#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": "Räuml.Planung, Entw., Geoinfo.",
## "Freq": 463
## },
## {
## "Var1": "Schulträgeraufgaben",
## "Freq": 364
## },
## {
## "Var1": "Sicherheit und Ordnung",
## "Freq": 591
## },
## {
## "Var1": "Soziale Leistungen",
## "Freq": 663
## },
## {
## "Var1": "Sportförderung",
## "Freq": 224
## },
## {
## "Var1": "Stiftungen",
## "Freq": 31
## },
## {
## "Var1": "Umweltschutz",
## "Freq": 128
## },
## {
## "Var1": "Ver- und Entsorgung",
## "Freq": 155
## },
## {
## "Var1": "Verkehrsflächen/-anlagen,ÖPNV",
## "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": "Räuml.Planung, Entw., Geoinfo.",
## "Freq": 0.0744
## },
## {
## "Var1": "Schulträgeraufgaben",
## "Freq": 0.0585
## },
## {
## "Var1": "Sicherheit und Ordnung",
## "Freq": 0.0949
## },
## {
## "Var1": "Soziale Leistungen",
## "Freq": 0.1065
## },
## {
## "Var1": "Sportförderung",
## "Freq": 0.036
## },
## {
## "Var1": "Stiftungen",
## "Freq": 0.005
## },
## {
## "Var1": "Umweltschutz",
## "Freq": 0.0206
## },
## {
## "Var1": "Ver- und Entsorgung",
## "Freq": 0.0249
## },
## {
## "Var1": "Verkehrsflächen/-anlagen,ÖPNV",
## "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) Geschäftsbereichsleitung GB 1.1 ",
## "Freq": 5
## },
## {
## "Var1": "Beschäftigtenvertretung",
## "Freq": 1
## },
## {
## "Var1": "Bezirksvertretungen",
## "Freq": 7
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 1",
## "Freq": 15
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 2.1",
## "Freq": 7
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 2.2",
## "Freq": 7
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 4",
## "Freq": 28
## },
## {
## "Var1": "Gleichstellung von Frau und Mann",
## "Freq": 7
## },
## {
## "Var1": "Politische Gremien",
## "Freq": 7
## },
## {
## "Var1": "Verwaltungsführung",
## "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) Geschäftsbereichsleitung GB 1.1 ",
## "Freq": 0.05
## },
## {
## "Var1": "Beschäftigtenvertretung",
## "Freq": 0.01
## },
## {
## "Var1": "Bezirksvertretungen",
## "Freq": 0.07
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 1",
## "Freq": 0.15
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 2.1",
## "Freq": 0.07
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 2.2",
## "Freq": 0.07
## },
## {
## "Var1": "Geschäftsbereichsleitung GB 4",
## "Freq": 0.28
## },
## {
## "Var1": "Gleichstellung von Frau und Mann",
## "Freq": 0.07
## },
## {
## "Var1": "Politische Gremien",
## "Freq": 0.07
## },
## {
## "Var1": "Verwaltungsführung",
## "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": {
##
## }
## }
##