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
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
可以对 DataFrame 的多列使用apply函数,并传递多个参数。 importpandasaspd# 创建DataFramedf=pd.DataFrame({'A':range(1,6),'B':range(10,15)})# 定义一个处理多列的函数defsum_columns(x,y,factor):return(x+y)*factor# 使用 apply 函数df['C']=df.apply(lambdarow:sum_columns(row['A'],row['B...
Python program to map a function using multiple columns in pandas# Importing pandas package import pandas as pd # Importing numpy package import numpy as np # Creating a dictionary d = { 'a':[1,2,3,4,5], 'b':[6,7,8,9,10], 'c':[11,12,13,14,15] } # Creating a DataFrame ...
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;) ...
import pandas as pd import numpy as np data = [(3,5,7), (2,4,6),(5,8,9)] df = pd.DataFrame(data, columns = ['A','B','C']) print(df) # Using Dataframe.apply() # To apply function to every row def add(row): return row[0]+row[1]+row[2] df['new_col'] = df...
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...
#apply()函数使用案例# # 导入 numpy 库 import numpy as np # 导入 pandas 库 import pandas as pd # 定义 DataFrame # 数据为 3 行 4 列 s_data = pd.DataFrame([[5.1,3.5,1.4,0.2], [6.1,3.7,4.1,1.5], [5.8,2.7,5.1,1.9]], columns=['feature_one','feature_two','feature_three','fea...
将apply()函数应用于Pandas中的多个列？尝试使用以下代码，它应该会给出与在combined列上运行上述函数时...