4.pandas基础使用
pandas 是基于 Numpy 构建的含有更高级数据结构和工具的数据分析包
类似于 Numpy 的核心是 ndarray，pandas 也是围绕着 Series 和 DataFrame 两个核心数据结构展开的 。Series 和 DataFrame 分别对应于一维的序列和二维的表结构。
安装
conda install -n tensorflow pandasdemo实例
import sys
from pandas import Series,DataFrame
import pandas as pd
print(sys.version)
'''
3.5.3 |Continuum Analytics, Inc.| (default, May 15 2017, 10:43:23) [MSC v.1900 64 bit (AMD64)]
'''
print('Series部分')
s = Series([1,2,3.0,'abc'])
print(s)
'''
0 1
1 2
2 3
3 abc
dtype: object
'''
s = Series(data=[1, 3, 5, 7], index=['a', 'b', 'x', 'y'])
print(s)
'''
a 1
b 3
x 5
y 7
dtype: int64
'''
print(s.index)
print(s.values)
'''
Index(['a', 'b', 'x', 'y'], dtype='object')
[1 3 5 7]
'''
print('DataFrame部分')
data = {'state':['Ohino','Ohino','Ohino','Nevada','Nevada'],
'year':[2000,2001,2002,2001,2002],
'pop':[1.5,1.7,3.6,2.4,2.9]}
df = DataFrame(data)
print(df)
'''
pop state year
0 1.5 Ohino 2000
1 1.7 Ohino 2001
2 3.6 Ohino 2002
3 2.4 Nevada 2001
4 2.9 Nevada 2002
'''
df = DataFrame(data,index=['one','two','three','four','five'],
columns=['year','state','pop','debt'])
print(df)
print(df.index)
print(df.columns)
print(type(df['debt']))
'''
year state pop debt
one 2000 Ohino 1.5 NaN
two 2001 Ohino 1.7 NaN
three 2002 Ohino 3.6 NaN
four 2001 Nevada 2.4 NaN
five 2002 Nevada 2.9 NaN
Index(['one', 'two', 'three', 'four', 'five'], dtype='object')
Index(['year', 'state', 'pop', 'debt'], dtype='object')
'pandas.core.series.Series'>
'''