README.md
In Avsamoht/rmo: data store for air quality measurements
rmo: data store for air quality measurements
rmo reads exports from AIRMO in CSV or DAT format and saves the data as rds files.
The data is split in chunks grouped by year, site and zeitfenster.
Provides utility function to convert the data into a compatible format for openair.
Installation
require(devtools)
install_github('Avsamoht/rmo')
Brief examples
rmo long format
str(df)
## 'data.frame': 312183 obs. of 6 variables:
## $ startzeit : POSIXct, format: "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" ...
## $ airmo_kurzname: Factor w/ 2 levels "Zch_Schimmelstrasse",..: 1 1 1 2 2 2 1 1 1 2 ...
## $ parameter : Factor w/ 3 levels "NO","NOx","O3": 2 1 3 2 1 3 2 1 3 2 ...
## $ zeitfenster : Factor w/ 1 level "min30": 1 1 1 1 1 1 1 1 1 1 ...
## $ einheit : Factor w/ 2 levels "µg/m3","ppb": 2 1 1 2 1 1 2 1 1 2 ...
## $ value : num 89.58 76.74 1.59 75.4 63.81 ...
head(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2014-01-01 Zch_Schimmelstrasse NOx min30 ppb 89.58
## 2 2014-01-01 Zch_Schimmelstrasse NO min30 µg/m3 76.74
## 3 2014-01-01 Zch_Schimmelstrasse O3 min30 µg/m3 1.59
## 4 2014-01-01 Zch_Stampfenbachstrasse NOx min30 ppb 75.40
## 5 2014-01-01 Zch_Stampfenbachstrasse NO min30 µg/m3 63.81
## 6 2014-01-01 Zch_Stampfenbachstrasse O3 min30 µg/m3 1.74
read an export file from AIRMO and save it in the store
library(rmo)
# DAT format
df <- read_airmo_dat("O:/060_R/import_airmo/dat/wied_jahr_m30.dat")
rds_save_data(df, "rds")
# CSV format
df <- read_airmo_csv("O:/060_R/import_airmo/STA_data_2013_2015.csv")
rds_save_data(df, "rds")
# optional specify a file encoding, time zone and a time shift (eg. for converting end time to start time)
fn <- "O:/060_R/import_airmo/dat/wied_jahr_m30.dat"
df <- read_airmo_dat(fn, encoding = "cp1252", tz = "Etc/GMT-1",
time_shift = lubridate::minutes(-30))
load data from the store
sites <- c("Zch_Stampfenbachstrasse", "Zch_Schimmelstrasse")
df <- rds_load_data(sites, "min30", 2014:2017, c("NO", "NOx", "O3"), "rds")
str(df)
## 'data.frame': 312189 obs. of 6 variables:
## $ startzeit : POSIXct, format: "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" ...
## $ airmo_kurzname: Factor w/ 2 levels "Zch_Schimmelstrasse",..: 1 1 1 2 2 2 1 1 1 2 ...
## $ parameter : Factor w/ 3 levels "NO","NOx","O3": 2 1 3 2 1 3 2 1 3 2 ...
## $ zeitfenster : Factor w/ 1 level "min30": 1 1 1 1 1 1 1 1 1 1 ...
## $ einheit : Factor w/ 2 levels "µg/m3","ppb": 2 1 1 2 1 1 2 1 1 2 ...
## $ value : num 89.58 76.74 1.59 75.4 63.81 ...
head(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2014-01-01 Zch_Schimmelstrasse NOx min30 ppb 89.58
## 2 2014-01-01 Zch_Schimmelstrasse NO min30 µg/m3 76.74
## 3 2014-01-01 Zch_Schimmelstrasse O3 min30 µg/m3 1.59
## 4 2014-01-01 Zch_Stampfenbachstrasse NOx min30 ppb 75.40
## 5 2014-01-01 Zch_Stampfenbachstrasse NO min30 µg/m3 63.81
## 6 2014-01-01 Zch_Stampfenbachstrasse O3 min30 µg/m3 1.74
tail(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 312184 2017-12-31 23:30:00 Zch_Schimmelstrasse NO min30 µg/m3 1.415176
## 312185 2017-12-31 23:30:00 Zch_Schimmelstrasse NOx min30 ppb 5.711500
## 312186 2017-12-31 23:30:00 Zch_Schimmelstrasse O3 min30 µg/m3 54.884442
## 312187 2017-12-31 23:30:00 Zch_Stampfenbachstrasse NO min30 µg/m3 1.045155
## 312188 2017-12-31 23:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 6.752600
## 312189 2017-12-31 23:30:00 Zch_Stampfenbachstrasse O3 min30 µg/m3 52.877472
# all parameter for a station (set parameters = NULL)
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2014:2017, base_path="rds")
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2014:2017, NULL, "rds")
utility functions
merge_rmo_longformat
Merge two rmo dataframes
# Mergin: missing values (NA) in y will be replaced with the values from x
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2017, "NOx", base_path="rds")
x <- df[1:5,]
y <- df[3:7,]
y$value <- y$value * 2
xy <- merge_rmo_longformat(x, y)
print(x)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 30.437
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 35.397
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.928
print(y)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 60.874
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 70.794
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 55.856
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 59.332
## 7 2017-01-01 03:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 58.624
print(xy)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 60.874
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 70.794
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 55.856
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 59.332
## 7 2017-01-01 03:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 58.624
rmo_to_openair
library(openair)
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2017, NULL, "rds")
td <- rmo_to_openair(df)
head(td)
## date site zeitfenster co no no2 nox
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse min30 0.3642325 9.362537 38.56268 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse min30 0.3620788 9.481529 36.85615 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse min30 0.3663280 12.429375 39.14822 30.437
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse min30 0.3693082 18.150572 39.86169 35.397
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse min30 0.3642325 10.406644 37.45144 27.928
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse min30 0.3643955 11.167741 39.60812 29.666
## o3 pm1.0f_roh pm10 pm25 pn so2 wd ws
## 1 1.4207791 NA 76.37508 NA 16254 3.349949 296.15 1.31050
## 2 1.4741852 NA 135.38172 NA 15579 3.114319 288.27 1.41930
## 3 1.4191033 NA 94.85740 NA 12497 1.998468 301.20 1.20090
## 4 1.2726902 NA 77.34658 NA 12020 1.967742 291.53 1.01940
## 5 1.2167305 NA 78.60730 NA 10350 1.813478 286.61 1.12830
## 6 0.8141794 NA 77.15706 NA 10742 1.791059 271.17 0.61363
summaryPlot(td)
# optional add an id column and rename some parameters
site_ids <- list("Zch_Schimmelstrasse"="Wied", "Zch_Stampfenbachstrasse"="Staba")
df <- rds_load_data(names(site_ids), "min30", 2017, c("NOx", "O3", "PM2.5", "WD"), "rds")
parameter_names <- list("O3"="O3_renamed")
td <- rmo_to_openair(df, site_ids, parameter_names)
head(td)
## date site zeitfenster nox o3_renamed pm25 wd id
## 1 2017-01-01 00:30:00 Zch_Schimmelstrasse min30 49.573 1.432410 69.07397 336.86 Wied
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse min30 27.672 1.420779 NA 296.15 Staba
## 3 2017-01-01 01:00:00 Zch_Schimmelstrasse min30 57.428 1.428300 72.01043 338.13 Wied
## 4 2017-01-01 01:00:00 Zch_Stampfenbachstrasse min30 26.875 1.474185 NA 288.27 Staba
## 5 2017-01-01 01:30:00 Zch_Schimmelstrasse min30 72.514 1.479951 65.96797 340.56 Wied
## 6 2017-01-01 01:30:00 Zch_Stampfenbachstrasse min30 30.437 1.419103 NA 301.20 Staba
Avsamoht/rmo documentation built on May 22, 2019, 1:46 p.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
rmo: data store for air quality measurements
rmo reads exports from AIRMO in CSV or DAT format and saves the data as rds files. The data is split in chunks grouped by year, site and zeitfenster. Provides utility function to convert the data into a compatible format for openair.
Installation
require(devtools)
install_github('Avsamoht/rmo')
Brief examples
rmo long format
str(df)
## 'data.frame': 312183 obs. of 6 variables:
## $ startzeit : POSIXct, format: "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" ...
## $ airmo_kurzname: Factor w/ 2 levels "Zch_Schimmelstrasse",..: 1 1 1 2 2 2 1 1 1 2 ...
## $ parameter : Factor w/ 3 levels "NO","NOx","O3": 2 1 3 2 1 3 2 1 3 2 ...
## $ zeitfenster : Factor w/ 1 level "min30": 1 1 1 1 1 1 1 1 1 1 ...
## $ einheit : Factor w/ 2 levels "µg/m3","ppb": 2 1 1 2 1 1 2 1 1 2 ...
## $ value : num 89.58 76.74 1.59 75.4 63.81 ...
head(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2014-01-01 Zch_Schimmelstrasse NOx min30 ppb 89.58
## 2 2014-01-01 Zch_Schimmelstrasse NO min30 µg/m3 76.74
## 3 2014-01-01 Zch_Schimmelstrasse O3 min30 µg/m3 1.59
## 4 2014-01-01 Zch_Stampfenbachstrasse NOx min30 ppb 75.40
## 5 2014-01-01 Zch_Stampfenbachstrasse NO min30 µg/m3 63.81
## 6 2014-01-01 Zch_Stampfenbachstrasse O3 min30 µg/m3 1.74
read an export file from AIRMO and save it in the store
library(rmo)
# DAT format
df <- read_airmo_dat("O:/060_R/import_airmo/dat/wied_jahr_m30.dat")
rds_save_data(df, "rds")
# CSV format
df <- read_airmo_csv("O:/060_R/import_airmo/STA_data_2013_2015.csv")
rds_save_data(df, "rds")
# optional specify a file encoding, time zone and a time shift (eg. for converting end time to start time)
fn <- "O:/060_R/import_airmo/dat/wied_jahr_m30.dat"
df <- read_airmo_dat(fn, encoding = "cp1252", tz = "Etc/GMT-1",
time_shift = lubridate::minutes(-30))
load data from the store
sites <- c("Zch_Stampfenbachstrasse", "Zch_Schimmelstrasse")
df <- rds_load_data(sites, "min30", 2014:2017, c("NO", "NOx", "O3"), "rds")
str(df)
## 'data.frame': 312189 obs. of 6 variables:
## $ startzeit : POSIXct, format: "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" "2014-01-01 00:00:00" ...
## $ airmo_kurzname: Factor w/ 2 levels "Zch_Schimmelstrasse",..: 1 1 1 2 2 2 1 1 1 2 ...
## $ parameter : Factor w/ 3 levels "NO","NOx","O3": 2 1 3 2 1 3 2 1 3 2 ...
## $ zeitfenster : Factor w/ 1 level "min30": 1 1 1 1 1 1 1 1 1 1 ...
## $ einheit : Factor w/ 2 levels "µg/m3","ppb": 2 1 1 2 1 1 2 1 1 2 ...
## $ value : num 89.58 76.74 1.59 75.4 63.81 ...
head(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2014-01-01 Zch_Schimmelstrasse NOx min30 ppb 89.58
## 2 2014-01-01 Zch_Schimmelstrasse NO min30 µg/m3 76.74
## 3 2014-01-01 Zch_Schimmelstrasse O3 min30 µg/m3 1.59
## 4 2014-01-01 Zch_Stampfenbachstrasse NOx min30 ppb 75.40
## 5 2014-01-01 Zch_Stampfenbachstrasse NO min30 µg/m3 63.81
## 6 2014-01-01 Zch_Stampfenbachstrasse O3 min30 µg/m3 1.74
tail(df)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 312184 2017-12-31 23:30:00 Zch_Schimmelstrasse NO min30 µg/m3 1.415176
## 312185 2017-12-31 23:30:00 Zch_Schimmelstrasse NOx min30 ppb 5.711500
## 312186 2017-12-31 23:30:00 Zch_Schimmelstrasse O3 min30 µg/m3 54.884442
## 312187 2017-12-31 23:30:00 Zch_Stampfenbachstrasse NO min30 µg/m3 1.045155
## 312188 2017-12-31 23:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 6.752600
## 312189 2017-12-31 23:30:00 Zch_Stampfenbachstrasse O3 min30 µg/m3 52.877472
# all parameter for a station (set parameters = NULL)
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2014:2017, base_path="rds")
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2014:2017, NULL, "rds")
utility functions
merge_rmo_longformat
Merge two rmo dataframes
# Mergin: missing values (NA) in y will be replaced with the values from x
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2017, "NOx", base_path="rds")
x <- df[1:5,]
y <- df[3:7,]
y$value <- y$value * 2
xy <- merge_rmo_longformat(x, y)
print(x)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 30.437
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 35.397
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.928
print(y)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 60.874
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 70.794
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 55.856
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 59.332
## 7 2017-01-01 03:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 58.624
print(xy)
## startzeit airmo_kurzname parameter zeitfenster einheit value
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 60.874
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 70.794
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 55.856
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse NOx min30 ppb 59.332
## 7 2017-01-01 03:00:00 Zch_Stampfenbachstrasse NOx min30 ppb 58.624
rmo_to_openair
library(openair)
df <- rds_load_data("Zch_Stampfenbachstrasse", "min30", 2017, NULL, "rds")
td <- rmo_to_openair(df)
head(td)
## date site zeitfenster co no no2 nox
## 1 2017-01-01 00:00:00 Zch_Stampfenbachstrasse min30 0.3642325 9.362537 38.56268 27.672
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse min30 0.3620788 9.481529 36.85615 26.875
## 3 2017-01-01 01:00:00 Zch_Stampfenbachstrasse min30 0.3663280 12.429375 39.14822 30.437
## 4 2017-01-01 01:30:00 Zch_Stampfenbachstrasse min30 0.3693082 18.150572 39.86169 35.397
## 5 2017-01-01 02:00:00 Zch_Stampfenbachstrasse min30 0.3642325 10.406644 37.45144 27.928
## 6 2017-01-01 02:30:00 Zch_Stampfenbachstrasse min30 0.3643955 11.167741 39.60812 29.666
## o3 pm1.0f_roh pm10 pm25 pn so2 wd ws
## 1 1.4207791 NA 76.37508 NA 16254 3.349949 296.15 1.31050
## 2 1.4741852 NA 135.38172 NA 15579 3.114319 288.27 1.41930
## 3 1.4191033 NA 94.85740 NA 12497 1.998468 301.20 1.20090
## 4 1.2726902 NA 77.34658 NA 12020 1.967742 291.53 1.01940
## 5 1.2167305 NA 78.60730 NA 10350 1.813478 286.61 1.12830
## 6 0.8141794 NA 77.15706 NA 10742 1.791059 271.17 0.61363
summaryPlot(td)
# optional add an id column and rename some parameters
site_ids <- list("Zch_Schimmelstrasse"="Wied", "Zch_Stampfenbachstrasse"="Staba")
df <- rds_load_data(names(site_ids), "min30", 2017, c("NOx", "O3", "PM2.5", "WD"), "rds")
parameter_names <- list("O3"="O3_renamed")
td <- rmo_to_openair(df, site_ids, parameter_names)
head(td)
## date site zeitfenster nox o3_renamed pm25 wd id
## 1 2017-01-01 00:30:00 Zch_Schimmelstrasse min30 49.573 1.432410 69.07397 336.86 Wied
## 2 2017-01-01 00:30:00 Zch_Stampfenbachstrasse min30 27.672 1.420779 NA 296.15 Staba
## 3 2017-01-01 01:00:00 Zch_Schimmelstrasse min30 57.428 1.428300 72.01043 338.13 Wied
## 4 2017-01-01 01:00:00 Zch_Stampfenbachstrasse min30 26.875 1.474185 NA 288.27 Staba
## 5 2017-01-01 01:30:00 Zch_Schimmelstrasse min30 72.514 1.479951 65.96797 340.56 Wied
## 6 2017-01-01 01:30:00 Zch_Stampfenbachstrasse min30 30.437 1.419103 NA 301.20 Staba
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