很抱歉，如果这个问题相当简单
我是R的新手，我希望按组计算some_column列中缺失值的数量，这些值在我的数据集中替换为0值，然后获取具有该值的组最多0个值。这样做（使用包dplyr）：
missing_data <- group_by(some_data,some_group, count=sum(some_column==0))
但奇怪的是，我在count列中的整个数据集中都有相同的数字，就好像数据集没有分组一样。有人有想法
好的，我明白了
missing_data％＆gt;％group_by（some_group）％＆gt;％汇总（count = sum（some_column == 0））
答案 0 :(得分：1)
保持dplyr动词：
missing_data <- filter(some_data, some_column == 0) %>%
group_by(some_group) %>%
summarise(count = n()) %>%
arrange(desc(count))
答案 1 :(得分：0)
这是一个使用mtcars dataframe
的示例original output:
1 0 2 2 0 0 3 3 3 3 3 3 3 3 0
0 0 2 0 0 4 0 0 3 3 3 0 0 0 5
0 2 2 2 2 0 0 0 0 3 0 5 5 5 5
6 0 2 2 0 7 0 0 0 0 5 5 0 0 5
0 0 2 2 0 0 0 0 5 0 0 0 8 0 5
9 0 2 0 10 0 0 0 5 0 0 5 0 5 5
9 9 0 0 10 0 5 5 5 5 5 5 5 5 0
9 0 0 10 10 10 0 0 5 5 5 0 0 5 5
9 9 0 10 10 10 0 11 0 5 0 0 12 0 0
0 0 13 0 0 10 10 0 5 5 0 12 12 0 0
output that come:
1 0 2 2 0 0 3 3 3 3 3 3 3 3 0
0 0 2 0 0 4 0 0 3 3 3 0 0 0 5
0 2 2 2 2 0 0 0 0 3 0 5 5 5 5
6 0 2 2 0 7 0 0 0 0 5 5 0 0 5
0 0 2 2 0 0 0 0 5 0 0 0 9 0 5
10 0 2 0 11 0 0 0 5 0 0 5 0 5 5
10 10 0 0 11 0 5 5 5 5 5 5 5 5 0
10 0 0 11 11 11 0 0 5 5 5 0 0 5 5
10 10 0 11 11 11 0 12 0 5 0 0 13 0 0
0 0 14 0 0 11 11 0 5 5 0 13 13 0 0
package percolate;
public class Count
{
int i,j,count=0;
/*int[][] matrix = { {1,1,1,0,0,0,0,1,1},
{1,1,1,1,0,1,1,1,1},
{0,1,1,0,0,1,1,0,0},
{1,1,0,1,0,0,1,1,0},
{1,1,1,0,1,0,1,1,0},
{0,0,1,1,0,0,1,1,1},
{0,1,1,1,1,1,0,0,0},
{0,0,0,1,0,0,1,1,1},
{1,0,0,1,0,1,1,1,0}};*/
int[][] matrix = {
{1 ,0 ,1 ,1 ,0 ,0 ,1 ,1 ,1 ,1 ,1 ,1 ,1 ,1 ,0},
{0 ,0 ,1 ,0 ,0 ,1 ,0 ,0 ,1 ,1 ,1 ,0 ,0 ,0 ,1},
{0 ,1 ,1 ,1 ,1 ,0 ,0 ,0 ,0 ,1 ,0 ,1 ,1 ,1, 1},
{1 ,0 ,1 ,1 ,0 ,1 ,0 ,0 ,0 ,0 ,1 ,1, 0, 0, 1},
{0 ,0 ,1 ,1 ,0 ,0 ,0 ,0 ,1 ,0 ,0, 0, 1, 0, 1},
{1 ,0 ,1 ,0 ,1 ,0 ,0 ,0 ,1 ,0 ,0 ,1, 0 ,1, 1},
{1 ,1 ,0 ,0 ,1 ,0 ,1 ,1 ,1 ,1 ,1 ,1, 1 ,1 ,0},
{1 ,0 ,0 ,1 ,1 ,1 ,0 ,0 ,1 ,1 ,1 ,0, 0 ,1, 1},
{1 ,1 ,0 ,1 ,1 ,1 ,0 ,1 ,0 ,1 ,0 ,0 ,1, 0, 0},
{0 ,0 ,1 ,0 ,0 ,1 ,1 ,0 ,1 ,1 ,0 ,1, 1 ,0, 0},
};
int row =10,col =15;
int[][] label = new int [row][col];
private void operation(int i,int j)
{
// TODO Auto-generated method stub
if(i==0 && j==0)
{
count=count+1;
label[i][j]=count;
}
else if (((i-1)>=0) && j==0)
{
left(i,j);
}
else if (((j-1)>=0)&& i==0)
{
above(i,j);
}
else
{
aboveleft(i,j);
}
}
private void check()
{
// TODO Auto-generated method stub
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
if(matrix[i][j]==0)
{
label[i][j]=matrix[i][j];
}
else
{
operation(i,j);
}
}
}
}
private void left(int a,int b)
{
// TODO Auto-generated method stub
if(matrix[a-1][b]!=0)
{
label[a][b]=label[a-1][b];
}
else
{
count=count+1;
label[a][b]=count;
}
}
private void above(int a,int b)
{
// TODO Auto-generated method stub
if (matrix[a][b-1]!=0)
{
label[a][b]=label[a][b-1];
}
else
{
count=count+1;
label[a][b]=count;
}
}
private void aboveleft(int a,int b)
{
// TODO Auto-generated method stub
if (matrix[a][b-1]!=0 && matrix[a-1][b]==0)
{
label[a][b]=label[a][b-1];
}
else if (matrix[a-1][b]!=0 && matrix[a][b-1]==0)
{
label[a][b]=label[a-1][b];
}
else if (matrix[a][b-1]==0 && matrix[a-1][b]==0)
{
count=count+1;
label[a][b]=count;
}
else
{
checklabel(a, b);
}
}
private void checklabel(int a, int b)
{
// TODO Auto-generated method stub
if(label[a-1][b]>label[a][b-1])
{
label[a][b]=label[a][b-1];
int neww=label[a][b-1];
int old=label[a-1][b];
nonzero(old,neww);
count=count-1;
}
else if (label[a-1][b]==label[a][b-1])
{
label[a][b]=label[a-1][b];
}
else
{
label[a][b]=label[a-1][b];
int neww=label[a-1][b];
int old=label[a][b-1];
nonzero(old,neww);
count=count-1;
}
}
private void nonzero(int ol,int nw)
{
// TODO Auto-generated method stub
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
if (label[i][j]==ol)
{
label[i][j]=nw;
backtrace(i,j);
}
}
}
}
private void backtrace(int a,int b)
{
// TODO Auto-generated method stub
for (int i = a; i < row; i++)
{
for (int j = b; j < col; j++)
{
}
}
}
private void output()
{
// TODO Auto-generated method stub
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
System.out.print(label[i][j]+" ");
}
System.out.println();
}
}
public static void main(String[] args)
{
Count a=new Count();
a.check();
a.output();
}
}
答案 2 :(得分：0)
这里终于得到了答案
missing_data %>% group_by(some_group) %>% summarise(count=sum(some_column==0)) %>% arrange(desc(count))