(self, key, value) 1284 ) 1285 1286 check_dict_or_set_indexers(key) 1287 key = com.apply_if_callable(key, self) -> 1288 cacher_needs_updating = self._check_is_chained_assignment_possible() 1289 1290 if key is Ellipsis: 1291 key = slice(None) ~/work/pandas/pandas/pandas/core/seri...
converters={"col_1": str}) In [19]: df Out[19]: col_1 0 1 1 2 2 'A' 3 4.22 In [20]: df["col_1"].apply(type).value_counts() Out[20]: col_1 <class 'str'> 4 Name: count, dtype: int64
6, 7, 8]},...: index=pd.MultiIndex.from_product([["a", "b"], ["c", "d"]]),...: )...:In [425]: df.to_excel("path_to_file.xlsx")In [426]: df = pd.read_excel("path_to_file.xlsx", index_col=[0, 1])In [427]: dfOut[427]:a ba c 1 5d 2 6b c 3 7d 4...
the Dat 获取和设置选项 如上所述,get_option()和set_option()可从 pandas 命名空间中调用。要更改选项,请调用set_option('option regex', new_value)。 In [12]: pd.get_option("mode.sim_interactive")Out[12]: FalseIn [13]: pd.set_option("mode.sim_interactive", True)In [14]: pd.get_opt...
要将pyarrow.Table转换为DataFrame,您可以使用types_mapper=pd.ArrowDtype调用pyarrow.Table.to_pandas()方法。 In [33]: table = pa.table([pa.array([1,2,3],type=pa.int64())], names=["a"]) In [34]: df = table.to_pandas(types_mapper=pd.ArrowDtype) ...
freeze_panes=freeze_panes,File"D:\Users\Admin\Anaconda3\envs\tf2\lib\site-packages\pandas\io\excel\_openpyxl.py",line414,inwrite_cells xcell.value, fmt = self._value_with_fmt(cell.val)File"D:\Users\Admin\Anaconda3\envs\tf2\lib\site-packages\openpyxl-3.0.7-py3.7.egg\openpyxl\cell\cell...
.FindFormat.Interior .Pattern = xlSolid .color = searchColor End With ' Do the search Dim cell As Range Set cell = ws.Cells.Find(What:="", after:=afterCell, SearchDirection:=xlNext, SearchFormat:=True) If cell Is Nothing Then Exit Function ' now cell found with color If cell.row ...
format = workbook.add_format({'bg_color': '#21AD25'})# worksheet.set_row(0, cell_format=...
In [19]: pd.Series([0, 1, 2], index=["a", "b", "b"]).set_flags(allows_duplicate_labels=False) --- DuplicateLabelError Traceback (most recent call last) Cell In[19], line 1 ---> 1 pd.Series([0, 1, 2], index=["a", "b", "b"]).set_flags(allows_duplicate_labels=...
方法append_to_multiple和select_as_multiple可以同时从多个表中执行追加/选择操作。其思想是有一个表(称之为选择器表),你在这个表中索引大部分/全部列,并执行你的查询。其他表是数据表,其索引与选择器表的索引匹配。然后你可以在选择器表上执行非常快速的查询,同时获取大量数据。这种方法类似于拥有一个非常宽的...