Welcome to pandas!

1.4 Numpy数组转换

实现中需要将dataFrame表格和Series数据转为数组，dataFrame数据表格，再分别使用np.array()函数，df.to_numpy()函数，df.value属性。

1.4.1导入数据（数据形式）

import pandas as pd,numpy as np

path=r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

print (df)

返回：

1.4.2导入数据（数组形式）

import pandas as pd,numpy as np

path= r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

print (np.array(df))

返回：

[['张三' Timestamp('2023-11-01 00:00:00') 1000]

['李四' Timestamp('2020-01-01 00:00:00') 2050]

['王五' Timestamp('2021-07-07 00:00:00') 3041]]

import pandas as pd,numpy as np

path= r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

print (df.to_numpy()) #等同上面转成数组

返回：

[['张三' Timestamp('2023-11-01 00:00:00') 1000]

['李四' Timestamp('2020-01-01 00:00:00') 2050]

['王五' Timestamp('2021-07-07 00:00:00') 3041]]

import pandas as pd,numpy as np

path=r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

print (df.values) #等同上面转成数组

返回：

[['张三' Timestamp('2023-11-01 00:00:00') 1000]

['李四' Timestamp('2020-01-01 00:00:00') 2050]

['王五' Timestamp('2021-07-07 00:00:00') 3041]]

1.4.3导入数据（series形式）

import pandas as pd,numpy as np

path= r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

for i,s in df.items(): #写入标题，即第一行数据

print (i)

返回：

姓名

入职日期

基础工资

import pandas as pd,numpy as np

path=r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

for i,s in df.items(): #分列写入数据

print (s)

返回：

0 张三

1 李四

2 王五

Name: 姓名, dtype: object

0 2023-11-01

1 2020-01-01

2 2021-07-07

Name: 入职日期, dtype: datetime64[ns]

0 1000

1 2050

2 3041

Name: 基础工资, dtype: int64

import pandas as pd,numpy as np

path=r "D:\Pyobject2023\object\测试\素材\1.1.4 Numpy数组转换.xlsx"

df=pd.read_excel (path)

for i,s in df.items()

print (np.array(s)) #分列写入数组

返回：

['张三' '李四' '王五']

['2023-11-01T00:00:00.000000000' '2020-01-01T00:00:00.000000000' '2021-07-07T00:00:00.000000000']

[1000 2050 3041]