苹果股票数据分析（object数据的转换，行索引的转换）_苹果股票数据csv

导入数据分析三剑客
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

apple=pd.read_csv("C://Users/Administrator/Desktop/apple.csv")

#a=apple.dtypes
'''
Date          object
Open         float64
High         float64
Low          float64
Close        float64
Adj Close    float64
Volume         int64
dtype: object'''

#a=apple.head()
'''
         Date      Open      High       Low     Close  Adj Close     Volume
0  1999-03-01  1.243304  1.243304  1.200893  1.205357   1.051931  121956800
1  1999-03-02  1.218750  1.261161  1.205357  1.236607   1.079204  170763600
2  1999-03-03  1.241071  1.254464  1.196429  1.220982   1.065567   73337600
3  1999-03-04  1.232143  1.232143  1.156250  1.194196   1.042192   91817600
4  1999-03-05  1.225446  1.225446  1.156250  1.185268   1.034399  117009200
'''

apple['Date']=pd.to_datetime(apple['Date'])#pd.to_datetime()将object类型数据转换为时间类型数据，int。有利于排序

#a=apple.dtypes
'''
Date         datetime64[ns]
Open                float64
High                float64
Low                 float64
Close               float64
Adj Close           float64
Volume                int64
dtype: object
'''

#将Date设置为行索引
apple.set_index('Date',inplace=True)

#a=apple.head()
'''
                Open      High       Low     Close  Adj Close     Volume
Date                                                                    
1999-03-01  1.243304  1.243304  1.200893  1.205357   1.051931  121956800
1999-03-02  1.218750  1.261161  1.205357  1.236607   1.079204  170763600
1999-03-03  1.241071  1.254464  1.196429  1.220982   1.065567   73337600
1999-03-04  1.232143  1.232143  1.156250  1.194196   1.042192   91817600
1999-03-05  1.225446  1.225446  1.156250  1.185268   1.034399  117009200
'''

plt.plot(apple['Adj Close'])
plt.show()

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结果展示