corc | Stackless coroutine compiler for C | Android library
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kandi X-RAY | corc Summary
Stackless coroutine compiler for C.
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QUESTION
I'm trying to make a Geofence in Swift 4, but I have a problem, I have an error when calling locationManager, I do not understand why I get this error
this is the error:
Ambiguous use of locationManager
I tried to correct it by placing self.locationManager.startUpdatingLocation () and other different methods but none worked
Here I declare my variable locationManager:
...ANSWER
Answered 2019-May-27 at 18:36If locationManager
is an instance property use it directly
QUESTION
I have a data frame built as such:
...ANSWER
Answered 2017-Aug-27 at 04:55We can create the vector with paste
and cbind
it to the original dataset
QUESTION
How can I preserve one of the grouping names when using dply::summarise? Or, is there a better way to preserve one of the group names? I am probably going about this rather inefficiently.
I have a data.frame (df) as such:
...ANSWER
Answered 2017-Aug-26 at 21:47Here's an updated answer, based on the comment thread. We summarise by AU
and BU
separately and store the results in a list. We then show how to combine the summaries into a single data frame and to output the summary as a table.
QUESTION
I have a data.frame of numeric scores related to groups (y) measured across different factors (x) with resulting scores. Similar to the table below.
...ANSWER
Answered 2017-Aug-23 at 21:07cut
is a great function for dividing numbers into intervals and giving them explanatory names.
QUESTION
I have a tbl_df (tibble) named 'control.scores' that has a column called "Overall", which is some value between 1.00 and 4.00.
...ANSWER
Answered 2017-Aug-23 at 06:03We can consider to use case_when
from the dplyr
. Notice that I changed the range of your classification a little bit because there are gaps in your original classification. For example, 3.505 will have no any associated classes based on your original classification. dt2
is the final output.
QUESTION
I'm trying to find a better and faster way to put together a table of summary statistics comprised of weighted averages. Using dplyr to summarise and then bind_rows I end up with a table like this. These numbers are simple averages The averages are calculated for each factor for each group.
Dataframe: au.scores
...ANSWER
Answered 2017-Aug-23 at 02:10Overall.Group1 is Group1+Group4+Group5, Group2 is Group2+Group4+Group5 and Group3 is Group3+Group4+Group5 factors.
Your description of how overall scores are calculated is different from your formula for group1.overall
, which uses Group1 <- Group1+Group2+Group3 instead. In the approach below, I'm going by the description. You can tweak that if necessary:
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