'pandasdataframe.com4','pandasdataframe.com5'],'other_column':['other1','other2','other3','other4','other5']},index=['row1','row2','pandasdataframe.com_row','row4','row5'])# 使用filter方法选择行filtered_df=df.filter(axis=0,regex='pandasdataframe.com')print(filtered_df) Python Copy Output: 以上就...
ref: Ways to filter Pandas DataFrame by column values Filter by Column Value: To select rows based on a specific column value, use the index chain met
Sometimes, you may want to find a subset of data based on certain column values. You can filter rows by one or more columns value to remove non-essential data. Pandas DataFrame sample data Here is sample Employee data which will be used in below examples: NameAgeGender Ravi 28 Male Mich...
import polars as pl import time # 读取 CSV 文件 start = time.time() df_pl_gpu = pl.read_csv('test_data.csv') load_time_pl_gpu = time.time() - start # 过滤操作 start = time.time() filtered_pl_gpu = df_pl_gpu.filter(pl.col('value1') > 50) filter_time_pl_gpu = time.t...
df.filter(items=['column_name1', 'column_name2']) # 选择列名匹配正则表达式的列 df.filter(regex='regex') # 随机选择 n 行数据 df.sample(n=5)数据排序函数说明 df.sort_values(column_name) 按照指定列的值排序; df.sort_values([column_name1, column_name2], ascending=[True, False]) 按照...
column_first = df.iloc[:, 0] # 第一列 columns_first_two = df.iloc[:, :2] # 前两列 参考文档:Python Pandas 数据选择与过滤-CJavaPy 2)列的过滤 可以基于列名的过滤、基于条件的过滤、使用列表推导式和使用filter函数的方法进行过滤,如下, ...
1...导入 Pandas 库在使用 Pandas 之前,首先导入 Pandas 库: import pandas as pd 3...数据分组 4.1 单列分组 # 按某一列进行分组 grouped = df.groupby('column_name') 4.2 多列分组 # 按多列进行分组 grouped = df.groupby(...过滤通过 filter 方法可以根据分组的统计信息筛选数据: # 过滤出符合条...
df.filter(items=['Q1', 'Q2']) # 选择两列df.filter(regex='Q', axis=1) # 列名包含Q的列df.filter(regex='e$', axis=1) # 以e结尾的列df.filter(regex='1$', axis=0) # 正则,索引名以1结尾df.filter(like='2', axis=0) # 索引中有2的# 索引...
实例1 将分组后的字符拼接 import pandas as pd df=pd.DataFrame({ 'user_id':[1,2,1,3,3], 'content_id':[1,
Filter by isin() with Non-numeric Index Similarly, If you have values in a list and wanted to filter the DataFrame with these values, useisin()function. Suppose you would like to filter for rows where the non-numeric index value is equal to'Inx_A','Inx_B','Inx_C', or'Inx_AC'it...