FreesearchR/inst/translations/translation_da.csv

1	en	da
2	Hello	Hej
3	Get started	Kom i gang
4	File upload	Upload fil
5	REDCap server export	REDCap server export
6	Local or sample data	Lokal eller testdata
7	Please be mindfull handling sensitive data	Pas godt på og overvej nøje hvordan du håndterer personfølsomme data
8	The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).	***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
9	Quick overview	Hurtigt overblik
10	Select variables for final import	Vælg variabler til den endelige import
11	Exclude incomplete variables:	Ekskluder inkomplette variabler:
12	Manual selection:	Manuel udvælgelse:
13	Let's begin!	Kom i gang!
14	Analysis validation	Analysevalidering
15	Report	Rapport
16	Choose your favourite output file format for further work, and download, when the analyses are done.	Vælge dit foretrukne dataformat, og hent data, når du er ærdig med databehandlingen.
17	www/intro.html	www/intro_da.html
18	<p>The <em><strong>FreesearchR</strong></em> app only stores data for analyses, but please only use with sensitive data when running locally. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Read more here</a></p>	<p><em><strong>FreesearchR</strong></em> opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører <em><strong>FreesearchR</strong></em> direkte på dine egen maskine. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Læs mere her</a></p>
19	Overview and filter	Overblik og filtre
20	Overview and filtering	Overblik og filtrering
21	Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse data and apply different data filters.	Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse data and apply different data filters.
22	Visual overview	Visuelt overblik
23	Browse data	Udforsk data
24	Filter data types	Filtrer datatyper
25	Filter observations	Filtrer observationer
26	Apply filter on observation	Anvend filtre af observationer
27	Edit and create data	Ændr og opret variabler
28	Subset, rename and convert variables	Udvælg, omdøb og konverter variabler
29	Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).	Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).
30	There are more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with R code. At the bottom you can restore the original data.	There are more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with R code. At the bottom you can restore the original data.
31	Please note that data modifications are applied before any filtering.	Please note that data modifications are applied before any filtering.
32	Advanced data manipulation	Avanceret datamanipulation
33	Below options allow more advanced varaible manipulations.	Below options allow more advanced varaible manipulations.
34	Reorder factor levels	Arranger niveuer i faktor
35	Reorder the levels of factor/categorical variables.	Reorder the levels of factor/categorical variables.
36	New factor	Ny faktor
37	Create factor/categorical variable from a continous variable (number/date/time).	Create factor/categorical variable from a continous variable (number/date/time).
38	New variable	Ny variabel
39	Create a new variable based on an R-expression.	Create a new variable based on an R-expression.
40	Compare modified data to original	Compare modified data to original
41	Raw print of the original vs the modified data.	Raw print of the original vs the modified data.
42	Original data:	Original data:
43	Modified data:	Ændret data:
44	New column name:	Navn til ny variabel:
45	Group calculation by:	Group calculation by:
46	Enter an expression to define new column:	Enter an expression to define new column:
47	Click on a column name to add it to the expression:	Click on a column name to add it to the expression:
48	Create column	Create column
49	Choose a name for the column to be created or modified,	Choose a name for the column to be created or modified,
50	then enter an expression before clicking on the button above to validate or on	then enter an expression before clicking on the button above to validate or on
51	to delete it.	to delete it.
52	New column name cannot be empty	New column name cannot be empty
53	Create a new column	Create a new column
54	Some operations are not allowed	Some operations are not allowed
55	Column added!	Column added!
56	Unique values:	Unique values:
57	Variable to cut:	Variable to cut:
58	Number of breaks:	Number of breaks:
59	Close intervals on the right	Close intervals on the right
60	Include lowest value	Include lowest value
61	Create factor variable	Create factor variable
62	Fixed breaks:	Fixed breaks:
63	Method:	Method:
64	Convert Numeric to Factor	Convert Numeric to Factor
65	Unique:	Unique:
66	Missing:	Missing:
67	Most Common:	Most Common:
68	Min:	Min:
69	Mean:	Mean:
70	Max:	Max:
71	Decimal separator:	Decimal separator:
72	First five rows are shown below:	First five rows are shown below:
73	Imported data	Imported data
74	www/intro.md	www/intro.md
75	Choose your data	Choose your data
76	Upload a file, get data directly from REDCap or use local or sample data.	Upload a file, get data directly from REDCap or use local or sample data.
77	Factor variable to reorder:	Factor variable to reorder:
78	Sort by levels	Sort by levels
79	Sort by count	Sort by count
80	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
81	Update factor variable	Updater faktor-variabel
82	Sort count	Sorter antal
83	Levels	Niveauer
84	Count	Antal
85	Update levels of a factor	Updater niveauerne for en faktor
86	Update & select variables	Update & select variables
87	Date format:	Datoformat:
88	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
89	Apply changes	Apply changes
90	No data to display.	Ingen data at vise.
91	Data successfully updated!	Data er opdateret!
92	You removed {p_out} % of observations.	Du har fjernet {p_out} % af observationerne.
93	You removed {p_out} % of variables.	Du har fjernet {p_out} % af variablerne.
94	You can import {file_extensions_text} files	Du kan vælge mellem disse filtyper: {file_extensions_text}.
95	You can choose between these file types:	Du kan vælge mellem følgene filtyper:
96	Rows to skip before reading data:	Rækker der skal springes over:
97	Missing values character(s):	Tegn for manglende værdier:
98	if several use a comma (',') to separate them	if several use a comma (',') to separate them
99	Encoding:	Kodning:
100	Upload a file:	Upload en fil:
101	Browse...	Vælg...
102	Select sheet to import:	Vælg ark:
103	No file selected.	Ingen fil valgt.
104	Evaluate	Evaluer
105	Visuals	Grafik
106	Regression	Regression
107	Download	Download
108	{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.	{data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases.
109	Prepare	Forbered
110	At 0, only complete variables are included; at 100, all variables are included.	At 0, only complete variables are included; at 100, all variables are included.
111	The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.	The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.
112	No variables have a correlation measure above the threshold.	Ingen variabler er korrelerede over den angivne tærskelværdi.
113	and	og
114	from each pair	fra hvert par
115	Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.	Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.
116	Plot	Plot
117	Adjust settings, then press "Plot".	Adjust settings, then press "Plot".
118	Plot height (mm)	Plot height (mm)
119	Plot width (mm)	Plot width (mm)
120	File format	File format
121	Download plot	Download plot
122	Select variable	Select variable
123	Response variable	Response variable
124	Plot type	Plot type
125	Please select	Please select
126	Additional variables	Additional variables
127	Secondary variable	Secondary variable
128	No variable	No variable
129	Grouping variable	Grouping variable
130	No stratification	No stratification
131	Drawing the plot. Hold tight for a moment..	Drawing the plot. Hold tight for a moment..
132	#Plotting\n	#Plotting\n
133	Drawing the plot. Hold on for a moment..	Drawing the plot. Hold on for a moment..
134	Stacked horizontal bars	Stacked horizontal bars
135	A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars	A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars
136	Violin plot	Violin plot
137	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
138	Sankey plot	Sankey plot
139	A way of visualising change between groups	A way of visualising change between groups
140	Scatter plot	Scatter plot
141	A classic way of showing the association between to variables	A classic way of showing the association between to variables
142	Box plot	Box plot
143	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
144	Euler diagram	Euler diagram
145	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships