Thedrop()method in Pandas DataFrame is used to remove rows or columns based on their index labels. By default, thedrop()method removes rows (axis=0). You can specifyaxis=1or column parameter to drop columns instead. To specify the rows you want to drop, pass a list of index labels to...
The “set_index()” method sets the index by taking the specified column name as an argument. The “reset_index()” takes the parameter “drop=True” and removes/drops the index of the Pandas DataFrame. Output The DataFrame has been removed successfully. Example 2: Remove the Multi-Index ...
百度试题 结果1 题目pandas中用于从DataFrame中删除指定列的方法是: A. drop_columns() B. remove_columns() C. delete_columns() D. drop() 相关知识点: 试题来源: 解析 D 反馈 收藏
Assume you want to drop the first column or the last column of the DataFrame without using the column name. In such cases, use the DataFrame.columns attribute to delete a column of the DataFrame based on its index position. Simply passdf.columns[index]to the columns parameter of theDataFrame...
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...
Example 3: Remove Multiple Columns from pandas DataFrame by Index PositionSo far, we have used the column names to get rid of certain variables. This example explains how to delete columns of a pandas DataFrame using the index position of these columns....
df = df.reset_index(level='Age', drop=True) print(df) The index column has been deleted from the multi-index without keeping the value: Dropping Other Columns Using “DataFrame.drop()” Method We can also use the drop() method to remove any other columns from the data frame by specify...
df.to_excel(writer, index=False)# 读取Excel数据output.seek(0)df = pd.read_excel(output)# 输出数据基本信息print(df.info())"""输出:<class 'pandas.core.frame.DataFrame'>RangeIndex: 3 entries, 0 to 2Data columns (total 3 columns): # Column Non-Null Count Dtype --- --- --...
The operators are: | for or, & for and, and ~ for not. These must be grouped by using parentheses. To remove all rows where column 'score' is < 50 and > 20 df= df.drop(df[(df.score < 50) & (df.score > 20)].index)
当列很多的时候,每个column对应的index一个个数可太麻烦了,df.info()是一个非常简洁又高效的方法。他会返回dataframe的行数,列数,列名对应的index,数据类型,非空值和memory usage。 所以第一个df.info()就是为了找出你要删的列明的起始index和终止index,注意,如果你要删2-4列,stop_index应该是5才会把第4列...