I have a dataframe that looks like this:
Date
Tag
Section
1/21/22
001
1
1/22/22
001
2
1/23/22
001
3
1/21/22
002
2
1/22/22
002
1
1/23/22
002
2
The dataframe has already been grouped by Tag number and date from oldest to newest. My objective is to see if the object with the tag number is moving or staying in the same section, moving up sections or moving down sections between dates. In this case moving from 1 to 2 would be moving up and moving from 2 to 1 would be down.
A new column could have no movement for the first observation of the tag it is in but would have movement for the next two dates. All tag numbers are unique values. I have been thinking about dplyr statement or and if statement but have not been able to come up with anything.
Related
Sorry I do not know how to properly title my question. It is easier to understand with an example.
Sample data
Consider the following example.
> l_ids=as.data.frame(cbind(a=c("strong","intense","intensity"),
id=c("1","2","3"),new_id=c("","1","2")),stringsAsFactors = FALSE)
a id new_id
1 strong 1
2 intense 2 1
3 intensity 3 2
I would like to update the id of each word in a with a new_id, if it applies. Consider this as a synonym dictionary. As I iterate over new_id;
> for (i in 1:nrow(l_ids)){
+ if (nchar(l_ids$new_id[i])>0){
+ l_ids$id[i]=l_ids$new_id[i]
+ }
+ }
> l_ids
a id new_id
1 strong 1
2 intense 1 1
3 intensity 2 2
The problem is that I would like for intensity to also be given a 1. Is there a way to do this without having to iterate multiple times?
Update on background
I have a document where I have a list of synonyms. These are synonyms only relevant to the field of application of the problem. Example:
> dictionary
good bad
1 strong intense
2 intense intensity
3 light soft
I am then given a list of words, each with a given id. My task is to check if any of those words is in the bad column of dictionary and, if so, update it with the id of the word to its left. As can be seen, intensity would need two steps to become strong (a good word in the dictionary). Is there a way to do so without having to do multiple iterations? (say, a for loop)
I posted yesterday another question but I feel I need to clarify it.
Let's say I have this code
md.NAME <- (subset(MyData, HotelName=="ALAMEDA"))
md.NAME.fc <- (subset(md.ALAMEDA, TIPO=="FORECAST"))
md.NAME.fc.bar <- (subset(md.ALAMEDA.fc, Market.Segment=="BAR"))
What I want is that NAME changes according to a variable set before those 3 lines are run,
So NAME is just dynamic in the sense that before these 3 lines I could say, ok, NAME now is equal to JOHN, but then, I could say that NAME is now equal to PATRIC.
So after running those 3 lines, twice (once for John and once for Patric) somehow in the environment I will get something like this:
6 dataframes, 3 for JOHN and 3 for PATRIC
DATAFRAME 1 WILL BE md.JOHN
DATAFRAME 2 WILL BE md.JOHN.fc
DATAFRAME 3 WILL BE md.JOHN.fc.bar
DATAFRAME 1 WILL BE md.PATRIC
DATAFRAME 2 WILL BE md.PATRIC.fc
DATAFRAME 3 WILL BE md.PATRIC.fc.bar
All the answers I had so far would help me only if "md" and "fc" or "fc.bar" are always the same. But I will have several variables like this, which will change a lot as far as the naming goes. So, it is the center part (NAME) the only one that should change.
I could even have something like:
md.test$NAME <- ...
I have the following data frame:
group_id date_show date_med
1 1976-02-07 1971-04-14
1 1976-02-09 1976-12-11
1 2011-03-02 1970-03-22
2 1993-08-04 1997-06-13
2 2008-07-25 2006-09-01
2 2009-06-18 2005-11-12
3 2009-06-18 1999-11-03
I want to subset my data frame in such a way that the new data frame only shows the rows in which the values of date_show are further than 10 days apart but this condition should only be applied per group. I.e. if the values in the date_show column are less than 10 days apart but the group_ids are different, I need to keep both entries. What I want my result to look like based on the above table is:
group_id date_show date_med
1 1976-02-07 1971-04-14
1 2011-03-02 1970-03-22
2 1993-08-04 1997-06-13
2 2008-07-25 2006-09-01
2 2009-06-18 2005-11-12
3 2009-06-18 1999-11-03
Which row gets deleted isn't important because the reason why I'm subsetting in the first place is to calculate the number of rows I am left with after applying this criteria.
I've tried playing around with the diff function but I'm not sure how to go about it in the simplest possible way because this problem is already within another sapply function so I'm trying to avoid any kind of additional loop (in this case by group_id).
The df I'm working with has around 100 000 rows. Ideally, I would like to do this with base R because I have no rights to install any additional packages on the machine I'm working on but if this is not possible (or if solving this with an additional package would be significantly better), I can try and ask my admin to install it.
Any tips would be appreciated!
To put it simple, I have three columns in excel like the ones below:
Vehicle x y
1 10 10
1 15 12
1 12 9
2 8 7
2 11 6
3 7 12
x and y are the coordinates of customers assigned to the corresponding vehicle. This file is the output of a program I run in advance. The list will always be sorted by vehicle, but the number of customers assigned to vehicle "k" may change from one experiment to the next.
I would like to plot a graph containing 3 series, one for each vehicle, where the customers of each vehicle would appear (as dots in 2D based on their x- and y- values) in different color.
In my real file, I have 12 vehicles and 3200 customers, and the ranges change from one experiment to the next, so I would like to automate the process, i.e copy-paste the list on my excel and see the graph appear automatically (if this is possible).
Thanks in advance for your time and effort.
EDIT: There is a similar post here: Use formulas to select chart data but requires the use of VB. Moreover, I am not sure whether it has been indeed answered.
you should try this free online tool - www.cloudyexcel.com/excel-to-graph/
I need to show a report of same set of data with different condition.
I need to show count of users registered by grouping region, country and userType, I have used drill down feature for showing this and is working fine. Also the reported data is the count of users registered between two dates. Along with that I have to show the total users in the system using the same drill down that is total users by region, country and usertype in a separate column along with each count (count of users between two date)
so that my result will be as follwsinitialy it will be like
Region - Country - New Reg - Total Reg - User Type 1 - UserType2
+ Region1 2 10 1 5 1 5
+ Region2 3 7 2 4 1 3
and upon expanding the region it will be like
Region - Country - New Reg - Total Reg - User Type 1 - UserType2
+ Region1 2 10 1 5 1 5
country1 1 2 1 2 - -
country2 1 8 1 8 - -
+ Region2 3 7 2 4 1 3
Is there a way I can show my report like this, I have tried with two data sets one with conditional datas and other with non conditional but it didn't work, its always bing total number of regiostered users for all the total reg columns
Unless I'm mistaken, you're trying to create an expandable table, with different grouping levels? Fortunately, this can be easily done in SSRS if you know where to look. The totals on your example don't seem to match up in the user columns, so I may have misunderstood the problem.
For starters, set up your query to produce a single dataset like this:
Region Country New Reg - Total Reg - User Type 1 - User Type 2
Region1 country1 1 2 1
Region1 country2 1 8 1
Region2 country3 2 4 1 1
Region2 country4 1 3 1
Now that you've got that, you want to set up a new table with the fields "NewReg", "TotalReg", "UserType1" and "UserType2". Then right-click the table row, and go to "Add Group > Row Group > Parent Group". Select "Country" in the Group by and click okay. Then, repeat this process and select "Region". This time however, tick the "Add group header" box. This will insert another row above the original.
Now, for each of your fields ("NewReg", "TotalReg" etc), click in the new row above and select the field again. this will automaticaly add a Sum(FieldName) value into the cell. This will add together all the individual row totals and present a new, grouped by region row when you run the report.
That should give you the table you require with the data aggregated correctly, so all you need to do is manage the show/hide the detail rows on demand.
To do this, select your detail row (the original row) and right-click "> Row visibility". Set this to "Hide". Now, select the cell that contains the "Region" and take note of its ID using Properties (for now, let's assume it's called "Region"). Click back onto your detail row and look at the properties window. At the bottom you'll see a "Visibility" setting. In there, set "InitialToggleState" to False and "ToggleItem" to the name of your region group's cell (i.e. "Region").
Now all that should be left is to do the formatting etc and tidy up.
I have solved this problem by taking all the records from DB and filtering the records to collect new reg count by using an expression as following
=Sum(IIF(Fields!RegisteredOn.Value >Parameters!FromDate.Value and Fields!RegisteredOn.Value < Parameters!EndDate.Value , 1,0))