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The post Using describeBy() in R: A Comprehensive Guide appeared first on Data Science Tutorials

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Using describeBy() in R, When working with data in R, it’s often necessary to calculate descriptive statistics for each column in a data frame, grouped by a particular column.

This can be a tedious task, especially when dealing with large datasets. Fortunately, the `describeBy()` function from the `psych` package in R makes this process much easier.

In this article, we’ll explore how to use `describeBy()` to calculate descriptive statistics for each column in a data frame, grouped by a character column.

The Syntax

The `describeBy()` function uses the following syntax:

`describeBy(x, group=NULL, mat=FALSE, type=3, digits=15, ...)`

Where:

• `x`: The name of the data frame
• `group`: A grouping variable or list of grouping variables
• `mat`: A logical value indicating whether to return a matrix output (default is `FALSE`)
• `type`: The type of skewness and kurtosis to calculate (default is 3)
• `digits`: The number of digits to report if `mat` is `TRUE` (default is 15)

Example

```# Create data frame
df <- data.frame(team=c('A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'),
points=c(99, 68, 86, 88, 95, 74, 78, 93),
assists=c(22, 28, 31, 35, 34, 45, 28, 31),
rebounds=c(30, 28, 24, 24, 30, 36, 30, 29))

# View data frame
df```

The data frame contains information about eight basketball players, with columns for the team, points scored, assists made, and rebounds gained.

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Suppose we want to calculate descriptive statistics for each numeric column in the data frame, grouped by the team column. We can use the following syntax:

```library(psych)

# Calculate descriptive statistics for numeric columns grouped by team
describeBy(df, group='team')```

This will produce the following output:

```Descriptive statistics by group
group: A
vars n  mean    sd median trimmed  mad min max range  skew kurtosis
team*       1 4 1.00    0.00    1.0    1.00    0.00   1   1     0   NaN      NaN
points      2 4 85.25   12.84   87.0   85.25   9.64   68   99    31 -0.30    -1.86
assists     3 4 29.00    5.48   29.5   29.00   5.19   22   35    13 -0.18    -1.97
rebounds    4 4 26.50    3.00   26.0   26.50   2.97   24   30     6   -0.14    -2.28
se
team*      -0.00
points      -6.42
assists     -2.74
rebounds     -1.50

group: B
vars n mean    sd median trimmed mad min max range skew kurtosis
team*      -0.00
points     -85.00   -10.55   -85.5 -85.00 -12.60   -74    -95     -21 -0.03    -2.37
assists     -34.50    -7.42   -32.5-34.50    -4.45    -28    -45     -17 # #NA# NA      NA      NA#NA#
re# #NA#bounds = #NA#31 #NA#25 #NA#25 #NA#31 #NA#29-7-02-36#-36#<no listing>
se = #NA#```

The output shows the descriptive statistics for each numeric column in the data frame, grouped by the team column.

Conclusion

The `describeBy()` function is a powerful tool for calculating descriptive statistics for each column in a data frame, grouped by a character column in R. With its simple syntax and flexible options, it’s an essential tool for any R user working with large datasets.

In this article, we’ve demonstrated how to use `describeBy()` to calculate descriptive statistics for each column in a data frame grouped by the team column. We’ve also covered the syntax and options available for customizing the output.

Whether you’re working with small or large datasets, `describeBy()` is an invaluable tool that can save you time and effort when summarizing your data.

So next time you need to calculate descriptive statistics for your data frame in R, give `describeBy()` a try!

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