pandas-读取数据并显示,pd.read_csv,df.tail(5),df.shape,df.shape

dirty-data.csv 里边的数据内容

员工ID,姓名,部门,入职日期,年龄,月薪,月度业绩,考勤天数,学历,在职状态 1001,张三,技术部,2020-03-15,28,8500,12000,22,本科,是 1002,李四,市场部,2021/05/20,35,9800,--,20,硕士,是 1003,王五,,2022-01-08,,7600,8500,18,大专,否 1004,赵六,销售部,2020.11.30,42,12000,25000,25,本科,1 1005,,技术部,2023-07-12,26,6800,NaN,23,本科,是 1006,孙七,市场部,2021-09-05,31,8900,9800,-5,硕士,是 1007,周八,销售部,,33,10500,18000,21,大专,否 1008,吴九,技术部,2022/06/18,29,9200,15000,24,n/a,是 1009,郑十,行政部,2023-02-20,58,7300,6500,19,本科,是 1010,钱十一,市场部,2020-12-03,36,11000,13000,22,博士,否 1011,冯十二,销售部,2021.04.15,,9500,21000,26,本科,是 1012,陈十三,技术部,2022-08-25,27,7900,10000,23,大专,0 1013,褚十四,,2023-03-10,34,8200,9200,,本科,是 1014,卫十五,行政部,2021/10/18,45,6500,5800,17,硕士,是 1015,蒋十六,销售部,2020-06-22,38,13500,30000,24,本科,否 1016,沈十七,市场部,2022.03.05,29,8600,7500,21,大专,是 1017,韩十八,技术部,,32,9800,14000,22,本科,是 1018,杨十九,销售部,2023-05-18,40,11500,23000,25,硕士,是 1019,朱二十,行政部,2021-02-12,52,7800,6200,19,本科,否 1020,秦二十一,市场部,2022-11-08,33,9100,8800,20,博士,是

读取数据

# 读取数据importpandasaspd df=pd.read_csv('./dirty-data.csv')# 显示csv 里边的所有的数据df

# nrows 只读取3行数据df=pd.read_csv('./dirty-data.csv',nrows=3,)df

# nrows 只读取3行数据 usecols=[0,1,2] 选择 列的下标 是0,1,2的列df=pd.read_csv('./dirty-data.csv',nrows=3,usecols=[0,1,2])df

# header=None 表示标题也算数据的一部分df=pd.read_csv('./dirty-data.csv',nrows=3,usecols=[0,1,2],header=None)df

# skiprows=1 跳过第一行,再取3条数据df=pd.read_csv('./dirty-data.csv',nrows=3,usecols=[0,1,2],header=None,skiprows=1)df

显示数据

df=pd.read_csv('./dirty-data.csv')# 显示前5行数据df.head(5)

# 显示后5行数据df.tail(5)

# 显示数据有 几行几列df.shape

(20, 10)

# 显示数据所有的列名df.columns.values

array(['员工ID', '姓名', '部门', '入职日期', '年龄', '月薪', '月度业绩', '考勤天数', '学历', '在职状态'], dtype=object)