FreesearchR/inst/translations/translation_sw.csv

1	en	sw
2	Hello	Habari
3	Get started	Tuanze
4	File upload	Upakiaji wa faili
5	REDCap server export	Uhamishaji wa seva ya REDCap
6	Local or sample data	Taarifa za ndani au za mfano
7	Please be mindfull handling sensitive data	Tafadhali kumbuka kushughulikia data nyeti
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).	Programu ya ***FreesearchR*** huhifadhi data kwa uchanganuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani ya nchi. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
9	Quick overview	Muhtasari wa haraka
10	Select variables for final import	Chagua vigeu kwa ajili ya uingizaji wa mwisho
11	Exclude incomplete variables:	Usijumuishe vigeu visivyokamilika:
12	Manual selection:	Uchaguzi wa mikono:
13	Let's begin!	Tuanze!
14	Analysis validation	Uthibitishaji wa uchambuzi
15	Report	Ripoti
16	Choose your favourite output file format for further work, and download, when the analyses are done.	Chagua umbizo la faili la towe lako kwa kazi zaidi, na upakue, uchanganuzi utakapofanywa.
17	www/intro.html	www/intro_sw.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>Programu ya <em><strong>FreesearchR</strong></em> huhifadhi data kwa ajili ya uchanganuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani ya nchi. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Soma zaidi hapa</a></p>
19	Overview and filter	Muhtasari na chujio
20	Overview and filtering	Muhtasari na uchujaji
21	Visual overview	Muhtasari wa kuona
22	Filter data types	Chuja aina za data
23	Filter observations	Chuja uchunguzi
24	Apply filter on observation	Tumia kichujio unapotazama
25	Edit and create data	Edit and create data
26	Subset, rename and convert variables	Subset, rename and convert variables
27	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.).
28	Please note that data modifications are applied before any filtering.	Please note that data modifications are applied before any filtering.
29	Advanced data manipulation	Advanced data manipulation
30	Below options allow more advanced varaible manipulations.	Below options allow more advanced varaible manipulations.
31	Reorder factor levels	Reorder factor levels
32	Reorder the levels of factor/categorical variables.	Reorder the levels of factor/categorical variables.
33	New factor	New factor
34	Create factor/categorical variable from a continous variable (number/date/time).	Create factor/categorical variable from a continous variable (number/date/time).
35	New variable	New variable
36	Create a new variable based on an R-expression.	Create a new variable based on an R-expression.
37	Compare modified data to original	Compare modified data to original
38	Raw print of the original vs the modified data.	Raw print of the original vs the modified data.
39	Original data:	Data asili:
40	Modified data:	Data iliyobadilishwa:
41	New column name:	New column name:
42	Group calculation by:	Group calculation by:
43	Enter an expression to define new column:	Enter an expression to define new column:
44	Click on a column name to add it to the expression:	Click on a column name to add it to the expression:
45	Create column	Create column
46	New column name cannot be empty	New column name cannot be empty
47	Create a new column	Create a new column
48	Some operations are not allowed	Some operations are not allowed
49	Column added!	Column added!
50	Unique values:	Unique values:
51	Variable to cut:	Variable to cut:
52	Close intervals on the right	Close intervals on the right
53	Include lowest value	Include lowest value
54	Create factor variable	Create factor variable
55	Fixed breaks:	Fixed breaks:
56	Method:	Method:
57	Convert Numeric to Factor	Convert Numeric to Factor
58	Unique:	Unique:
59	Missing:	Missing:
60	Most Common:	Most Common:
61	Min:	Min:
62	Mean:	Mean:
63	Max:	Max:
64	Decimal separator:	Decimal separator:
65	First five rows are shown below:	First five rows are shown below:
66	Imported data	Imported data
67	www/intro.md	www/intro.md
68	Choose your data	Choose your data
69	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.
70	Factor variable to reorder:	Factor variable to reorder:
71	Sort by levels	Sort by levels
72	Sort by count	Sort by count
73	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
74	Update factor variable	Update factor variable
75	Sort count	Sort count
76	Levels	Levels
77	Count	Count
78	Update levels of a factor	Update levels of a factor
79	Update & select variables	Update & select variables
80	Date format:	Date format:
81	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
82	Apply changes	Apply changes
83	No data to display.	No data to display.
84	Data successfully updated!	Data successfully updated!
85	You removed {p_out} % of observations.	You removed {p_out} % of observations.
86	You removed {p_out} % of variables.	You removed {p_out} % of variables.
87	You can import {file_extensions_text} files	You can import {file_extensions_text} files
88	You can choose between these file types:	You can choose between these file types:
89	Rows to skip before reading data:	Rows to skip before reading data:
90	Missing values character(s):	Missing values character(s):
91	if several use a comma (',') to separate them	if several use a comma (',') to separate them
92	Encoding:	Encoding:
93	Upload a file:	Upload a file:
94	Browse...	Browse...
95	Select sheet to import:	Select sheet to import:
96	No file selected.	No file selected.
97	Evaluate	Evaluate
98	Visuals	Visuals
99	Regression	Regression
100	Download	Download
101	{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.	{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.
102	Prepare	Prepare
103	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.
104	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.
105	No variables have a correlation measure above the threshold.	No variables have a correlation measure above the threshold.
106	and	and
107	from each pair	from each pair
108	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.
109	Plot	Plot
110	Adjust settings, then press "Plot".	Adjust settings, then press "Plot".
111	Plot height (mm)	Plot height (mm)
112	Plot width (mm)	Plot width (mm)
113	File format	File format
114	Download plot	Download plot
115	Select variable	Select variable
116	Response variable	Response variable
117	Plot type	Plot type
118	Please select	Please select
119	Additional variables	Additional variables
120	Secondary variable	Secondary variable
121	No variable	No variable
122	Grouping variable	Grouping variable
123	No stratification	No stratification
124	Drawing the plot. Hold tight for a moment..	Drawing the plot. Hold tight for a moment..
125	#Plotting\n	#Plotting\n
126	Stacked horizontal bars	Stacked horizontal bars
127	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
128	Violin plot	Violin plot
129	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
130	Sankey plot	Sankey plot
131	A way of visualising change between groups	A way of visualising change between groups
132	Scatter plot	Scatter plot
133	A classic way of showing the association between to variables	A classic way of showing the association between to variables
134	Box plot	Box plot
135	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
136	Euler diagram	Euler diagram
137	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships
138	Documentation	Documentation
139	Data is only stored for analyses and deleted when the app is closed.	Data is only stored for analyses and deleted when the app is closed.
140	Consider [running ***FreesearchR*** locally](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) if working with sensitive data.	Consider [running ***FreesearchR*** locally](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) if working with sensitive data.
141	Feedback	Feedback
142	License: AGPLv3	License: AGPLv3
143	Source	Source
144	Data includes {n_pairs} pairs of highly correlated variables.	Data includes {n_pairs} pairs of highly correlated variables.
145	Create plot	Create plot
146	Coefficients plot	Coefficients plot
147	Checks	Checks
148	Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.	Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.
149	Browse observations	Browse observations
150	Settings	Settings
151	The following error occured on determining correlations:	The following error occured on determining correlations:
152	We encountered the following error creating your report:	We encountered the following error creating your report:
153	No variable chosen for analysis	No variable chosen for analysis
154	No missing observations	No missing observations
155	Missing vs non-missing observations in the variable **'{variabler()}'**	Missing vs non-missing observations in the variable **'{variabler()}'**
156	There is a significant correlation between {n_nonmcar} variables and missing observations in the outcome variable {outcome}.	There is a significant correlation between {n_nonmcar} variables and missing observations in the outcome variable {outcome}.
157	There is a total of {p_miss} % missing observations.	There is a total of {p_miss} % missing observations.
158	Median:	Median:
159	Restore original data	Restore original data
160	Reset to original imported dataset. Careful! There is no un-doing.	Reset to original imported dataset. Careful! There is no un-doing.
161	Characteristics	Characteristics
162	Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.	Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.
163	Compare strata?	Compare strata?
164	Correlations	Correlations
165	To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.	To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.
166	Correlation cut-off	Correlation cut-off
167	Set the cut-off for considered 'highly correlated'.	Set the cut-off for considered 'highly correlated'.
168	Missings	Missings
169	Class	Class
170	Observations	Observations
171	Data classes and missing observations	Data classes and missing observations
172	Sure you want to reset data? This cannot be undone.	Sure you want to reset data? This cannot be undone.
173	Cancel	Cancel
174	Confirm	Confirm
175	The filtered data	The filtered data
176	Create new factor	Create new factor
177	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
178	Create new variables	Create new variables
179	Select data types to include	Select data types to include
180	Uploaded data overview	Uploaded data overview
181	Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.	Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.
182	Specify covariables	Specify covariables
183	If none are selected, all are included.	If none are selected, all are included.
184	Analyse	Analyse
185	Working...	Working...
186	Press 'Analyse' to create the regression model and after changing parameters.	Press 'Analyse' to create the regression model and after changing parameters.
187	Show p-value	Show p-value
188	Model checks	Model checks
189	Please confirm data reset!	Please confirm data reset!
190	Import data from REDCap	Import data from REDCap
191	REDCap server	REDCap server
192	Web address	Web address
193	Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'	Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'
194	API token	API token
195	The token is a string of 32 numbers and letters.	The token is a string of 32 numbers and letters.
196	Connect	Connect
197	Data import parameters	Data import parameters
198	Select fields/variables to import and click the funnel to apply optional filters	Select fields/variables to import and click the funnel to apply optional filters
199	Import	Import
200	Click to see data dictionary	Click to see data dictionary
201	Connected to server!	Connected to server!
202	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
203	Data dictionary	Data dictionary
204	Preview:	Preview:
205	Imported data set	Imported data set
206	Select fields/variables to import:	Select fields/variables to import:
207	Specify the data format	Specify the data format
208	Fill missing values?	Fill missing values?
209	Requested data was retrieved!	Requested data was retrieved!
210	Data retrieved, but it looks like only the ID was retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.	Data retrieved, but it looks like only the ID was retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
211	Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.	Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
212	Click to see the imported data	Click to see the imported data
213	Regression table	Regression table
214	Import a dataset from an environment	Import a dataset from an environment
215	Select a dataset:	Select a dataset:
216	List of datasets...	List of datasets...
217	No data selected!	No data selected!
218	No dataset here...	No dataset here...
219	Use a dataset from your environment or from the environment of a package.	Use a dataset from your environment or from the environment of a package.
220	Not a data.frame	Not a data.frame
221	Select source	Select source
222	Select a data source:	Select a data source:
223	Yes	Yes
224	No	No
225	Coefficient plot	Coefficient plot
226	Select outcome variable	Select outcome variable
227	Choose regression analysis	Choose regression analysis
228	Covariables to format as categorical	Covariables to format as categorical
229	Select variable to stratify baseline	Select variable to stratify baseline
230	Select models to plot	Select models to plot
231	Creating regression models failed with the following error:	Creating regression models failed with the following error:
232	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
233	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
234	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
235	Select checks to plot	Select checks to plot
236	Multivariable regression model checks	Multivariable regression model checks
237	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
238	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
239	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
240	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
241	Data import	Data import
242	Data import formatting	Data import formatting
243	Data modifications	Data modifications
244	Variables filter	Variables filter
245	Data filter	Data filter
246	Data characteristics table	Data characteristics table
247	The dataset without text variables	The dataset without text variables
248	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
249	Select variable to stratify analysis	Select variable to stratify analysis
250	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
251	We encountered the following error showing missingness:	We encountered the following error showing missingness:
252	We encountered the following error browsing your data:	We encountered the following error browsing your data:
253	To consider if data is missing by random, choose the outcome/dependent variable (only variables with any missings are available). If there is a significant difference across other variables depending on missing observations, it may not be missing at random.	To consider if data is missing by random, choose the outcome/dependent variable (only variables with any missings are available). If there is a significant difference across other variables depending on missing observations, it may not be missing at random.
254	Choose a name for the column to be created or modified, then enter an expression before clicking on the button below to create the variable, or cancel to exit without saving anything.	Choose a name for the column to be created or modified, then enter an expression before clicking on the button below to create the variable, or cancel to exit without saving anything.
255	Other	Other
256	Hour of the day	Hour of the day
257	Breaks	Breaks
258	By day of the week	By day of the week
259	By weekday	By weekday
260	By week number and year	By week number and year
261	By week number	By week number
262	By month and year	By month and year
263	By month only	By month only
264	By quarter of the year	By quarter of the year
265	By year	By year
266	Keep only most common	Keep only most common
267	Number	Number
268	Combine below percentage	Combine below percentage
269	Percentage	Percentage
270	By specified numbers	By specified numbers
271	By quantiles (groups of equal size)	By quantiles (groups of equal size)
272	Please fill in web address and API token, then press 'Connect'.	Please fill in web address and API token, then press 'Connect'.
273	There are more advanced options to modify factor/categorical variables as well as create new factor from an existing 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 an existing variable or new variables with R code. At the bottom you can restore the original data.
274	Text or character to split string by	Text or character to split string by
275	Split the variable	Split the variable
276	Variable to split:	Variable to split:
277	Direction:	Direction:
278	Split string to multiple columns. Keep number of rows.	Split string to multiple columns. Keep number of rows.
279	Split string to multiple observations (rows) in the same column. Also ads id and instance columns	Split string to multiple observations (rows) in the same column. Also ads id and instance columns
280	Split character string	Split character string
281	Split text	Split text
282	Split a character string by a common delimiter	Split a character string by a common delimiter
283	Select delimiter	Select delimiter
284	Browse data preview	Browse data preview
285	Original data	Original data
286	Preview of result	Preview of result
287	No character variables with accepted delimiters detected.	No character variables with accepted delimiters detected.
288	Split a text column by a recognised delimiter.	Split a text column by a recognised delimiter.
289	Apply split	Apply split
290	Stacked relative barplot	Stacked relative barplot
291	Create relative stacked barplots to show the distribution of categorical levels	Create relative stacked barplots to show the distribution of categorical levels
292	Side-by-side barplot	Side-by-side barplot
293	Create side-by-side barplot to show the distribution of categorical levels	Create side-by-side barplot to show the distribution of categorical levels