10.16 Replacing Missing Values
20201026 See Section 10.11 to impute (guess) values to replace missing values.
To replace missing values (NA) in a data set with a specific
default value, like 0 for numeric data, we can use
tidyr::replace_na() within a pipeline. In the following
example only the numeric columns of the dataset are considered
dplyr::across() the dataset, by checking
tidyselect::where() the data base::is.numeric().
ds %>%
mutate(across(where(is.numeric), ~replace_na(.x, 0)))## # A tibble: 176,747 × 24
## date location min_temp max_temp rainfall evaporation sunshine
## <date> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2008-12-01 Albury 13.4 22.9 0.6 4.8 8.5
## 2 2008-12-02 Albury 7.4 25.1 0 4.8 8.5
## 3 2008-12-03 Albury 12.9 25.7 0 4.8 8.5
## 4 2008-12-04 Albury 9.2 28 0 4.8 8.5
## 5 2008-12-05 Albury 17.5 32.3 1 4.8 8.5
## 6 2008-12-06 Albury 14.6 29.7 0.2 4.8 8.5
## 7 2008-12-07 Albury 14.3 25 0 4.8 8.5
## 8 2008-12-08 Albury 7.7 26.7 0 4.8 8.5
## 9 2008-12-09 Albury 9.7 31.9 0 4.8 8.5
## 10 2008-12-10 Albury 13.1 30.1 1.4 4.8 8.5
## # … with 176,737 more rows, and 17 more variables: wind_gust_dir <ord>,
## # wind_gust_speed <dbl>, wind_dir_9am <ord>, wind_dir_3pm <ord>,
## # wind_speed_9am <dbl>, wind_speed_3pm <dbl>, humidity_9am <dbl>,
## # humidity_3pm <dbl>, pressure_9am <dbl>, pressure_3pm <dbl>,
## # cloud_9am <dbl>, cloud_3pm <dbl>, temp_9am <dbl>, temp_3pm <dbl>,
## # rain_today <fct>, risk_mm <dbl>, rain_tomorrow <fct>Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0
