学习python的第三天

一、三国人物Top10

import jieba
from wordCloud import WordCloud
import imageio
with open('./threekingdom.txt','r',encoding='utf-8') as f:
    words = f.read()
    counts={}
    #不是人名的集合
    excludes = {"将军", "却说", "丞相", "二人", "不可", "荆州", "不能", "如此", "商议",
                "如何", "主公", "军士", "军马", "左右", "次日", "引兵", "大喜", "天下",
                "东吴", "于是", "今日", "不敢", "魏兵", "陛下", "都督", "人马", "不知",
                "孔明曰", "玄德曰", "刘备", "云长"}
    #top10
    li=[]
    # print(len(words)) jieba分词
    words_list = jieba.lcut(words)
    print(words_list)
    for word in words_list:
        if len(word) <=1:
            continue
        else:
            counts[word]=counts.get(word,0)+1
    print(counts)
    counts['孔明']=counts['孔明']+counts['孔明曰']
    counts['玄德']=counts['玄德']+counts['玄德曰']+counts['刘备']
    counts['关公'] = counts['云长'] + counts['关公']
    #删除
    for word in excludes:
        del counts[word]

    #排序
    items=list(counts.items())
    print(items)

    items.sort(key=lambda x:x[1],reverse=True)
    print(items)

    for i in range(10):
        #序列解包
        role,count=items[i]
        print(role,count)
        #_表示循环里不需要使用临时变量
        for _ in range(count):
            li.append(role)
    mask = imageio.imread('./china.jpg')
    text=' '.join(li)
    WordCloud(
        font_path='msyh.ttc',
        background_color='white',
        width=800,
        height=600,
        #相邻两个重复词之间的匹配
        collocations=False,
        mask=mask
    ).generate(text).to_file('Top10.png')

二、匿名函数

1、lambda表达式

1.1、形式：lambda x1,x2,....xn:表达式。参数无数多个，表达式只有一个

from random import randint
num=lambda x1,x2:x1+x2
print(num(3,3))

#列表和字典通过lambda表达式排序
list=[
    ('a',32),
    ('b',32),
    ('c',56),
    ('d',34),
]
list.sort(key=lambda x:x[1],reverse=True)
print(list)

info=[
    {"name":"xiaoxin","age":18},
    {"name":"xiao","age":19},
    {"name":"xin","age":10},
    {"name":"aoin","age":17},
]
info.sort(key=lambda x:x["age"])
print(info)

1.2、列表推导式

#[表达式(返回值) for 临时变量 in 可迭代对象 可追加条件]
print([i for i in range(10)])

1.3、列表解析

#筛选出列表中所有的偶数
#普通方法
li=[]
for i in range(10):
    if i%2==0:
        li.append(i)
print(li)
#列表解析
print([ i for i in range(10) if i%2==0])
print("111")

三、画图

使图上的字不乱码
plt.rcParams["font.sans-serif"] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

1、[0,2π]正弦曲线图

x=np.linspace(0,2*np.pi,num=100)
print(x)
y=np.sin(x)
#正弦余弦在同一坐标系下
cosy=np.cos(x)
plt.plot(x,cosy)
plt.plot(x,y,color='r',linestyle='--',label='sin(x)')#设置曲线和颜色,形式
plt.xlabel("时间（s）")#x,y轴标识
plt.ylabel('电压（V）')
plt.table('xx表')
#图例
plt.legend()
plt.show()

2、柱状图

import  string
# print(string.ascii_uppercase[0:6])#切片
x=['猫{}'.format(x) for x in string.ascii_uppercase[0:5] ]
y=[randint(100,1000) for _ in range(5)]
plt.bar(x,y)
print(x)
plt.show()

3、饼状图

counts=[randint(3500,9000) for _ in range(6)]
labels=['员工{}'.format(x) for x in string.ascii_lowercase[:6]]
#距离圆心点的距离
colors = ['red', 'purple','blue', 'yellow','gray','green']
explode=[0.1,0,0,0,0,0]
plt.pie(counts,explode = explode,shadow=True, labels=labels, autopct = '%1.1f%%',colors=colors)
plt.legend(loc=2)
plt.axis('equal')
plt.show()

4、闪点图

#闪点图
#（均值，标准差，数量）
x=np.random.normal(0,1,100)
y=np.random.normal(0,1,100)
#alpha透明度
plt.scatter(x,y,alpha=0.1)
plt.show()