Count Observations Greater Than a Particular Value

Count observations greater than a particular value

Try using logical test and then sum over the values meeting the condition

sum(output$V4 > 2000)

counting observations greater than 20 in R

The data is character in this dataframe and not numeric. When numbers are characters weird things happen.

"2" > "13"
#[1] TRUE

Change the data to numeric before using sum.

df[-1] <- lapply(df[-1], as.numeric)
sum(df[,-1] > 20, na.rm=TRUE)
#[1] 8

tidyverse: finding number of observations greater than multiple values

You can use summarize directly:

dt1 %>% 
  summarise(X1 = sum(X >= 5),
            X2 = sum(X >= 7))

# A tibble: 1 x 2
     X1    X2
  <int> <int>
1     6     4

Count observations with certain value in a group?

df <- df %>%
  group_by(Year, Month) %>%
  mutate(XGreaterThanYCount = sum(X > Y))

number of values in a list greater than a certain number

You could do something like this:

>>> j = [4, 5, 6, 7, 1, 3, 7, 5]
>>> sum(i > 5 for i in j)
3

It might initially seem strange to add True to True this way, but I don't think it's unpythonic; after all, bool is a subclass of int in all versions since 2.3:

>>> issubclass(bool, int)
True

How to determine how many entries exceed a certain value

If df is your dataset:

df[df$cumula > 3000,]

will give you the entries that exceed 3000.

If you only need to count how many, you can do

sum(df$cumula > 3000)

counting the number of values greater than 0 in R in multiple columns

We can use

colSums(myDF[c("L2", "L3", "L4")] > 0)

How to count observations matching the values of a vector of characters

To count matching or non-matching elements, you can use

num_foods <- nrow(mydf[!str_detect(mydf$Product, non.food),])
num_non_foods <- nrow(mydf[str_detect(mydf$Product, non.food),])

You can see, that num_foods == 8 and num_non_foods == 8, so your code seems to do what it should.

data

mydf <- structure(list(id = 1:16, Product = c("Pizza", "Cleaning Product", 
"Chocolate", "Fruit", "Red Meat", "Cleaning Product", "Bracelet", 
"Trucker Hat", "Shirt", "Shirt", "Chicken Breast", "Chocolate", 
"Cereal", "Fruit", "Cleaning Product", "Trucker Hat"), price = c(2, 
3.5, 1, 1, 2.5, 3.5, 3, 5, 15, 20, 2.5, 1, 2, 1, 3.5, 4), place = c("Supermarket", 
"Supermarket", "Supermarket", "Little Store", "Supermarket", 
"Supermarket", "Little Store", "Gas Station", "Supermarket", 
"Supermarket", "Little Store", "Gas Station", "Gas Station", 
"Little Store", "Supermarket", "Supermarket")), row.names = c(NA, 
-16L), class = "data.frame")

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