python

Series

import pandas as pd

#创建一个字典
dc={"name":"张三","age":18,"birth":"2025-10-1"}
indexs=["name","city"]
s1=pd.Series(dc)
print("Series:",s1)
#属性
print(s1.shape)#形状
print(s1.dtype)#元素类型
ls=s1.values#返回series对象值构成的一个数组
print(ls)
print(type(ls))
s1.name="test"#为series对象取名
print(s1)
s1.index.name="index_name"#为索引取名
print(s1.size)#元素个数
print(s1.ndim)#维度
print(s1.nbytes)#大小

print(s1['name'])

ls=[1,2,3,4]
s2=pd.Series(ls)
print(s2[2:4])

创建DataFrame对象

#创建dataframe对象
#使用list对象构造dataframe对象
alist=[[1,2,3,4],[5,6,7,8]]
indexs=['one','two']
columns=['one','two','three','four']
df1=pd.DataFrame(alist,index=indexs,columns=columns)
print(df1)
#使用字典构建dataframe对象
adict={
    "name":['张三','李四','王五'],
    'age':[18,19,20],
    'city':['上海','北京','武汉']
}
df2=pd.DataFrame(adict)
print(df2)
#使用嵌套字典构建dataframe对象
adict1={
    "name":{1:'张三',2:'李四',3:'王五'},
    'age':{1:18,2:19,3:20},
    'city':{1:'上海',2:'北京',3:'武汉'}
}
df3=pd.DataFrame(adict1)
print(df3)

查找DataFrame对象

#列索引访问
print(df3['name'])
print(type(df3['name']))
#行索引+列索引：先确定series对象，再去确定属于哪个元素
print(df3['name'][1])
#切片
print(df3[0:2])#获取前两行
print(df3['name'][0:2])#先确定某一列，再去切片

DataFrame对象

#属性
print(df3.dtypes)
print(df3.values)
print(df3.index)
print(df3)
new_df3=df3.rename(columns={'name':'n','age':'a','city':'c'})#修改列索引名
print(new_df3)
print(df3)
#修改行索引名
new_df3=df3.rename(index={1:10,2:20,3:30})
print(new_df3)
print(df3)
#为索引添加名
df3.index.name="test"
print(df3)
print(df3.shape)
print(df3.size)
print(df3.ndim)