arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']] pd.MultiIndex.from_arrays(arrays, names=('number', 'color')) # 结果 MultiIndex(levels=[[1, 2], ['blue', 'red']], codes=[[0, 0, 1, 1], [1, 0, 1, 0]], names=['number', 'color']) 2、Panel (1)...
可以使用df.columns命令对数据字段进行预览 df.columns 使用df.dtypes命令查看数据类型，其中，日期是日期...
4.2 连接时处理索引 # 忽略原有索引result=pd.concat([df5,df6],ignore_index=True)print("\nConcatenation with Ignored Index:\n",result)# 添加多级索引result=pd.concat([df5,df6],keys=['df5','df6'])print("\nConcatenation with MultiIndex:\n",result) 1. 2. 3. 4. 5. 6. 7. 5. 数据...
通过为 header 参数指定行位置列表,您可以读取列的 MultiIndex。指定非连续行将跳过介于其间的行。 In [211]: mi_idx = pd.MultiIndex.from_arrays([[1, 2, 3, 4], list("abcd")], names=list("ab")) In [212]: mi_col = pd.MultiIndex.from_arrays([[1, 2], list("ab")], names=list("...
A MultiIndex can be created by itself and then reused; the columns in the preceding DataFrame with level names could be created like this. tmp = pd.MultiIndex.from_arrays([['Ohio','Ohio','Colorado'], ['Green','Red','Green']], ...
df = pd.DataFrame([[38.0, 2.0, 18.0, 22.0, 21, np.nan],[19, 439, 6, 452, 226,232]],index=pd.Index(['Tumour (Positive)', 'Non-Tumour (Negative)'], name='Actual Label:'),columns=pd.MultiIndex.from_product([['Decision Tree', 'Regression', 'Random'],['Tumour', 'Non-Tumour...
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...
MultiIndex.from_product(iterables) Create aMultiIndex from the cartesian product of iterables.用可迭代对象创建一个MultiIndex对象。 numbers = [0, 1, 2] colors= ['green','purple'] pd.MultiIndex.from_product([numbers, colors], names=['number','color'])#产生类似笛卡尔积的list集合.MultiIndex([...
Pandas中一共有三种数据结构,分别为:Series、DataFrame和MultiIndex(老版本中叫Panel )。 其中Series是一维数据结构,DataFrame是二维的表格型数据结构,MultiIndex是三维的数据结构。 1.2.1 Series Series是一个类似于一维数组的数据结构,它能够保存任何类型的数据,比如整数、字符串、浮点数等,主要由一组数据和与之相关的...
Naming pandas multilevel columns For pandas multilevel column name, you can usepandas.MultiIndex.from_tuples()method inside which we will pass the column that we want to add. Since pandas have support for multilevel column names, this feature is very useful since it allows multiple versions of...