① 全部列都选中时，就不用设置subset参数 ② 设置keep=last，就会看到默认的索引是最后一行 ③ 在上面的基础上设置ignore_index=True，可以看到索引进行重新排列 ④ 设置keep=False，就会删除所有重复的数据行
duplicate_rows = df.duplicated() 替换重复值:可以使用drop_duplicates()函数将重复的行从 DataFrame 中删除,只保留第一次出现的行。默认情况下,drop_duplicates()函数会比较 DataFrame 的所有列,并根据所有列的值判断是否为重复行。可以通过指定subset参数来只比较特定的列。
By usingpandas.DataFrame.T.drop_duplicates().Tyou can drop/remove/delete duplicate columns with the same name or a different name. This method removes all columns of the same name beside the first occurrence of the column and also removes columns that have the same data with a different colu...
删除重复的数据# Removing duplicate rows df.drop_duplicates(subset=['Column1
pandas的drop_duplicate方法 `pandas` 的 `drop_duplicates` 方法用于从 `DataFrame` 或 `Series` 中删除重复的行或元素。它通常用于数据清洗,以去除数据集中的重复项。 ### 基本用法 对于`DataFrame`: ```python import pandas as pd # 创建一个示例 DataFrame df = pd.DataFrame({ 'A': [1, 2, 2, ...
It’s crucial to specify whether to drop rows based on index labels or positions, utilizing appropriate parameters such aslabelsorindex. 1. Create a Sample DataFrame Let’s create a pandas DataFrame to explain how to remove the list of rows with examples, my DataFrame contains the column names...
False– Drop all duplicates. inplace:It is used to specify whether to return a new DataFrame or update an existing one. It is a boolean flag with default False. ignore_index:It is a boolean flag to indicate if row index should be reset after dropping duplicate rows.False: It keeps the...
Pandas duplicated and drop_duplicates:查找并去除重复项 DataFrame.drop_duplicates(subset=None, keep='first', inplace=False) method of pandas.core.frame.DataFrame instance Return DataFrame with duplicate(重复) rows removed, optionally only considering ce... ...
df.drop(1)/df.drop([1,2],inplace=True) X. 将多个df写入指定工作簿的不同worksheet writer = pd.ExcelWriter(resultPath, engine='openpyxl') df.to_excel(writer,sheet_name='第一张表',index=False) df2.to_excel(writer,sheet_name='第二张表',index=False) ...
运行结果如下: nameage marksaJoe2085.10bNat2177.80cHarry1991.54dNat2177.80dropduplicate rows with ignore_index=False:nameage marksaJoe2085.10cHarry1991.54dropduplicate rows with ignore_index=True:nameage marks0Joe2085.101Harry1991.54