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
value_vars, …])“Unpivots” a DataFrame from wide format to long format, optionallyDataFrame.TTranspose index and columnsDataFrame.to_panel()Transform long (stacked) format (DataFrame) into wide (3D, Panel) format.DataFrame.to_xarray()Return...
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']], names=['state','color']) tmp MultiIndex(levels=[['Col...
五、重设Index与Columns_name 1、重设Index行标签: 方法一:df.index=自定义的索引值np数组(列表) 方法二:df.set_index(keys,drop,inplace):把现有的列(列组合则是多级索引multiIndex)或者一个长度正确的array设置为index 方法三:df.reset_index(drop,inplace):重新设置索引,即变成0、1、2、3... 方法四:有...
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。
See the indexing documentationIndexing and Selecting DataandMultiIndex / Advanced Indexing Getting Selecting a single column, which yields aSeries, equivalent todf.A In [23]:df['A']Out[23]:2013-01-01 0.4691122013-01-02 1.2121122013-01-03 -0.8618492013-01-04 0.7215552013-01-05 -0.4249722013-01-...
Reset single level of MultiIndex df.reset_index(level=1) Copy Typical Errors on Pandas Drop MultiIndex When the droplevel is invoked on wrong axis: columns or rows like: cols=pd.MultiIndex.from_tuples([(0,1),(0,1)])df=pd.DataFrame([[1,2],[3,4]],index=cols)df.columns.droplevel()...
to_csv(self, path_or_buf: 'FilePathOrBuffer[AnyStr] | None' = None, sep: 'str' = ',', na_rep: 'str' = '', float_format: 'str | None' = None, columns: 'Sequence[Hashable] | None' = None, header: 'bool_t | list[str]' = True, index: 'bool_t' = True, index_label...
left_index: If True, use the index (row labels) from the left DataFrame or Series as its join key(s). In the case of a DataFrame or Series with a MultiIndex (hierarchical), the number of levels must match the number of join keys from the right DataFrame or Series. ...
If I use MultiIndex columns and if a level happens to have empty values for all columns, the saved CSV file cannot be read. I expected to recover the dataframe from the saved CSV perfectly. I believe #6618 might be related, because this ...