"second"]) Out[9]: MultiIndex([('bar', 'one'), ('bar', 'two'), ('baz', 'one'), ('baz', 'two'), ('foo', 'one'), ('foo', 'two'), ('qux', 'one'), ('qux', 'two')], names=['first', 'second'
# 指定’姓名‘或’班级‘这一列为行索引df = pd.read_excel('C:/Users/asus/Desktop/index.xlsx',index_col='姓名')# df = pd.read_excel('C:/Users/asus/Desktop/index.xlsx',index_col='班级')df # 指定’班级‘、’姓名‘这两列为层级索引MultiIndexdf = pd.read_excel('C:/Users/asus/Deskt...
df = pd.read_excel('C:/Users/asus/Desktop/index.xlsx',index_col='姓名') # df = pd.read_excel('C:/Users/asus/Desktop/index.xlsx',index_col='班级') df 1. 2. 3. 4. # 指定’班级‘、’姓名‘这两列为层级索引MultiIndex df = pd.read_excel('C:/Users/asus/Desktop/index.xlsx',in...
In [1]: dates = pd.date_range('1/1/2000', periods=8) In [2]: df = pd.DataFrame(np.random.randn(8, 4), ...: index=dates, columns=['A', 'B', 'C', 'D']) ...: In [3]: df Out[3]: A B C D 2000-01-01 0.469112 -0.282863 -1.509059 -1.135632 2000-01-02 1.212112...
random.randint(0,10,size = (20,3)), columns=['Python','Math','En'], index = pd.MultiIndex.from_product([list('ABCDEFHIJK'),['期中','期末']])) # 多层索引 df2由图可见,行索引是分两级的,这时候如果想对行索引进行单级别的行列转换,就需要用到unstack函数:...
2.MultiIndex的结构 .name为普通属性,返回MultiIndex的名字。同Index .values/._values为property属性,返回MultiIndex的内部数据的视图。同Index ._data为None,这里是与Index不同。 .shape为property属性,返回内部属性的形状 。同Index ._engine为标签映射管理器,它负责管理label和下标之间的映射。同Index ...
使用MultiIndex 读取索引 假设您的数据由两列索引: In [205]: data = 'year,indiv,zit,xit\n1977,"A",1.2,.6\n1977,"B",1.5,.5' In [206]: print(data) year,indiv,zit,xit 1977,"A",1.2,.6 1977,"B",1.5,.5 In [207]: with open("mindex_ex.csv", mode="w") as f: ...: ...
first_valid_index() 返回第一个非NA /空值的索引。floordiv(other[, axis, level, fill_value]) 获取数据帧的整数除法和其他逐元素的方法(二进制运算符florordiv)。 from_dict(data[, orient, dtype, columns]) 从类似数组或字典的字典构造DataFrame。from_records(data[, index, exclude, …]) 将结构化...
Thereset_index()function also comes in handy when dealing with multi-index DataFrames. Let’s create a multi-index DataFrame and see how to reset its index: index=pd.MultiIndex.from_tuples([(i,j)foriinrange(3)forjinrange(3)],names=['outer','inner'])df=pd.DataFrame({'A':range(9...
64Index GrouperHDFStore Index IndexSlice Int16Dtype Int32DtypeInt64Dtype Int64Index Int8Dtype Interval IntervalDtypeIntervalIndex MultiIndex NA NaT NamedAggPeriod PeriodDtype PeriodIndex RangeIndex SeriesSparseDtype StringDtype Timedelta TimedeltaIndex TimestampUInt16Dtype UInt32Dtype UInt64Dtype UInt64Index ...