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I have a dataset which include two columns (trip_start_date,trip_end_date). both of these columns were chr datatype so i converted them into dttm using this code:

I want to write a code that can be used on different XML files (all with TEI encoding) to see if specific elements and attributes appear, how often they appear and in what context). To do this I have written the following code:

I am just getting started with regular expressions (working with the stringr package), and I have written some code that does not do exactly what I want it to do. I am working with a dataset with some very messy string data and am trying to clean it up to be used with a google maps API.

I've attached a sample of the data below.

Basically, I want to select every row where loc_01 is a simple street name. By this, I mean I want it to take on the following formats:

A numbered street, such as 10th Ave; A named street, such as MAIN ST, and any directional modification of such street names (such as 10TH AVE NW, W MAIN ST, or W 10TH AVE.)

I have tried the following expression:

I have preprocessed this a df containing info on US Emergency and Disaster history, to now contain the ```['Place, Disaster_type, Start_date, End_date Disaster_length, Year'] from 1960-2017.

Now, I would like to create 2 new dfs.

1. = to the number of times a disaster occurred in each year,
2. = to the number times each type of disaster occurred each year.

This is my current attempt at trying to calculate the number of disasters that happened each year and create a new df, but I'm not sure how to have it specifically count the number of disasters pear year.

I am currently trying to calculate the length of disasters, measured in days, and then with this column that is the difference between the start date and end date, use groupby ( I think), in order to sum the length of disasters for each year, as my data set is from 1960 to present. Eventually, I'd like to also group it by disaster type as well to see how the length of particular disasters changed overtime, but one step at a time.

So far I have converted the dates to pd.datetime format, and then used the code below to create the column with the difference of the two dates

I have a data.frame with a column containing California counties in each cell separated by a space. I would like to add a comma and space after each one, however I can't just gsub every space into a comma and space, (i.e. gsub("\s",",\s",text)), as some counties in California have two names, (e.g. Los Angeles, San Francisco, etc.)

Fortunately, the two-word counties all have common first words so I'd like to write a gsub that preserves the space in those counties without adding a comma. I've attached example data as well as what I'd like the final form to look like. For instance, with this data, I'd like to add a comma and space except after "El", "San" and "Del".

Example data:

The task at hand is mapping the empprevyearpct value to a county map. The sample data is below.

following are my files for html, .ts and json . As json data was very extensive therefore i have just added a few states and their cities. my 1st dropdown is showing all states. Now I want to match my 1st dropdown's selected value of state with a key "state" in "cities" object in my json file so i can populate 2nd dropdown with cities relevant to that state. and I want to do this in function "getCitiesForSelectedState". please help me find solution for this.

//.ts file

I'm reading tables from a website where one of the columns is university name and some of the names have special characters which are the following (but the names are written like I put them here, so is not a task I can fix by reading the web in a different way):