Index(['australia,indonesia,united states', 'france,saudi arabia',
       'denmark,france,portugal', 'france,greece,netherlands', 'togo', 'qatar',
       'denmark,france,switzerland', 'france,luxembourg',
       'egypt,united kingdom,united states', 'australia,new zealand'],
      dtype='object', name='countries_en')

对排名前10的数据进行简单的可视化展示(例如，使用matplotlib中的柱状图、折线图或者饼图等任意一种绘图方式进行)

plt.figure(figsize=(10, 6))
plt.pie(group.head(10),labels=group.head(10).index, colors=sns.color_palette('hls',10),
       shadow=True,startangle=90,autopct='%.2f%%')
plt.axis('equal')
plt.legend(loc='upper right')

本文地址：https://blog.csdn.net/qq_41754907/article/details/107164607