如何找到R数据帧的列值的总和?
在本文中,我们将使用sum()函数在 R 中查找数据帧的列值的总和。
句法:
sum(dataframe$column_name)
创建数据框
可以使用 R 库中预定义的 data.frame()函数创建数据帧。此函数接受要创建的数据框所需的元素以及行数和列数。
以下是用于创建数据框的 R 程序:
R
# R Program to create a dataframe
# Creating a Data Frame
df<-data.frame(row1 = 0:2, row2 = 3:5, row3 = 6:8)
print(df)
R
# Computing sum of column values
# Using sum() function
sum(df$row1)
sum(df$row2)
R
# R program to illustrate dataframe
Roll_num = c(01, 02, 03)
Age = c(22, 25, 45)
Marks = c(70, 80, 90)
# To create dataframe use data.frame command and
# then pass each of the vectors
# we have created as arguments
# to the function data.frame()
df = data.frame(Roll_num, Age, Marks)
print(df)
# Computing Sum using sum() function
sum(df$Roll_num)
sum(df$Age)
sum(df$Marks)
R
# R program to illustrate dataframe
ID = c(01, 02, 03)
Age = c(25, 30, 70)
Salary = c(70000, 85000, 40000)
# To create dataframe use data.frame command and
# then pass each of the vectors
# we have created as arguments
# to the function data.frame()
df = data.frame(ID, Age, Salary)
# Computing total salary
cat("Total Salary =", sum(df$Salary))
输出:
row1 row2 row3
1 0 3 6
2 1 4 7
3 2 5 8
计算列值的总和
R 语言提供了一个内置函数sum()来计算数据帧的平均值。以下是用于实现sum()的 R 程序。
电阻
# Computing sum of column values
# Using sum() function
sum(df$row1)
sum(df$row2)
输出:
3
12
示例 2:
电阻
# R program to illustrate dataframe
Roll_num = c(01, 02, 03)
Age = c(22, 25, 45)
Marks = c(70, 80, 90)
# To create dataframe use data.frame command and
# then pass each of the vectors
# we have created as arguments
# to the function data.frame()
df = data.frame(Roll_num, Age, Marks)
print(df)
# Computing Sum using sum() function
sum(df$Roll_num)
sum(df$Age)
sum(df$Marks)
输出:
6
92
240
示例 3:
电阻
# R program to illustrate dataframe
ID = c(01, 02, 03)
Age = c(25, 30, 70)
Salary = c(70000, 85000, 40000)
# To create dataframe use data.frame command and
# then pass each of the vectors
# we have created as arguments
# to the function data.frame()
df = data.frame(ID, Age, Salary)
# Computing total salary
cat("Total Salary =", sum(df$Salary))
输出:
195000