今日练习:(即注意事项)
第一:求1-100之间和
res=0
num=1
while num <= 100:
res+=num # res=res+num 0+1=1 1+2=3 3+3=6 ...
num+=1 # num=num+1
print(res) #
注意点:python的缩进严重影响你输出的结果,如果print(res)没有和while对齐,其实是每循环一次会求和一次,结果如下
![](data:image/png;base64,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)
正确的书写方式为:
res=0
num=1
while num <= 100:
res+=num # 每次如何运算的 res=res+num 0+1=1 1+2=3 3+3=6 ...
num+=1 # num=num+1
print(res)
![](data:image/png;base64,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)
第二:输出乘法口诀
for henghang in range(1,10): # 1 2 3 4 思路:henghang和shuhang对应的值
for shuhang in range(1,i+1): # 1 12 123 1234
print('%s*%s=%s'%(henghang,shuhang,henghang*shuhang),end=" ")
print( )
注意点1:python的缩进严重影响你输出的结果,如果print()没有和第二个for对齐,结果显示格式其实是不一样的:
![](data:image/png;base64,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)
正确的写法:
for i in range(1,10): # 1 2 3 4
for j in range(1,i+1): # 1 12 123 1234
print('%s*%s=%s'%(i,j,i*j),end=" ")
print( )
第三:用for循环取出下面list列表、字典dict的值
names=["zhangsan","lisi","wangwu","zhaoliu"]
user_info={"name":"zhangsan","age":21,"sex":"male","address":"sh"}
for x in names:
print(x) #取出所有names里面所有人的名字
for y in user_info: #y="age"
print(y) #取出所有user_info里面的key值
for y in user_info: #y="age"
print(y,user_info[y]) #取出所有user_info里面的key和value值
最后1个的输出结果如下:
![](data:image/png;base64,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)