time seri from long to wide

I have a data frame like

date.	precipitation.
1950-01-01	2.5
1950-01-02	1.5
.	.
.	.
2021-12-30	1.5
2021-12-31	1

I want to have data frame like this :

year	month	1	2	.	.	30	31
1950	01	2.5	1.5	.	.	3	3.25
1950	02	2	1.7	.	.	3.1	3.5
.	.	.	.	.	.	.	.
.	.	.	.	.	.	.	.
2021	11	2.5	1.5	.	.	3	3.25
2021	12	2.3	1.67	.	.	1.7	1.5

I would appreciate it if some one could help me. thanks in advance

I extracted month, day, and year in separate columns and use pivot wider:

wide_table <- pivot_wider(df, names_from = day, values_from = value, names_prefix = "Day_", values_fill = NA)

but the result is not exactly the format that I want

Solution

For problems like this, split the date up into separate columns first, then use pivot_wider:

library(tidyverse)

data <- tibble(date = c('1950-01-01', '1950-01-02'),
               precip = c(2.5, 1.5))

data

date       precip
  <chr>       <dbl>
1 1950-01-01    2.5
2 1950-01-02    1.5

data.wide <- data %>% 
  mutate(date = as.Date(date),
         year = year(date),
         month = month(date),
         day = day(date)) %>% 
  select(-date) %>% 
  pivot_wider(names_from = day, values_from = precip)

data.wide

# A tibble: 1 × 4
   year month   `1`   `2`
  <dbl> <dbl> <dbl> <dbl>
1  1950     1   2.5   1.5

Also, this is a very common and standard problem that has many answers on both this website and others. It's worth developing your searching abilities, especially for usage of basic functions like pivot_wider(). And remember to include example data in your question, not a table, make it easy for your answerers!