duplicate_rows = data.duplicated() 删除重复行:使用pandas的drop_duplicates()函数删除重复行。该函数会返回一个新的DataFrame对象,其中不包含重复行。可以使用以下代码删除重复行: 代码语言:txt 复制 data = data.drop_duplicates() 完整的代码示例: 代码语言:txt 复制 import pandas as pd # 读取数据 data = ...
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。
DataFrame.drop_duplicates(self, subset=None, keep='first', inplace=False) Return DataFrame with duplicate rows removed, optiona
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...
Table 1 shows the output of the previous syntax: We have created some example data containing seven rows and three columns. Some of the rows in our data are duplicates. Example 1: Drop Duplicates from pandas DataFrame In this example, I’ll explain how to delete duplicate observations in a...
对于数据转换,pandas常用的函数使用 删除重复元素对于重复值的处理 DataFrame.duplicated(subset=None,keep='first')Return boolean Series denoting duplicate rows. 返回的是布尔数组,表示该行是否是…
drop_duplicates()is used to remove duplicate rows from a DataFrame. You can specify which columns to check for duplicates using thesubsetparameter. By default,drop_duplicates()keeps the first occurrence of each duplicate row, but you can change this behavior with thekeepparameter (e.g., ‘last...
TheDataFrame.drop_duplicates()function This function is used to remove the duplicate rows from a DataFrame. DataFrame.drop_duplicates(subset=None, keep='first', inplace=False, ignore_index=False) Parameters: subset: By default, if the rows have the same values in all the columns, they are ...
Remove duplicate rows from the DataFrame: importpandas as pd data = { "name": ["Sally","Mary","John","Mary"], "age": [50,40,30,40], "qualified":[True,False,False,False] } df = pd.DataFrame(data) newdf= df.drop_duplicates() ...
drop_duplates()可以使用这个方法删除重复的行。 # Drop duplicate rows (but only keep the first row) df = df.drop_duplicates(keep='first') #keep='first' / keep='last' / keep=False # Note: inplace=True modifies the DataFrame rather than creating a new one df.drop_duplicates(keep='first...