na_rep: 'str | None' = None, precision: 'int | None' = None, decimal: 'str' = '.', thousands: 'str | None' = None, escape: 'str | None' = None,) -> 'StylerRenderer'Docstring:Format the text display value of cells.formatter...
In [1]: import numba In [2]: def double_every_value_nonumba(x): return x * 2 In [3]: @numba.vectorize def double_every_value_withnumba(x): return x * 2 # 不带numba的自定义函数: 797 us In [4]: %timeit df["col1_doubled"] = df["a"].apply(double_every_value_nonumba) ...
() ---> 1 df and df2 ~/work/pandas/pandas/pandas/core/generic.py in ?(self) 1575 @final 1576 def __nonzero__(self) -> NoReturn: -> 1577 raise ValueError( 1578 f"The truth value of a {type(self).__name__} is ambiguous. " 1579 "Use a.empty, a.bool(), a.item(), a....
(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...
pandas 可以利用PyArrow来扩展功能并改善各种 API 的性能。这包括: 与NumPy 相比,拥有更广泛的数据类型 对所有数据类型支持缺失数据(NA) 高性能 IO 读取器集成 便于与基于 Apache Arrow 规范的其他数据框架库(例如 polars、cuDF)进行互操作性 要使用此功能,请确保您已经安装了最低支持的 PyArrow 版本。
cell = worksheet.cell(row=row_index, column=col_index) cell.value = merged_cell.value# 读取原始xlsx文件,拆分并填充单元格,然后生成中间临时文件。defunmerge_cell(filename): wb = openpyxl.load_workbook(filename)forsheet_nameinwb.sheetnames: ...
.PyObjectHashTable.get_item() File pandas/_libs/hashtable_class_helper.pxi:7089, in pandas._libs.hashtable.PyObjectHashTable.get_item() KeyError: 'a' The above exception was the direct cause of the following exception: KeyError Traceback (most recent call last) Cell In[27], line 1 --...
fillna(value) # 填充缺失值 # 数据转换和处理 df.groupby(column_name).mean() # 按列名分组并计算均值 df[column_name].apply(function) # 对某一列应用自定义函数 数据可视化 import matplotlib.pyplot as plt # 绘制柱状图 df[column_name].plot(kind="bar") # 绘制散点图 df.plot(...
运行cell:shift+enter今日重点:数据清洗、map映射和map充当运算工具、groupby分组聚合、pivot_table透视¶In [ ]: pdf有表格 pandas+。。。手机销量分析案例¶巩固分组聚合操作 In [46]: #加载数据 import pandas as pd data = pd.read_excel('./data/Phone.xlsx')In...
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_option("mode.sim_interactive...