Python之DataFrame的使用
以下是Python之DataFrame的使用:
1.定义DataFrame的方式(不带参、使用list、使用列标签)
import pandas as pd df = pd.DataFrame print(df) arr = [1,2,3,4,5] df = pd.DataFrame(arr) print(df) list = [["小明","20"],["小锋","28"]] df = pd.DataFrame(list,columns=["姓名","年龄"]) print(df)
结果如下
2.定义DataFrame的方式(使用字典+行标签、列表嵌套字典、Series)
import pandas as pd data = { "name": ["小勇","小锋"], "age": [28,29], } df = pd.DataFrame(data,index=["a","b"]) print(df) data = [{"name":"小勇","age":28,},{"name":"小民","age":30,}] df = pd.DataFrame(data) print(df) df = pd.DataFrame(pd.Series(["小意","小业"],index=["a","b"])) print(df)
结果如下
3.获取DataFrame的数据、插入(insert和直接新增字段)和删除(del和pop)字段
import pandas as pd data = { "name": ["小勇","小锋"], "age": [28,29], } df = pd.DataFrame(data,index=["a","b"]) print(df) print("--------------") print(df["age"]) print("--------------") df.insert(1,column="score",value=[80,100]) print(df) print("--------------") del df["score"] print(df) print("--------------") df["score"] = pd.Series([80],index=["b"]) print(df) print("--------------") df.pop("score") print(df) print("--------------")
结果如下
4.获取某行的数据(loc)
import pandas as pd data = { "name": ["小勇","小锋","小民"], "age": [28,29,30], } df = pd.DataFrame(data,index=["a","b","c"]) print(df) print("--------------") print(df.loc["a"]) print("--------------") print(df.loc["a":"b"]) print("--------------")
结果如下
5.删除某行的数据(drop)
import pandas as pd data = { "name": ["小勇","小锋","小民"], "age": [28,29,30], } df = pd.DataFrame(data,index=["a","b","c"]) print(df) print("--------------") df = df.drop("b") print(df) print("--------------")
结果如下
6.行列转换(T)、获取轴上的字段名(axes)、获取数据类型(dtypes)、清空(empty)
import pandas as pd data = { "name": ["小勇","小锋","小民"], "age": [28,29,30], } df = pd.DataFrame(data,index=["a","b","c"]) print(df) print("--------------") # 行列转换 print(df.T) print("--------------") # 获取轴上的字段名 print(df.axes) print("--------------") # 获取数据类型 print(df.dtypes) print("--------------") # 清空 print(df.empty) print("--------------")
结果如下
7.获取矩阵形状(shape)、矩阵元素数量(size)、头部和尾部(head和tail)
import pandas as pd data = { "name": ["小勇","小锋","小民"], "age": [28,29,30], } df = pd.DataFrame(data,index=["a","b","c"]) print(df) print("--------------") # 获取矩阵形状 print(df.shape) print("--------------") # 获取矩阵元素数量 print(df.size) print("--------------") # 获取头部和尾部 print(df.head(2)) print("--------------") print(df.tail(2)) print("--------------")
结果如下