census | 📜Automated review of open source software projects | Code Analyzer library

I have three large dataframes and I want to append some of the elements from one onto another based on several criteria. I looked up similar questions in Stack Overflow but they don't seem to work for my dataframe format (or I'm not skilled enough to adapt it properly).

What needs to happen is:

1. Filter by sex in maindf1
2. Search for the same ZCTA value in maindf1 in a rowname (first column) in maledflookup
3. Also search for the right age strata from a row in maindf1 in the column name of maledflookup
4. Add a new column of data to maindf1 row with matching ZCTA that has the census population value for that sex and age strata taken from maledflookup
5. Repeat with femaledflookup
6. End result is maindf1 having a censuspop value for every row that was matched by sex, ZCTA, and age strata

maindf1 is raw data where each row is an individual and columns are survey responses or collected data on individuals

The lookup table from the census website I had to use is in weird formatting so the easiest solution for me to fix one of the issues with it was to separate the lookup tables by sex first.

I had no luck in writing successful code as I'm not very experienced with coding in R yet. I tried some for & if loops and failed at adapting fuzzyjoin code for this task. I appreciate your help!

Example data:

I'm following the O'Reilly's hands on ML book for the analysis of adult census data. I have used the same method before on another set and had little problem. When I run the lin_reg.fit() this is what I get:

This is my X and y:

X:

I'm trying to write a function I'm frequently in my dissertation but having a hard time getting it to run.

The code works but then fails once I run the function, I think, because of how R reads in the designated variable via the embracing function options. Here is the successful code for one variable, prburden and a link to sample data:

I'm working with house price indices and I have a question on how to add another geom to a ggplot. This is an example data that I made for this question. I have housing data from a census and from online postings. rooms a variable for a housing characteristic (many or few rooms), and value is the percentage of homes for each source that has that characteristic. Then, houses and apts show the percentage of houses and apts that the city has for that data source. So for example, city 1 has 40% houses and 60% apartments in the census data and 45% houses and 55% apartments in the zillow data. I made a geom_bar faceting by rooms and filling by source so I have two plots, one for rooms=1 and another for rooms=2, each one of them with two bars for each city (one for each source). Now, I want to fill those same bars with the percentage of houses and apartments for each city and source.

I'd be very grateful if someone can help me with this.

The code I'm currently using for the plot is the following:

I have looked over the responses to previous zip downloading questions and I keep running into problems. I used BeatifulSoup to identify a particular zip file I want to download using the following code:

I am trying to calculate the population under 20 by race for each county in MN using the American Community Survey in R. Using Tidycensus I am aware this can be done using the B01001H variables for each race and age group in R. However I would need to aggregate all the variables for those under 20 for each racial group. According to this webpage (https://www.census.gov/content/dam/Census/library/publications/2018/acs/acs_general_handbook_2018_ch08.pdf) while aggregating the estimates is merely the sum of each of the subgroup values, aggregating the margin of error requires I calculate this formula:

I'm trying to calculate landcover repartition for each US county. I have obtained NLCD for the Apache county using the FedData package (devtools version) and I'm using county shapefiles from the Census bureau.

The problem is that I get an area that is much larger than the official one and the one indicated in my shapefile, namely 51,000km^2 instead of 29,0000km^2 officially. There must be something I don't understand about the raster object but I'm a very confused after hours of websearching, any help appreciated.

The following describes the code used and the method used to calculate. The county data can be downloaded here: https://www2.census.gov/geo/tiger/TIGER2016/COUNTY/

The following code assumes the county shapefile is saved and unzipped.

1. Get and read the data

Our system needs to return several KPIs grouped in different topics:

• Census:
  • citizens (number of inhabitants)
  • citizens without any studies
  • ...
• Information desk
  • Phone response time
  • Mail response time
  • ...
• Tax
  • Online payments
  • Window payments
  • ...

To my understanding, it would make sense to have an entity for each topic and each KPI being a KeyPerformanceIndicator attribute. eg: This could work similar to:

I have 2 dataframes with numeric codes that represent various jobs.
One df (df_a) has codes from census the other (df_b) has codes that represent essential jobs.
I need to create a new column in df_a with where jobs are listed as essential or non-essential based on codes in df_b.
The issue is that some job codes in df_a have character M = multiple integers in df_b (e.g. 123M5 in df_a = 12335, 12345, 12355... in df_b). I am trying to accomplish this by setting M='\\d' in df_a but not succeeding... any thoughts on a better way to approach this? Thanks!