20,30],'C':['pandasdataframe.com','modify','columns']})# 定义一个函数,如果数值大于10,加10defadd_ten(x):returnx+10ifx>10elsex# 对'A'和'B'列应用条件函数df[['A','B']]=df[['A','B']].applymap(add_ten)print(df) Python Copy 示例4:对Da
示例代码 2: 使用 apply 返回多列 importpandasaspd# 创建一个 DataFramedf=pd.DataFrame({'A':range(1,6),'B':['pandasdataframe.com'for_inrange(5)]})# 定义一个函数,返回多个新的列值defmultiple_columns(row):returnpd.Series([row['A']*2,row['A']*3],index=['double','triple'])# 应用...
Pandas | Applying a function to Multiple columns: In this tutorial, we will learn how can we apply a function to multiple columns in a DataFrame with the help of example?ByPranit SharmaLast updated : April 19, 2023 How to Apply a Function to Multiple Columns of DataFrame?
In Pandas, the apply() function can indeed be used to return multiple columns by returning a pandas Series or DataFrame from the applied function. In this
return pd.DataFrame(array([[1,2]]), columns=['x1', 'x2']) df['size'].astype(int).apply(gimmeMultiple) df['size'].astype(int).apply(gimmeMultipleDf) 返回一个数据帧肯定有它的好处,但有时不是必需的。您可以查看apply()返回的内容,并对函数进行一些操作;) ...
代码语言:javascript 代码运行次数:0 运行 AI代码解释 Index(['a','b','c'],dtype='object')a b c 同时索引也有它的方法和属性。 查看DataFrame的常用属性 包含values、index、columns、ndim和shape。 Pandas索引操作 1.重建索引
运行apply函数,记录耗时: for col in md_data.columns: md_data[col] = md_data.apply(lambda x: apply_md5(x[col]), axis=1) 查看运行结果: 4. Pandarallel测试 Pandarallel特点: 非常简单实现Pandas并行; 没有自己的读取文件方式,依赖Pandas读取文件; 用户文档: 读取数据集,记录耗时: import pandas as...
# Groupby & multiple aggregations on different columns result = df.groupby('Courses').aggregate({'Duration':'count','Fee':['min','max']}) Pandas GroupBy Multiple Columns Example You can apply different aggregation functions to different columns in a singlegroupbyoperation using theagg()method....
现在,我们可以使用apply函数,将多列乘以同一列的数据。apply函数用于将一个函数应用于Pandas DataFrame的一行或一列数据。 sales['sales_pct']=sales[['sales','price','quantity']].apply(lambdarow:(row['sales']*row['price']*row['quantity'])/total_sales,axis=1) ...
Whenever we want to perform some operation on the entire DataFrame, we either use apply method. It is used on the grouped objects in pandas DataFrame. The apply() method Theapply()method passes the columns of each group in the form of a DataFrame inside the function which is describ...