///////////////////////////////////////////////// df = pd.DataFrame({"ID":[1,2,3], "Name":["Time", "Victor", "Nick"]}) df = df.set_index("ID") # 设置索引 print(df) df.to_excel("C:/Users/Administrator/Desktop/Test_excel/output.xlsx") print("Done!") ///////////////////////////////////////////////// import pandas as pd people = pd.read_excel("C:/Users/Administrator/Desktop/Test_excel/id.xls") print(people.shape) # 有效行列 print(people.columns) # 有效列 print(people.head()) # 默认 - 前五行 print(people.head(3)) # 默认 - 前五行 print(people.tail(5)) # 默认 - 尾五行 ///////////////////////////////////////////////// // 空行/乱行处理 - // columns 从0开始 people = pd.read_excel("C:/Users/Administrator/Desktop/Test_excel/id.xls",header=1 // ) ///////////////////////////////////////////////// // 没columns处理 people = pd.read_excel("C:/Users/Administrator/Desktop/Test_excel/id.xlsx", header=None) people.columns = ["id", "nsc_id", "num", "engish_name", "chinese_name"] # 设置列头 people = people.set_index("id") # 设置索引 people.set_index("id", inplace=True) # 设置索引 people.to_excel("C:/id.xlsx") # 复制表格 ///////////////////////////////////////////////// // 其他数据类型 -> pd // 方法一 d = {"x":100, "y":200, "z":300} print(d) s1 = pd.Series(d) print(s1) print(s1.index) // 方法二 L1 = [100, 200, 300] L2 = ["x", "y", "z"] s1 = pd.Series(L2,index=L1) print(s1) print(s1.index) // 方法三 s1 = pd.Series([100, 200, 300],index=["x", "y", "z"]) print(s1) print(s1.index) // 方法四 s1 = pd.Series(["Time", "Victor", "Nick"],index=[1,2,3]) print(s1) ///////////////////////////////////////////////// // BUG 1 变成科学计数法: 1326732364356800522 -> 1310146663108920000
import pandas as pd # 读取原始表 df_grade = pd.read_excel("E:/ProgramData/PyCharm/pandas_v2/excels/学生成绩表.xlsx") print(df_grade.head()) df_sinfo = pd.read_excel("E:/ProgramData/PyCharm/pandas_v2/excels/学生信息表.xlsx") print(df_sinfo.head()) # 裁剪表 df_sinfo = df_sinfo[["学号", "姓名", "性别"]] print(df_sinfo.head()) # 拼接表 df_merge = pd.merge(left=df_grade, right=df_sinfo, left_on="学号", right_on="学号") print(df_merge.head()) # 调整列的顺序 new_columns = df_merge.columns.to_list() print(new_columns) for name in ["姓名", "性别"][::-1]: new_columns.remove(name) new_columns.insert(new_columns.index("学号") + 1, name) print(new_columns) df_merge = df_merge.reindex(columns = new_columns) print(df_merge.head()) # 输出表 df_merge.to_excel("E:/ProgramData/PyCharm/pandas_v2/excels/merge.xlsx")