Pandas库，如何利用loc或iloc从DataFrame获取或设置数据？

import pandas as pd
df = pd.DataFrame([
    ('虎子', 5, "dog"),
    ('老许', 3, "bird"), ],
)
df2 = pd.DataFrame([
    ('虎子', 5, "dog"),
    ('老许', 3, "bird"),
    ('二赖子', 6, "fish"), ],
    columns=("name", "age", "class")
)
df3 = pd.DataFrame([
    ('虎子', 5, "dog"),
    ('老许', 3, "bird"),
    ('二赖子', 6, "fish"), ],
    index=["a1", "a2", "a3"],
    columns=("name", "age", "class")
)

# <class 'str'>
print(df.loc[0, 0])           # 虎子
# print(df2.loc[0,1])         # KeyError: 1
# print(df3.loc[0,1])         # KeyError: 1
print(df2.loc[0, "name"])     # 虎子
# print(df3.loc[0,"name"])    # KeyError: 0
print(df3.loc["a1", "name"])  # 虎子

# <class 'pandas.core.series.Series'>
a2 = df2.loc[:, "name"]
a3 = df2.loc[:2, "name"]
# a4 = df3.loc[1:2, "name"] # TypeError: cannot do slice indexing on Index with these indexers 
a4 = df3.loc["a1":"a3", "name"]
a5 = df3.loc["a1":"a3", "name":"class"]

# print(df2.iloc[0,"name"])  # ValueError: Can only index by location with a [integer, integer
print(df.iloc[0, 0])   # 虎子
print(df2.iloc[0, 1])  # 5
print(df3.iloc[0, 1])  # 5

# print(df2.iloc[1,"name"]) #虎子
print(df.iloc[:,1]) 
print(df2.iloc[2:,1]) 
print(df3.iloc[:2,1]) 
print(df3.iloc[:2,0:2])

# print(df.loc[1,2].values)     # AttributeError: 'str' object has no attribute 'values'
print(df.loc[:,2].values)       # ['dog' 'bird']
# print(df2.loc[0:2,2].values)  # KeyError: 2
print(df2.iloc[0:2,2].values)   # ['dog' 'bird']         <class 'numpy.ndarray'>
print(df2.iloc[0:2,0:2].values) # [['虎子' 5]['老许' 3]]  <class 'numpy.ndarray'>

df2.loc[df2.loc[:, 'name'] == "虎子", "ok"] = 1 

import pandas as pd
df = pd.DataFrame(
    [
        ["虎子", "狗", 15],
        ["老许", "猫", 10],
     ],
    columns=["姓名", "种类", "重量"],
)

# 修改行
df.iloc[1] = ["小许", "猫", 3]
df.iloc[0, :] = ["二赖子", "狗", 16]
print(df)

# 修改列
df.iloc[:, 1] = ["dog", "cat"]
print(df)

    姓名  种类  重量
0  二赖子  狗   16
1   小许   猫   3

    姓名   种类  重量
0  二赖子  dog   16
1   小许   cat   3

SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

df["nan"][4] = None

df.loc[4, "nan"] = None