Series与DataFrame的区别
DataFrame是多个共用相同索引的Series组成
Series没有列索引，DataFrame有列索引

#coding=utf-8
import pandas as pd
import numpy as np

dicts={"name":["lemon","jack","jason"],
       "age":[20,15,30],
       "sex":["male","male","fmale"]
       }
df=pd.DataFrame(dicts)
print(df)
'''
   age   name    sex
0   20  lemon   male
1   15   jack   male
2   30  jason  fmale
'''

#DataFrame可拆分成多个Series
print(df['name'])
print(type(df['name']))
'''
0    lemon
1     jack
2    jason
Name: name, dtype: object

<class 'pandas.core.series.Series'>
'''



#多个Series可组成DataFrame
name=df['name']
age=df['age']
print(name)
print(age)
#name和age两个Series组成DataFrame
print(pd.DataFrame([name,age]))
'''
          0     1      2
name  lemon  jack  jason
age      20    15     30
这么看结果和原DataFrame不一致，可以利用 .T转换
'''
print(pd.DataFrame([name,age]).T)
'''
    name age
0  lemon  20
1   jack  15
2  jason  30
'''



#逐行读取DataFrame数据
for index,value in df.iterrows():
    print(index)
    print('---------')
    print(value)
'''
0
---------
age        20
name    lemon
sex      male
Name: 0, dtype: object
1
---------
age       15
name    jack
sex     male
Name: 1, dtype: object
2
---------
age        30
name    jason
sex     fmale
Name: 2, dtype: object
'''

#仅读取sex和age的值
for index,value in df.iterrows():
    age,name,sex=value
    print(age)
    print(sex)
'''
20
male
15
male
30
fmale
'''