How to Solve R Error as.Date.numeric(x) : ‘origin’ must be supplied

This error occurs when you try to convert a number to a date without providing an origin date. You can solve this error by providing a date as an origin argument to the as.Date function. For example,

as.Date(34291, origin = "1900-01-01")

This tutorial will go through the error in detail and how to solve it with code examples.

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Example

Let’s look at an example of reproducing the error.

# Data frame containing water level of man made pond in cms after n days from creating

df <- data.frame(days_after=c(14, 80, 40, 350),
                 water_level=c(30, 20, 89,  50))

# Print structure of the data frame

str(df)

The str() function returns the structure of the data frame and informs us of the data type in each column:

'data.frame':	4 obs. of  2 variables:
 $ days_after : num  14 80 40 350
 $ water_level: num  30 20 89 50

Both the days_after and water_level columns are numeric. We can use the as.Date method to convert the days_after column to date format.

df$days_after <- as.Date(df$days_after)

Let’s run the code to see what happens:

Error in as.Date.numeric(df$days_after) : 'origin' must be supplied

The error occurred because we did not specify an origin argument for the as.Date method.

If you pass a numeric argument for x to the as.Date method, R interprets x as the number of days since a specified origin.

Solution

We can solve the error by specifying an origin. The origin must be a Date object or something that can be coerced by as.Date(origin, _) to a Date object.

Let’s look at the revised code:

df$days_after <- as.Date(df$days_after, origin="2007-07-04")
df

Let’s run the code to get the result:

 days_after water_level
1 2007-07-18          30
2 2007-09-22          20
3 2007-08-13          89
4 2008-06-18          50

[1] "Date"

When we provide an origin date, the R interpreter converts the numeric values to dates by adding the number of days in the days_after column to the origin. For example,

• The first row of the days_after column is 14 and the date 2007-07-18 is 14 days after 2007-07-04
• The second row of the days_after column is 80 and the date 2007-09-22 is 80 days after 2007-07-04

We can confirm that the days_after column has the class Date using the class() function:

class(df$days_after)

[1] "Date"

Summary

Congratulations on reading to the end of this tutorial!

For further reading on R-related errors, go to the articles: 

• How to solve R Error in xj[i] : invalid subscript type ‘list’
• How to Solve R Error: Arguments imply differing number of rows
• How to Solve R Error: contrasts can be applied only to factors with 2 or more levels
• How to Solve R Error: Incorrect number of dimensions

Go to the online courses page on R to learn more about coding in R for data science and machine learning.

Have fun and happy researching!