Kleanthis Koupidis, Aikaterini Chatzopoulou, Charalampos Bratsas
#DescriptiveStats.OBeu Εstimate and return the necessary parameters for descriptive statistics visualizations, used in OpenBudgets.eu. It includes functions for measuring central tendency and dispersion of amount variables along with their distributions and correlations and the frequencies of categorical variables for Budget data of municipalities across Europe, according to the OpenBudgets.eu data model.
This package can generally be used to extract visualization parameters convert them to JSON format and use them as input in a different graphical interface. Most functions can have general use out of the OpenBudgets.eu data model. You can see detailed information here.
# install DescriptiveStats.OBeu- cran stable version
install.packages(DescriptiveStats.OBeu)
# or
# alternatively install the development version from github
devtools::install_github("okgreece/DescriptiveStats.OBeu")Load library DescriptiveStats.OBeu
library(DescriptiveStats.OBeu)#Descriptive Statistics in a call
ds.analysis is used to estimate minimum, maximum, range, mean,
median, first and third quantiles, variance, standart deviation,
skewness and kurtosis, boxplot, histogram parameters needed for
visualization of numeric variables and frequencies of factor variables
of a given vector, matrix or data frame of data.
ds.analysis returns by default a list object, we set tojson
parameter TRUE, outliers parameter FALSE,
fr.select = "Produktbereich". Τhere is one numeric variable,
correlation will be empty.
wuppertalanalysis = ds.analysis(Wuppertal_df,outliers=FALSE, fr.select = "Produktbereich", tojson=TRUE) # json string format
jsonlite::prettify(wuppertalanalysis) # use prettify of jsonlite library to add indentation to the returned JSON string## {
## "descriptives": {
## "Min": {
## "Amount": [
## -2040680.54
## ]
## },
## "Max": {
## "Amount": [
## 507995000
## ]
## },
## "Range": {
## "Amount": [
## 510035680.54
## ]
## },
## "Mean": {
## "Amount": [
## 6171229.3658
## ]
## },
## "Median": {
## "Amount": [
## 736038.09
## ]
## },
## "Quantiles": {
## "Amount": [
## 243696.13,
## 2653000
## ]
## },
## "Variance": {
## "Amount": [
## 777106882358169
## ]
## },
## "StandardDeviation": {
## "Amount": [
## 27876636.8552
## ]
## },
## "Kurtosis": [
## 160.1519
## ],
## "Skewness": [
## 11.4762
## ]
## },
## "boxplot": {
## "Amount": {
## "lo.whisker": [
## -2040680.54
## ],
## "lo.hinge": [
## 243696.13
## ],
## "median": [
## 736038.09
## ],
## "up.hinge": [
## 2653000
## ],
## "up.whisker": [
## 6243113.59
## ],
## "box.width": [
## 11.83
## ],
## "lo.out": {
##
## },
## "up.out": {
##
## },
## "n": [
## 6225
## ]
## }
## },
## "histogram": {
## "Amount": {
## "cuts": [
## -50000000,
## 0,
## 50000000,
## 100000000,
## 150000000,
## 200000000,
## 250000000,
## 300000000,
## 350000000,
## 400000000,
## 450000000,
## 500000000,
## 550000000
## ],
## "counts": [
## 46,
## 6032,
## 83,
## 30,
## 10,
## 0,
## 1,
## 11,
## 2,
## 4,
## 4,
## 2
## ],
## "mean": [
## 6171229.3658
## ],
## "median": [
## 736038.09
## ]
## }
## },
## "frequencies": {
## "frequencies": {
## "Produktbereich": [
## {
## "Var1": "Allgemeine Finanzwirtschaft",
## "Freq": 101
## },
## {
## "Var1": "Bauen und Wohnen",
## "Freq": 193
## },
## {
## "Var1": "Gesundheitsdienste",
## "Freq": 207
## },
## {
## "Var1": "Innere Verwaltung",
## "Freq": 1737
## },
## {
## "Var1": "Kinder-, Jugend- u. Familienhilfe",
## "Freq": 373
## },
## {
## "Var1": "Kultur und Wissenschaft",
## "Freq": 346
## },
## {
## "Var1": "Natur- und Landschaftspflege",
## "Freq": 256
## },
## {
## "Var1": "Rauml.Planung, Entw., Geoinfo.",
## "Freq": 463
## },
## {
## "Var1": "Schultrageraufgaben",
## "Freq": 364
## },
## {
## "Var1": "Sicherheit und Ordnung",
## "Freq": 591
## },
## {
## "Var1": "Soziale Leistungen",
## "Freq": 663
## },
## {
## "Var1": "Sportforderung",
## "Freq": 224
## },
## {
## "Var1": "Stiftungen",
## "Freq": 31
## },
## {
## "Var1": "Umweltschutz",
## "Freq": 128
## },
## {
## "Var1": "Ver- und Entsorgung",
## "Freq": 155
## },
## {
## "Var1": "Verkehrsflachen/-anlagen,OPNV",
## "Freq": 261
## },
## {
## "Var1": "Wirtschaft und Tourismus",
## "Freq": 132
## }
## ]
## },
## "relative.frequencies": {
## "Produktbereich": [
## {
## "Var1": "Allgemeine Finanzwirtschaft",
## "Freq": 0.0162
## },
## {
## "Var1": "Bauen und Wohnen",
## "Freq": 0.031
## },
## {
## "Var1": "Gesundheitsdienste",
## "Freq": 0.0333
## },
## {
## "Var1": "Innere Verwaltung",
## "Freq": 0.279
## },
## {
## "Var1": "Kinder-, Jugend- u. Familienhilfe",
## "Freq": 0.0599
## },
## {
## "Var1": "Kultur und Wissenschaft",
## "Freq": 0.0556
## },
## {
## "Var1": "Natur- und Landschaftspflege",
## "Freq": 0.0411
## },
## {
## "Var1": "Rauml.Planung, Entw., Geoinfo.",
## "Freq": 0.0744
## },
## {
## "Var1": "Schultrageraufgaben",
## "Freq": 0.0585
## },
## {
## "Var1": "Sicherheit und Ordnung",
## "Freq": 0.0949
## },
## {
## "Var1": "Soziale Leistungen",
## "Freq": 0.1065
## },
## {
## "Var1": "Sportforderung",
## "Freq": 0.036
## },
## {
## "Var1": "Stiftungen",
## "Freq": 0.005
## },
## {
## "Var1": "Umweltschutz",
## "Freq": 0.0206
## },
## {
## "Var1": "Ver- und Entsorgung",
## "Freq": 0.0249
## },
## {
## "Var1": "Verkehrsflachen/-anlagen,OPNV",
## "Freq": 0.0419
## },
## {
## "Var1": "Wirtschaft und Tourismus",
## "Freq": 0.0212
## }
## ]
## }
## },
## "correlation": {
##
## }
## }
##
ds.analysis uses internally the functions
ds.statistics,ds.hist,ds.boxplot,ds.correlation and
ds.frequency. However, these functions can be used independently and
depends on the user requirements (see package manual or vignettes).
#Descriptive Statistics on OpenBudgets.eu platform
open_spending.ds is designed to estimate and return the basic
descriptive measures, the correlation and the boxplot parameters of all
the numerical variables and the frequencies of all factor variables of
OpenBudgets.eu datasets.
The input data must be a JSON link according to the OpenBudgets.eu data
model. There are different
parameters that a user could specify, e.g. dimensions,
measured.dimensions and amounts should be defined by the user, to
form the dimensions of the dataset. Then the basic descriptive measures
of tendency and spread, boxplot and histogram parameters are estimated
in order to describe and visualize the distribution characteristics of
the desired dataset.
open_spending.ds estimates and returns the json data that are
described with the OpenBudgets.eu data
model, using ds.analysis
function.
descript = open_spending.ds(
json_data = Wuppertal_openspending,
dimensions ="functional_classification_3.Produktgruppe|date_2.Year",
amounts = "Amount"
)
# Pretty output using prettify of jsonlite library
jsonlite::prettify(descript,indent = 2)## {
## "descriptives": {
## "Min": {
## "Amount": [
## 533.21
## ]
## },
## "Max": {
## "Amount": [
## 2997043.49
## ]
## },
## "Range": {
## "Amount": [
## 2996510.28
## ]
## },
## "Mean": {
## "Amount": [
## 659132.4457
## ]
## },
## "Median": {
## "Amount": [
## 476400.565
## ]
## },
## "Quantiles": {
## "Amount": [
## 313924.26,
## 656962.815
## ]
## },
## "Variance": {
## "Amount": [
## 469375540712.697
## ]
## },
## "StandardDeviation": {
## "Amount": [
## 685109.8749
## ]
## },
## "Kurtosis": [
## 5.7675
## ],
## "Skewness": [
## 2.5221
## ]
## },
## "boxplot": {
## "Amount": {
## "lo.whisker": [
## 533.21
## ],
## "lo.hinge": [
## 306296.49
## ],
## "median": [
## 476400.565
## ],
## "up.hinge": [
## 658308.4
## ],
## "up.whisker": [
## 1185907.2
## ],
## "box.width": [
## 1.5
## ],
## "lo.out": [
##
## ],
## "up.out": [
## 2954238.51,
## 2979998.49,
## 2992244.95,
## 2916160.36,
## 2885816.5,
## 2997043.49,
## 2875275.56,
## 1252420.49,
## 1248584.45
## ],
## "n": [
## 100
## ]
## }
## },
## "histogram": {
## "Amount": {
## "cuts": [
## 0,
## 500000,
## 1000000,
## 1500000,
## 2000000,
## 2500000,
## 3000000
## ],
## "counts": [
## 54,
## 32,
## 7,
## 0,
## 0,
## 7
## ],
## "mean": [
## 659132.4457
## ],
## "median": [
## 476400.565
## ]
## }
## },
## "frequencies": {
## "frequencies": {
## "functional_classification_3.Produktgruppe": [
## {
## "Var1": "",
## "Freq": 2
## },
## {
## "Var1": "(entfallen in 2013) Geschaftsbereichsleitung GB 1.1 ",
## "Freq": 5
## },
## {
## "Var1": "Beschaftigtenvertretung",
## "Freq": 1
## },
## {
## "Var1": "Bezirksvertretungen",
## "Freq": 7
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 1",
## "Freq": 15
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 2.1",
## "Freq": 7
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 2.2",
## "Freq": 7
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 4",
## "Freq": 28
## },
## {
## "Var1": "Gleichstellung von Frau und Mann",
## "Freq": 7
## },
## {
## "Var1": "Politische Gremien",
## "Freq": 7
## },
## {
## "Var1": "Verwaltungsfuhrung",
## "Freq": 14
## }
## ],
## "date_2.Year": [
## {
## "Var1": "2009",
## "Freq": 16
## },
## {
## "Var1": "2010",
## "Freq": 15
## },
## {
## "Var1": "2011",
## "Freq": 14
## },
## {
## "Var1": "2012",
## "Freq": 14
## },
## {
## "Var1": "2013",
## "Freq": 15
## },
## {
## "Var1": "2014",
## "Freq": 13
## },
## {
## "Var1": "2015",
## "Freq": 13
## }
## ]
## },
## "relative.frequencies": {
## "functional_classification_3.Produktgruppe": [
## {
## "Var1": "",
## "Freq": 0.02
## },
## {
## "Var1": "(entfallen in 2013) Geschaftsbereichsleitung GB 1.1 ",
## "Freq": 0.05
## },
## {
## "Var1": "Beschaftigtenvertretung",
## "Freq": 0.01
## },
## {
## "Var1": "Bezirksvertretungen",
## "Freq": 0.07
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 1",
## "Freq": 0.15
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 2.1",
## "Freq": 0.07
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 2.2",
## "Freq": 0.07
## },
## {
## "Var1": "Geschaftsbereichsleitung GB 4",
## "Freq": 0.28
## },
## {
## "Var1": "Gleichstellung von Frau und Mann",
## "Freq": 0.07
## },
## {
## "Var1": "Politische Gremien",
## "Freq": 0.07
## },
## {
## "Var1": "Verwaltungsfuhrung",
## "Freq": 0.14
## }
## ],
## "date_2.Year": [
## {
## "Var1": "2009",
## "Freq": 0.16
## },
## {
## "Var1": "2010",
## "Freq": 0.15
## },
## {
## "Var1": "2011",
## "Freq": 0.14
## },
## {
## "Var1": "2012",
## "Freq": 0.14
## },
## {
## "Var1": "2013",
## "Freq": 0.15
## },
## {
## "Var1": "2014",
## "Freq": 0.13
## },
## {
## "Var1": "2015",
## "Freq": 0.13
## }
## ]
## }
## },
## "correlation": {
##
## }
## }
##