Pandas 0 数据结构Series

# -*- encoding:utf-8 -*-
# Copyright (c) 2015 Shiye Inc.
# All rights reserved.
#
# Author: ldq <liangduanqi@shiyejinrong.com>
# Date: 2019/2/12 9:26

import numpy as np
import pandas as pd

s = pd.Series()
'''
创建一个空序列
Series([], dtype: float64)
'''

data1 = np.array(["a", "b", "c", "d"])
s1 = pd.Series(data1)
'''
0    a
1    b
2    c
3    d
dtype: object
'''

s10 = pd.Series(data1, index=range(100, 104))
'''
index参数为一个可迭代集合
100    a
101    b
102    c
103    d
dtype: object
'''
data11 = {"a": 0., "b": 1., "c": 2.}
s11 = pd.Series(data11)
'''
字典的key用于构建索引
a    0.0
b    1.0
c    2.0
dtype: float64
'''
s12 = pd.Series(data11, index=["b", "c", "d", "a"])
'''
b    1.0
c    2.0
d    NaN
a    0.0
dtype: float64
'''

s2 = pd.Series(5, index=[0,1,2,3])
'''
0    5
1    5
2    5
2    5
dtype: int64
'''
a = s2[1]
b = s2[1:]
'''
类似python的list可被切片
1    5
2    5
3    5
dtype: int64
'''
c = s2[[0,1,2]]
'''
使用索引标签值列表检索多个元素
0    5
1    5
2    5
dtype: int64
'''