miss_count: Count missing values in all columns and calculate the...
In UBC-MDS/slimreda: Exploratory Data Analysis
Description
Usage
Arguments
Value
Examples
Description
Count missing values in all columns and calculate the percentage
Usage
1
miss_count(df, ascending = FALSE)
Arguments
df
A dataframe of type data.frame
ascending
A boolean value to decide whether the df is sorted ascending or decending
Value
A dataframe with thee columns: column,counts and percentage
Examples
1
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3
4
5
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7
mydf <- data.frame(
name = c("Amy","Tony","Jessica"),
age = c(18,21,30),
hobby = c("lab","quiz","swim")
)
miss_value <- miss_count(mydf,ascending = FALSE)
miss_value
UBC-MDS/slimreda documentation built on Feb. 7, 2022, 9:12 a.m.
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Description Usage Arguments Value Examples
Description
Count missing values in all columns and calculate the percentage
Usage
1 | miss_count(df, ascending = FALSE)
|
Arguments
df |
A dataframe of type data.frame |
ascending |
A boolean value to decide whether the df is sorted ascending or decending |
Value
A dataframe with thee columns: column,counts and percentage
Examples
1 2 3 4 5 6 7 | mydf <- data.frame(
name = c("Amy","Tony","Jessica"),
age = c(18,21,30),
hobby = c("lab","quiz","swim")
)
miss_value <- miss_count(mydf,ascending = FALSE)
miss_value
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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