DataFrame - sort_values() function The sort_values() function is used to sort by the values along either axis. Syntax: DataFrame.sort_values(self, by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last') Parameters: Returns:sorted_obj - DataFrame or None DataFram...
sort_values的调用与这个代数运算符的行为相同。sort_index操作符按照行(列是轴=1)标签的列序进行排序。sort_by代数运算符不与数据的行或列标签交互,所以必须在sort_by运算符之前调用from_labels运算符,将标签移到数据中,以便按照这些标签的值进行排序。在排序之后,to_labels可以将列移回标签中,从而保证与pandas的...
df.sort_values(by='Alpha', ascending=True, inplace=True)print(df) 输出结果: Alpha BravoFirst 2 5Second 3 6 6. sort_index方法 用处:根据轴标签进行排序。 语法规范:DataFrame.sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_...
DataFrame.sort_values(by[, axis, ascending]) #Sort by the values along either axis DataFrame.sort_index([axis, level, …]) #Sort object by labels (along an axis) DataFrame.nlargest(n, columns[, keep]) #Get the rows of a DataFrame sorted by the n largest values of columns. DataFrame....
DataFrame.combine_first(other)Combine two DataFrame objects and default to non-null values in frame calling the method. 函数应用&分组&窗口 方法描述 DataFrame.apply(func[, axis, broadcast, …])应用函数 DataFrame.applymap(func)Apply a function to a DataFrame that is intended to operate elementwise...
DataFrame.sort_values(by[, axis, ascending, …]) Sort by the values along either axis DataFrame.sort_index([axis, level, …]) Sort object by labels (along an axis) DataFrame.nlargest(n, columns[, keep]) Get the rows of a DataFrame sorted by the n largest values of columns. ...
ascending = df.sort_values('Student') 1. 化学分数按降序排列 descending = df.sort_values('Chemistry',ascending=False) 1. 更复杂一点的,我们希望按物理分数的升序排序,然后按化学分数的降序排序。 df.sort_values(['Physics','Chemistry'],ascending=[True,False]) ...
pivot(index="foo", columns="bar", values="N", aggregate_function="first") .lazy() ) out = q.collect() print(out) Melts 代码语言:javascript 代码运行次数:0 运行 AI代码解释 import polars as pl df = pl.DataFrame( { "A": ["a", "b", "a"], "B": [1, 3, 5], "C": [...
nsmallest() Sort the DataFrame by the specified columns, ascending, and return the specified number of rows nunique() Returns the number of unique values in the specified axis pct_change() Returns the percentage change between the previous and the current value pipe() Apply a function to the...
# spark排序color_df.sort('color',ascending=False).show()# pandas的排序df.sort_values(by='b') (2)多字段排序 color_df.filter(color_df['length']>=4) .sort('length','color', ascending=False).show() (3)混合排序 color_df.sort(color_df.length.desc(),color_df.color.asc()) ...