【数据分析与可视化】股票市场分析实战之历史趋势分析
# 基本信息
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
# 股票数据读取
import pandas_datareader as pdr
# 可视化
import matplotlib.pyplot as plt
import seaborn as sns
#%matplotlib inline
# time
from datetime import datetime
start = datetime(2015,9,20)
# 获取阿里股票数据
alibaba = pdr.get_data_yahoo('BABA', start=start)
# 获取亚马逊数据
amazon = pdr.get_components_yahoo('AMZN')
# 数据存储alibaba.to_csv('url')
# 读取本地数据
alibaba = pd.read_csv('/Users/bennyrhys/Desktop/数据分析可视化-数据集/homework/BABA.csv',index_col=0)
amazon = pd.read_csv('/Users/bennyrhys/Desktop/数据分析可视化-数据集/homework/AMZN.csv',index_col=0)
alibaba.head()
| Open | High | Low | Close | Adj Close | Volume | |
|---|---|---|---|---|---|---|
| Date | ||||||
| 2015-09-21 | 65.379997 | 66.400002 | 62.959999 | 63.900002 | 63.900002 | 22355100 |
| 2015-09-22 | 62.939999 | 63.270000 | 61.580002 | 61.900002 | 61.900002 | 14897900 |
| 2015-09-23 | 61.959999 | 62.299999 | 59.680000 | 60.000000 | 60.000000 | 22684600 |
| 2015-09-24 | 59.419998 | 60.340000 | 58.209999 | 59.919998 | 59.919998 | 20645700 |
| 2015-09-25 | 60.630001 | 60.840000 | 58.919998 | 59.240002 | 59.240002 | 17009100 |
amazon.head()
| Open | High | Low | Close | Adj Close | Volume | |
|---|---|---|---|---|---|---|
| Date | ||||||
| 2015-09-21 | 544.330017 | 549.780029 | 539.590027 | 548.390015 | 548.390015 | 3283300 |
| 2015-09-22 | 539.710022 | 543.549988 | 532.659973 | 538.400024 | 538.400024 | 3841700 |
| 2015-09-23 | 538.299988 | 541.210022 | 534.000000 | 536.070007 | 536.070007 | 2237600 |
| 2015-09-24 | 530.549988 | 534.559998 | 522.869995 | 533.750000 | 533.750000 | 3501000 |
| 2015-09-25 | 542.570007 | 542.799988 | 521.400024 | 524.250000 | 524.250000 | 4031000 |
# 闭盘走势
alibaba['Adj Close'].plot(legend=True)
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