Pandas基本操作
Pandas基本操作
1.Series
(1)Series的创建
pd.Series(data,index=列表)
import pandas as pd
se = pd.Series(["张三", "李四", "王五"], index=["stu1", "stu2", "stu3"])
print(se)
![](https://blog.hanstary.com/file/57.png)
也可以用字典创建
import pandas as pd
dic = {
"sud1": "张三",
"stu2": "李四",
"stu3": "王五"
}
se = pd.Series(dic)
print(se)
![](https://blog.hanstary.com/file/58.png)
字典的key就会变成行名,字典的value就会变成数据
(2)Series的属性
属性 | 说明 |
---|---|
index | 行名 |
values | 数据 |
import pandas as pd
dic = {
"sud1": "张三",
"stu2": "李四",
"stu3": "王五"
}
se = pd.Series(dic)
print("行名")
print(se.index)
print("数值")
print(se.values)
![](https://blog.hanstary.com/file/60.png)
(3)取值
se.loc[行名]
import pandas as pd
dic = {
"sud1": "张三",
"stu2": "李四",
"stu3": "王五"
}
se = pd.Series(dic)
print(se.loc["sud1"])
![](https://blog.hanstary.com/file/59.png)
2.DataFrame
(1)DataFrame的创建
pd.DataFrame(data,index=列表,columns=列表)
import pandas as pd
data = [
["张三", "男", "18"],
["李四", "男", "19"],
["王五", "男", "20"]
]
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"], columns=["姓名", "性别", "年龄"])
print(df)
![](https://blog.hanstary.com/file/61.png)
字典创建
import pandas as pd
data = [
{"姓名": "张三", "性别": "男", "年龄": 18},
{"姓名": "李四", "性别": "男", "年龄": 19},
{"姓名": "王五", "性别": "男", "年龄": 20}
]
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
print(df)
或者
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
print(df)
![](https://blog.hanstary.com/file/62.png)
(2)DataFrame的属性
属性 | 说明 |
---|---|
dtypes | DataFrame的类型 |
values | DataFrame的数据 |
index | 行名 |
columns | 列名 |
shape | 形状 |
size | 元素个数 |
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
print("dtypes")
print(df.dtypes)
print("values")
print(df.values)
print("index")
print(df.index)
print("columns")
print(df.columns)
print("shape")
print(df.shape)
print("size")
print(df.size)
![](https://blog.hanstary.com/file/63.png)
(3)对齐输出
pd.set_option("display.unicode.east_asian_width",True)
(4)数据操作
A.查
df.loc[行名,列名]
df.iloc[行下标,列下标]
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
# 获得单个数据
print(df.loc["stu2", "姓名"])
# 获得行数据
print(df.loc["stu1", :])
# 获得列数据
print(df.loc[:, "年龄"])
# 获得多个数据
print(df.loc[["stu1", "stu2"], :])
print(df.loc[:, ["姓名", "年龄"]])
![](https://blog.hanstary.com/file/64.png)
B.改
df.loc[行名,列名]=新值
df.iloc[行下标,列下标]=新值
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
df.loc["stu1", "年龄"] = 25
print(df)
![](https://blog.hanstary.com/file/65.png)
C.增
# 添加行数据
df.loc[行名]=值
df.iloc[行下标]=值
#添加列数据
df.loc[:,列名]=值
df.iloc[:,列下标]=值
df[列名]=值
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
# 显示的对齐
pd.set_option("display.unicode.east_asian_width",True)
# 插入行
df.loc["stu4"] = ["赵六", "男", 21]
# 插入列
df.loc[:, "爱好"] = ["唱", "跳", "rap", "篮球"]
print(df)
![](https://blog.hanstary.com/file/66.png)
D.删
# 删除行数据
df.drop(行名或列名,axis=0)
# 删除列数据
df.drop(行名或列名,axis=1)
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
# 显示的对齐
pd.set_option("display.unicode.east_asian_width", True)
# 删除行
df = df.drop("stu1", axis=0)
# 删除列
df = df.drop("性别", axis=1)
print(df)
![](https://blog.hanstary.com/file/67.png)
(5)遍历行列
# 遍历行
for key,value in df.iterrows():
...
# 遍历列
for key,value in df.items():
...
import pandas as pd
data = {
"姓名": ["张三", "李四", "王五"],
"性别": ["男", "男", "男"],
"年龄": [18, 19, 20]
}
df = pd.DataFrame(data, index=["stu1", "stu2", "stu3"])
# 显示的对齐
pd.set_option("display.unicode.east_asian_width", True)
# 遍历行
for key, value in df.iterrows():
print(key)
print(value)
# 遍历列
print("====================================")
for key, value in df.items():
print(key)
print(value)
![](https://blog.hanstary.com/file/68.png)
![](https://blog.hanstary.com/file/69.png)