In this post, I’ll show you a trick to flatten out MultiIndex Pandas columns to create a single index DataFrame. To start, I am going to create a sample DataFrame: Python 1 df = pd.DataFrame(np.random.randint(3,size=(4, 3)), index = ['apples','apples','oranges','oranges'],...
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...
参数: axis : {index (0), columns (1)} skipna : 布尔值,默认为True.表示跳过NaN值.如果整行/列都是NaN,那么结果也就是NaN level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series numeric_only : boolean...
3. MultiIndex to Single Index Sometimes you may be required to convert MultiIndex (multi-level) to a single Index. You can do this either by keeping one Index and converting the rest to columns or dropping them. # MultiIndex to Single Indexdf2=df.reset_index(level=[1])print("Convert mult...
Be careful to distinguish(分辨) the index names 'state' and 'color' Wiht partial column indexing you can similarly selectgroups of columns: (使用部分列索引, 可以相应地使用列组) frame['Ohio'] A MultiIndex can be created by itself and then reused; the columns in the preceding DataFrame with...
unless it is passed, in which case the values will beselected (see below). Any None objects will be dropped silently unlessthey are all None in which case a ValueError will be raised.axis : {0/'index', 1/'columns'}, default 0The axis to concatenate along.join : {'inner', 'outer'...
axis:{0 or ‘index’, 1 or ‘columns’},默认0 如果是 0 或“索引”,为每列生成计数。如果是 1 或“列”,为每一行生成计数。 level:int 或 str,可选 如果轴是 MultiIndex(分层),则沿特定级别计数,折叠成 DataFrame。 str 指定级别名称。
DataFrame( [[None, 10], [11, 7.0]], index=['London', 'Oxford'], columns=multi_col_2 ) df_multi_level_3.stack() df_multi_level_3.stack(dropna=False) 6. unstack: 简单案例 同样,Pandas unstack() 也支持参数级别,默认为 -1,它将对最内层索引应用操作。 index = pd.MultiIndex.from_...
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...
python--Pandas中DataFrame基本函数(略全) pandas里的dataframe数据结构常用函数。 构造函数 方法描述 DataFrame([data, index, columns, dtype, copy])构造数据框 属性和数据 方法描述 Axesindex: row la