Series的创建
##数据分析汇总学习
https://blog.csdn.net/weixin_39778570/article/details/81157884
# 使用列表创建
1 >>> import numpy as np 2 >>> import pandas as pd 3 >>> s1 = pd.Series([1,2,3,4]) 4 >>> s1 5 0 1 6 1 2 7 2 3 8 3 4 9 dtype: int64
1 # 查看s1的值和索引 2 >>> s1.values 3 array([1, 2, 3, 4], dtype=int64) 4 >>> s1.index 5 RangeIndex(start=0, stop=4, step=1) # 默认索引
# 使用数组创建
1 >>> s2 = pd.Series(np.arange(10)) 2 >>> s2 3 0 0 4 1 1 5 2 2 6 3 3 7 4 4 8 5 5 9 6 6 10 7 7 11 8 8 12 9 9 13 dtype: int32
# 使用字典创建
1 >>> s3 = pd.Series({'1':1, '2':2, '3':3}) 2 >>> s3 3 1 1 4 2 2 5 3 3 6 dtype: int64 7 >>> s3.values 8 array([1, 2, 3], dtype=int64) 9 >>> s3.index 10 Index(['1', '2', '3'], dtype='object')
Series的访问
1 >>> s4 = pd.Series([1,2,3,4], index = ['a','b','c','d']) 2 >>> s4 3 a 1 4 b 2 5 c 3 6 d 4 7 dtype: int64 8 >>> s4.values 9 array([1, 2, 3, 4], dtype=int64) 10 >>> s4.index 11 Index(['a', 'b', 'c', 'd'], dtype='object') 12 >>> s4['a'] # 访问索引为a的值 13 1 14 >>> s4[s4>2] #访问s4中值大于2的Series 15 c 3 16 d 4 17 dtype: int64
# Series与字典的转换
1 >>> s4.to_dict() # s4转换为字典 2 {'a': 1, 'b': 2, 'c': 3, 'd': 4} 3 4 5 >>> s5 = pd.Series(s4.to_dict()) # 字典转换为Series 6 >>> s5 7 a 1 8 b 2 9 c 3 10 d 4 11 dtype: int64
# e索引无值补充为NaN
1 >>> index_1 = ['a','b','c','d','e'] 2 >>> s6 = pd.Series(s5, index = index_1) 3 >>> s6 4 a 1.0 5 b 2.0 6 c 3.0 7 d 4.0 8 e NaN # s5此处无值 9 dtype: float64
# NaN判断
1 >>> pd.isnull(s6) 2 a False 3 b False 4 c False 5 d False 6 e True 7 dtype: bool 8 >>> pd.notnull(s6) 9 a True 10 b True 11 c True 12 d True 13 e False 14 dtype: bool
# 命名修改
1 >>> s6.name = 'demo' # s6的名字修改 2 >>> s6 3 a 1.0 4 b 2.0 5 c 3.0 6 d 4.0 7 e NaN 8 Name: demo, dtype: float64 9 10 >>> s6.index.name = 'demo_index' # s6的索引的名字的修改 11 >>> s6.index 12 Index(['a', 'b', 'c', 'd', 'e'], dtype='object', name='demo_index')
官网：http://pandas.pydata.org/pandas-docs/version/0.14.1/
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