一、DateFrame简介

1.导入pandas和matplotlib.pyplot

import pandas as pd
import matplotlib.pyplot as plt

2.读取facebook.csv数据，并设置第一列为索引，将索引变为时间格式11122

fb = pd.read_csv('data/facebook.csv',index_col=0)
fb.index=pd.to_datetime(fb.index)

3.取数据的前n行数据,默认是前5行

print(fb.head())

Date	Open	High	Low	Close	Adj Close	Volume
2014-12-31	20.400000	20.510000	19.990000	20.049999	19.459270	4157500
2015-01-02	20.129999	20.280001	19.809999	20.129999	19.536913	2842000
2015-01-05	20.129999	20.190001	19.700001	19.790001	19.206934	4948800
2015-01-06	19.820000	19.840000	19.170000	19.190001	18.624611	4944100
2015-01-07	19.330000	19.500000	19.080000	19.139999	18.576082	8045200

4.读取矩阵的长度

print(fb.shape)

输出：(780, 6)
含义：数据有780行，6列（Date为索引）

5.生成统计数据

print(fb.describe())

	Open	High	Low	Close	Adj Close	Volume
count	780.000000	780.000000	780.000000	780.000000	780.000000	7.800000e+02
mean	80.212705	81.285654	79.022397	80.264897	79.914215	1.204453e+07
std	64.226121	65.048907	63.190963	64.198375	64.327846	8.221848e+06
min	19.250000	19.500000	18.940001	19.139999	18.576082	1.311200e+06
25%	25.525000	26.085000	24.845000	25.475000	25.134512	7.215200e+06
50%	53.379999	54.034999	52.930000	53.420000	53.035403	9.728700e+06
75%	113.322502	115.779999	110.297499	113.702501	113.261238	1.408885e+07
max	245.770004	249.270004	244.449997	246.850006	246.850006	9.232320e+07

转到 describe

2.提取2015年数据

fb_2015 = fb.loc['2015-01-01':'2015-12-31']

Open 2.288000e+01
High 2.311000e+01
Low 2.273000e+01
Close 2.297000e+01
Adj Close 2.237908e+01
Volume 5.923900e+06
Name: 2015-03-16, dtype: float64

7.提取第一行第一列数据

print(fb.iloc[0, 0])

20.4

8.绘图

plt.figure(figsize=(10, 8))
fb['Close'].plot()
plt.margins(x=0)
plt.show()