9.8 Selecting Rows
20200419 Rows from a data frame can be dplyr::filter()’ed using specific conditions. The rows in the resulting data frame will be those for which the condition is true.
## # A tibble: 127,657 × 24
## date location min_temp max_temp rainfall evaporation sunshine
## <date> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2008-12-02 Albury 7.4 25.1 0 NA NA
## 2 2008-12-03 Albury 12.9 25.7 0 NA NA
## 3 2008-12-04 Albury 9.2 28 0 NA NA
## 4 2008-12-05 Albury 17.5 32.3 1 NA NA
## 5 2008-12-06 Albury 14.6 29.7 0.2 NA NA
## 6 2008-12-07 Albury 14.3 25 0 NA NA
## 7 2008-12-08 Albury 7.7 26.7 0 NA NA
## 8 2008-12-09 Albury 9.7 31.9 0 NA NA
## 9 2008-12-10 Albury 13.1 30.1 1.4 NA NA
## 10 2008-12-11 Albury 13.4 30.4 0 NA NA
## # ℹ 127,647 more rows
## # ℹ 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 <int>, humidity_3pm <int>,
## # pressure_9am <dbl>, pressure_3pm <dbl>, cloud_9am <int>, cloud_3pm <int>,
## # temp_9am <dbl>, temp_3pm <dbl>, rain_today <fct>, risk_mm <dbl>,
## # rain_tomorrow <fct>To select rows that have missing values, for example, use dplyr::filter() with purrr::pmap_lgl() to map base::is.na() for base::any() column in the row. In the following example we count the number with missing values using base::nrow(), formatted nicely using scales::comma():
ds %>%
select(-date) %>%
filter(purrr::pmap_lgl(., ~any(is.na(c(...))))) %>%
nrow() %>% scales::comma() %>% cat("rows have missing values.\n")## 196,937 rows have missing values.If you find this curated material useful then you can consider a donation to support it's ongoing availability and give you access to the PDF version of this book. The material has been scoped up by Generative AI without permission or any kind of recompense so do consider a donation if you can afford it. Unlike Generative AI your access to this materials is freely given. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Togaware has a 30 year tradition of making popular open source software which includes sold privacy preserving productivity apps, rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0
