我们可以使用以下代码删除columnB: df = df.drop('B', axis=1) print(df) 输出: A C 0 1 7 1 2 8 2 3 9 在drop方法中,我们需要指定要删除的column名称以及axis参数为1,表示删除column。同时,我们要将删除后的结果重新赋值给原来的变量,这样才能真正删除column。
DataFrame.xs(key[, axis, level, drop_level]) #Returns a cross-section (row(s) or column(s)) from the Series/DataFrame. DataFrame.isin(values) #是否包含数据框中的元素 DataFrame.where(cond[, other, inplace, …]) #条件筛选 DataFrame.mask(cond[, other, inplace, …]) #Return an object...
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
DataFrame.insert(loc, column, value[, …]) 在特殊地点插入行 DataFrame.iter() Iterate over infor axis DataFrame.iteritems() 返回列名和序列的迭代器 DataFrame.iterrows() 返回索引和序列的迭代器 DataFrame.itertuples([index, name]) Iterate over DataFrame rows as namedtuples, with index value as fi...
DataFrame.lookup(row_labels, col_labels)Label-based “fancy indexing” function for DataFrame. DataFrame.pop(item)返回删除的项目 DataFrame.tail([n])返回最后n行 DataFrame.xs(key[, axis, level, drop_level])Returns a cross-section (row(s) or column(s)) from the Series/DataFrame. ...
# Set DataFrame column values based on other column values (h/t: @mlevkov) df.loc[(df['column1'] == some_value) & (df['column2'] == some_other_value), ['column_to_change']] = new_value 创建新变量 # Concatenate two DataFrame columns into a new, single column # (useful whe...
In PySpark, we can drop one or more columns from a DataFrame using the .drop("column_name") method for a single column or .drop(["column1", "column2", ...]) for multiple columns.
columnNames IEnumerable<String> 列名 返回 DataFrame DataFrame 对象 适用于 Microsoft.Spark latest 产品版本 Microsoft.Sparklatest Drop(Int32) 返回一个新DataFrame值,该值删除包含小于minNonNulls非 null 和非 NaN 值的行。 C# publicMicrosoft.Spark.Sql.DataFrameDrop(intminNonNulls); ...
If there is a case where we want to drop columns in the DataFrame, but we do not know the name of the columns still we can delete the column using its index position. Note: Column index starts from 0 (zero) and it goes till the last column whose index value will belen(df.columns)...
xs(key[, axis, level, drop_level]) #Returns a cross-section (row(s) or column(s)) from the Series/DataFrame. DataFrame.isin(values) #是否包含数据框中的元素 DataFrame.where(cond[, other, inplace,…]) #条件筛选 DataFrame.mask(cond[, other, inplace,…]) #Return an object of same ...