The following uses skimr::skim()
to describe the data. Remember we created the skim output object in the R script. We just report it here.
Name | esoData |
Number of rows | 201022 |
Number of columns | 34 |
_______________________ | |
Column type frequency: | |
character | 1 |
factor | 1 |
numeric | 31 |
POSIXct | 1 |
________________________ | |
Group variables | None |
Variable type: character
skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
---|---|---|---|---|---|---|---|
DATETIME | 0 | 1 | 19 | 19 | 0 | 201022 | 0 |
Variable type: factor
skim_variable | n_missing | complete_rate | ordered | n_unique | top_counts |
---|---|---|---|---|---|
weekDay | 0 | 1 | TRUE | 7 | Thu: 28752, Fri: 28750, Sun: 28704, Mon: 28704 |
Variable type: numeric
skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
---|---|---|---|---|---|---|---|---|---|---|
GAS | 0 | 1 | 12753.47 | 5269.71 | 1556.0 | 8635.0 | 12880.0 | 16852.0 | 27472.0 | ▃▆▇▅▁ |
COAL | 0 | 1 | 8082.35 | 6590.29 | 0.0 | 1613.0 | 7172.0 | 13421.0 | 26044.0 | ▇▃▅▂▁ |
NUCLEAR | 0 | 1 | 7101.74 | 1041.41 | 3705.0 | 6405.0 | 7256.0 | 7896.0 | 9342.0 | ▁▂▆▇▃ |
WIND | 0 | 1 | 3220.80 | 3180.72 | 0.0 | 809.0 | 2172.0 | 4728.0 | 17129.0 | ▇▃▁▁▁ |
HYDRO | 0 | 1 | 396.56 | 246.11 | 0.0 | 192.0 | 366.0 | 565.0 | 1403.0 | ▇▇▅▁▁ |
IMPORTS | 0 | 1 | 1981.60 | 1099.72 | 0.0 | 1168.0 | 2018.0 | 2944.0 | 4884.0 | ▅▅▇▆▁ |
BIOMASS | 0 | 1 | 442.48 | 863.09 | 0.0 | 0.0 | 0.0 | 0.0 | 3204.0 | ▇▁▁▁▁ |
OTHER | 0 | 1 | 529.97 | 682.21 | 0.0 | 0.0 | 121.0 | 834.0 | 2456.0 | ▇▂▂▁▁ |
SOLAR | 0 | 1 | 642.51 | 1458.01 | 0.0 | 0.0 | 0.0 | 367.0 | 9680.0 | ▇▁▁▁▁ |
STORAGE | 0 | 1 | 310.04 | 348.86 | 0.0 | 0.0 | 294.0 | 452.0 | 2660.0 | ▇▂▁▁▁ |
GENERATION | 0 | 1 | 35461.52 | 7444.52 | 18287.0 | 29708.0 | 35384.0 | 40624.0 | 59512.0 | ▃▇▇▃▁ |
CARBON_INTENSITY | 0 | 1 | 388.69 | 139.73 | 54.0 | 264.0 | 403.0 | 508.0 | 695.0 | ▂▆▆▇▂ |
LOW_CARBON | 0 | 1 | 11804.09 | 4086.59 | 4626.0 | 8802.0 | 10737.0 | 14064.0 | 30746.0 | ▇▇▃▁▁ |
ZERO_CARBON | 0 | 1 | 11361.61 | 3636.51 | 4626.0 | 8698.0 | 10466.0 | 13459.0 | 28473.0 | ▇▇▃▁▁ |
RENEWABLE | 0 | 1 | 4259.87 | 3741.31 | 0.0 | 1284.0 | 3136.0 | 6271.0 | 23118.0 | ▇▃▁▁▁ |
FOSSIL | 0 | 1 | 20835.82 | 8809.41 | 2421.0 | 14126.0 | 20129.0 | 27086.0 | 49096.0 | ▃▇▆▃▁ |
GAS_perc | 0 | 1 | 35.54 | 12.23 | 5.0 | 26.5 | 36.4 | 45.0 | 70.1 | ▂▆▇▆▁ |
COAL_perc | 0 | 1 | 21.39 | 15.91 | 0.0 | 4.8 | 21.0 | 35.6 | 60.6 | ▇▅▅▅▁ |
NUCLEAR_perc | 0 | 1 | 20.88 | 5.24 | 9.2 | 17.0 | 20.1 | 24.0 | 43.1 | ▃▇▃▁▁ |
WIND_perc | 0 | 1 | 9.57 | 9.77 | 0.0 | 2.3 | 6.3 | 13.8 | 58.3 | ▇▂▁▁▁ |
HYDRO_perc | 0 | 1 | 1.10 | 0.64 | 0.0 | 0.6 | 1.0 | 1.5 | 4.2 | ▇▇▃▁▁ |
IMPORTS_perc | 0 | 1 | 6.01 | 3.64 | 0.0 | 3.2 | 6.2 | 8.6 | 18.9 | ▆▇▆▂▁ |
BIOMASS_perc | 0 | 1 | 1.37 | 2.71 | 0.0 | 0.0 | 0.0 | 0.0 | 16.1 | ▇▁▁▁▁ |
OTHER_perc | 0 | 1 | 1.58 | 2.11 | 0.0 | 0.0 | 0.4 | 2.6 | 10.5 | ▇▂▁▁▁ |
SOLAR_perc | 0 | 1 | 1.79 | 4.16 | 0.0 | 0.0 | 0.0 | 1.0 | 32.8 | ▇▁▁▁▁ |
STORAGE_perc | 0 | 1 | 0.78 | 0.84 | 0.0 | 0.0 | 0.7 | 1.2 | 7.9 | ▇▁▁▁▁ |
GENERATION_perc | 0 | 1 | 100.00 | 0.00 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | ▁▁▇▁▁ |
LOW_CARBON_perc | 0 | 1 | 34.70 | 13.69 | 10.7 | 24.2 | 31.8 | 42.5 | 87.9 | ▆▇▃▁▁ |
ZERO_CARBON_perc | 0 | 1 | 33.33 | 12.27 | 10.7 | 24.0 | 31.1 | 40.3 | 85.1 | ▆▇▃▁▁ |
RENEWABLE_perc | 0 | 1 | 12.46 | 11.16 | 0.0 | 3.6 | 9.0 | 18.2 | 66.2 | ▇▃▁▁▁ |
FOSSIL_perc | 0 | 1 | 56.93 | 16.19 | 9.0 | 45.9 | 58.7 | 70.1 | 88.0 | ▁▃▆▇▅ |
Variable type: POSIXct
skim_variable | n_missing | complete_rate | min | max | median | n_unique |
---|---|---|---|---|---|---|
rDateTime | 0 | 1 | 2009-01-01 | 2020-06-19 22:30:00 | 2014-09-25 23:15:00 | 201022 |
There’s quite a lot of data…
1.1 plots every data point in the data (!). Remember we created the plot output object in the R script. We just print it here.
Figure 1.1: Half-hourly generation (GW)
Report generated in 142.29 seconds ( 2.37 minutes) using knitr in RStudio with R version 3.6.3 (2020-02-29) running on x86_64-apple-darwin15.6.0.
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Catalina 10.15.5
##
## Matrix products: default
## BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_NZ.UTF-8/en_NZ.UTF-8/en_NZ.UTF-8/C/en_NZ.UTF-8/en_NZ.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] skimr_2.1 ggplot2_3.3.0 lubridate_1.7.4 here_0.1
## [5] drake_7.11.0 data.table_1.12.8 woRkflow_0.1.0
##
## loaded via a namespace (and not attached):
## [1] storr_1.2.1 progress_1.2.2 tidyselect_1.0.0 xfun_0.12
## [5] repr_1.1.0 purrr_0.3.3 colorspace_1.4-1 vctrs_0.2.4
## [9] viridisLite_0.3.0 htmltools_0.4.0 yaml_2.2.1 base64enc_0.1-3
## [13] utf8_1.1.4 rlang_0.4.5 pillar_1.4.3 txtq_0.2.0
## [17] glue_1.3.2 withr_2.1.2 lifecycle_0.2.0 stringr_1.4.0
## [21] munsell_0.5.0 gtable_0.3.0 evaluate_0.14 labeling_0.3
## [25] knitr_1.28 parallel_3.6.3 fansi_0.4.1 highr_0.8
## [29] Rcpp_1.0.4 scales_1.1.0 backports_1.1.5 filelock_1.0.2
## [33] jsonlite_1.6.1 farver_2.0.3 hms_0.5.3 packrat_0.5.0
## [37] digest_0.6.25 stringi_1.4.6 bookdown_0.18 dplyr_0.8.5
## [41] grid_3.6.3 rprojroot_1.3-2 cli_2.0.2 tools_3.6.3
## [45] magrittr_1.5 base64url_1.4 tibble_2.1.3 crayon_1.3.4
## [49] tidyr_1.0.2 pkgconfig_2.0.3 prettyunits_1.1.1 rmarkdown_2.1
## [53] assertthat_0.2.1 rstudioapi_0.11 R6_2.4.1 igraph_1.2.5
## [57] compiler_3.6.3
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