Most of these fall into the categrory of reductions or summary statistics, methods that exract(提取) a single value(like the sum or mean) from a Series of values from the rows or columns of a DataFrame. Compared with the similar methods found on NumPy arrays, they built-in handling for ...
df.iat[i, j] 行列位置来选取 reindex method Select either rows or columns by labels get_value, setvalue methods Select single value by row and column label Integer Indexes
首先使用Polars CPU对数据集进行读取、过滤、分组聚合等处理。 import polars as pl import time # 读取 CSV 文件 start = time.time() df_pl = pl.read_csv('test_data.csv') load_time_pl = time.time() - start # 过滤操作 start = time.time() filtered_pl = df_pl.filter(pl.col('value1'...
缺失数据 / 使用填充值的操作 在Series 和 DataFrame 中,算术函数有一个 fill_value 选项,即在某个位置的值缺失时要替换的值。例如,当添加两个 DataFrame 对象时,您可能希望将 NaN 视为 0,除非两个 DataFrame 都缺少该值,此时结果将为 NaN(如果需要,您可以稍后使用 fillna 将NaN 替换为其他值)。 代码语言:...
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。 数据...
Most of these fall into the categrory of reductions or summary statistics, methods that exract(提取) a single value(like the sum or mean) from a Series of values from the rows or columns of a DataFrame. Compared with the similar methods found on NumPy arrays, they built-in handling for ...
For getting a value explicitlyFor getting fast access to a scalar (equivalent to the prior method)// Boolean IndexingUsing a single column’s values to select data.Selecting values from a DataFrame where a boolean condition is met.Using the isin( ) method for filtering:...
isin([]):基于列表过滤数据。df (df (column_name”).isin ([value1, ' value2 '])) # Using isin for filtering rows df[df['Customer Country'].isin(['United States', 'Puerto Rico'])] # Filter rows based on values in a list and select spesific columns ...
·Select single value by rowandcolumn labels>>> df.loc[0,'Country']'Belgium'l ·Select single row of subset rows>>> df.ix[2]Country BrazilCapital BrasiliaPopulation208476l ·Select a single column of subset of columns>>> df.ix[:,'Capital']0Brussels1New Delhi2Brasilial ·Select rowsand...
Compared with NumPy arrays, you can use labels in the index when selecting single values or a set of values.-> 通过index来选取单个或多个元素 "选取单个元素[index]" obj2['a'] "修改元素-直接赋值-修改是-inplace" obj2['d']='cj' ...