1.创建 DataFrame 类型df 2.输出df的前三行 I 3.输出'age与animal两列数据 VMwa Workst 4.对df按列 animal进行排序，并打印df 5.将行为”f”，列为“age”的元素值修改为 6.输出所有visits属性值大于2的所有行 7.将此df的数据保存至excel文件中 上海市高 8.将animal 列中所有snake替换为panda 交信息打9.输出animal==cat且age<3的所有行， 10.在df的在后一列后添加一列列名为No.数据 0,1,2345679，并输出df

1.创建 DataFrame 类型df

import numpy as np
import pandas as pd
data = {'animal':['cat','cat','snake','dog','dog','cat','snake','cat','dog','dog'], 
        'age': [2.5, 3, 0.5, np.nan, 5, 2, 4.5, np.nan, 7, 3], 
        'visits':[1,3,2,3,2,3,1,1,2,1],
        'priority':['yes',np.nan,'no','yes','no','no','no','yes','no','no']}
labels = ['a','b','c','d','e','f','g','h','i','j']
df = pd.DataFrame(data=data, index=labels)
print(df)

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
b    cat  3.0       3     NaN
c  snake  0.5       2       no
d    dog  NaN       3      yes
e    dog  5.0       2       no
f    cat  2.0       3       no
g  snake  4.5       1       no
h    cat  NaN       1      yes
i    dog  7.0       2       no
j    dog  3.0       1       no

2.输出df的前三行

print(df.head(3))

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
b    cat  3.0       3     NaN
c  snake  0.5       2       no

3.输出'age与animal两列数据

print(df[['age', 'animal']])

输出：

   age animal
a  2.5    cat
b  3.0    cat
c  0.5  snake
d  NaN    dog
e  5.0    dog
f  2.0    cat
g  4.5  snake
h  NaN    cat
i  7.0    dog
j  3.0    dog

4.对df按列 animal进行排序，并打印df

print(df.sort_values(by='animal'))

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
b    cat  3.0       3     NaN
f    cat  2.0       3       no
h    cat  NaN       1      yes
c  snake  0.5       2       no
g  snake  4.5       1       no
d    dog  NaN       3      yes
e    dog  5.0       2       no
i    dog  7.0       2       no
j    dog  3.0       1       no

5.将行为”f”，列为“age”的元素值修改为2.5

df.loc['f', 'age'] = 2.5
print(df)

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
b    cat  3.0       3     NaN
c  snake  0.5       2       no
d    dog  NaN       3      yes
e    dog  5.0       2       no
f    cat  2.5       3       no
g  snake  4.5       1       no
h    cat  NaN       1      yes
i    dog  7.0       2       no
j    dog  3.0       1       no

6.输出所有visits属性值大于2的所有行

print(df[df['visits'] > 2])

输出：

  animal  age  visits priority
b    cat  3.0       3     NaN
d    dog  NaN       3      yes
f    cat  2.5       3       no

7.将此df的数据保存至excel文件中

df.to_excel('test.xlsx', index=False)

8.将animal 列中所有snake替换为panda

df['animal'] = df['animal'].replace('snake', 'panda')
print(df)

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
b    cat  3.0       3     NaN
c  panda  0.5       2       no
d    dog  NaN       3      yes
e    dog  5.0       2       no
f    cat  2.5       3       no
g  panda  4.5       1       no
h    cat  NaN       1      yes
i    dog  7.0       2       no
j    dog  3.0       1       no

9.输出animal==cat且age<3的所有行

print(df[(df['animal'] == 'cat') & (df['age'] < 3)])

输出：

  animal  age  visits priority
a    cat  2.5       1      yes
f    cat  2.5       3       no

10.在df的在后一列后添加一列列名为No.数据 0,1,2,3,4,5,6,7,8,9，并输出df

df['No.'] = np.arange(10)
print(df)

输出：

  animal  age  visits priority  No.
a    cat  2.5       1      yes    0
b    cat  3.0       3     NaN    1
c  panda  0.5       2       no    2
d    dog  NaN       3      yes    3
e    dog  5.0       2       no    4
f    cat  2.5       3       no    5
g  panda  4.5       1       no    6
h    cat  NaN       1      yes    7
i    dog  7.0       2       no    8
j    dog  3.0       1       no    9