drop_duplicates(keep='first') # 保留最后一次出现的行,删除之前的重复行 df_unique = df.drop_duplicates(keep='last') 在实际应用中,选择哪种去重方法取决于你的具体需求。如果你只是想简单地删除重复行,drop_duplicates() 方法是最直接的选项。如果你想找出重复的行,或者在读取数据时直接去除重复行,其他方法...
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 onedf.drop_duplicates(keep='first', ...
DataFrame.drop_duplicates(self, subset=None, keep='first', inplace=False) Return DataFrame with duplicate rows removed, optiona
pandas.DataFrame.drop_duplicates()函数 columns.也就是删除重复的行之后返回一个DataFrame,可以选择只考虑某些列。 函数原型如下:DataFrame.drop_duplicates(subset=None,keep='first',inplace=False)对3个参数的解释如下: 举个例子,a.csv内容如下。下面的代码的运行结果是执行下面的代码 结果为 ...
duplicated() # Check the number of duplicate rows df.duplicated().sum() drop_duplates()可以使用这个方法删除重复的行。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # Drop duplicate rows (but only keep the first row) df = df.drop_duplicates(keep='first') #keep='first' / keep='...
# Check duplicate rows df.duplicated() # Check the number of duplicate rows df.duplicated().sum() 1. 2. 3. 4. 5. drop_duplates() 1. 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...
# Removing duplicate rowsdf.drop_duplicates(subset=['Column1', 'Column2'], keep='first', inplace=True) 14、创建虚拟变量 pandas.get_dummies() 是 Pandas 中用于执行独热编码(One-Hot Encoding)的函数。 # Creating dummy variables for categorical datadummy_...
# Check the number of duplicate rows df.duplicated().sum() 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...
df2 = df.loc[:,~df.T.duplicated(keep='last')] # Example 6: Use DataFrame.columns.duplicated() # To drop duplicate columns duplicate_cols = df.columns[df.columns.duplicated()] df.drop(columns=duplicate_cols, inplace=True) Now, let’s create a DataFrame with a few duplicate rows and ...
pandas.get_dummies(data, prefix=None, prefix_sep=’_’, dummy_na=False, columns=None, sparse=False, drop_first=False) pandas中drop()函数用法 函数定义:DataFrame.drop(labels=None,axis=0, index=None, columns=None, inplace=False) 删除单个行 axis=0,指删除index,因此删除columns时要指定axis=1...