dredge | A Python package for assisting with data mining work

I ran multiple imputation to impute missing data for 2 variables of a data frame, then I got a new data frame (with 2 columns for 2 imputed variables).

Now, I want to replace the 2 columns in the original data frame with the two newly imputed columns from my new dataframe. What should I do?

Original data frame new data frame for imputed variables

This is the code I used. Only 2 columns in this data frame are missing data, so I only imputed those two. Is that ok? Can you please suggest me a better way?

I have a global moel with two smoothed terms and two random effects.

Basically I have a table and a user can add rows. Depending on row type, they are added a little differently. A standard row is always added by .append(), but an "instruction" row should always be added after the last row that was created or modified.

So I have a JSON file which I have loaded into a dictionary. It has 8 different keys that it is storing information for. I am trying to create a search engine that returns the recipe that contains all the words in the search string and returns them. I change the string into a list of "tokens" that I will be used for searching.

Here is an example of some of the information stored in the dictionary. A recipe should be returned as long as the tokens are located in either the title, categories, ingredients or directions.

I have produced an averaged GLM model (to find the habitat preference of a species), and I want to graph the shape of the relationship for each of the most important variables, “x1” and “x3” (understorey cover and canopy cover), against my response variable, “species” (species presence). I have been using the “predict”(predict.averaging) function, but I keep running into the same error:

Error in eval(predvars, data, env) : object 'x3' not found

More details and code:

My dataset, “data.csv”, is a table with 13 rows. The first 12 rows are scaled habitat variables (10 continuous, 2 categorical), named x1-x12. Row 13 is the response variable – species presence/absence (1 or 0). Here is my code:

library(MuMIn)

dataset <- read.csv(file = 'data.csv', stringsAsFactors = FALSE)

options(na.action = "na.fail")

m1 <- glm(species ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + x10 + x11 + x12, data=Dataset, family=binomial())

ms1 <- dredge(m1) #Running different model combinations

d2subset <- get.models(ms1, subset = delta < 2) #Models with delta AIC <2 are selected.

avgm <- model.avg(d2subset) #DeltaAIC<2 models are averaged.

summary(avgm) #Shows 'x1' to be the most significant variable.

The following code, attempting to predict from the averaged model, causes an error:

predict(avgm, data.frame(dataset$x1), se.fit = TRUE, type = "link", backtransform = TRUE, full = TRUE)

Errors produced:

Error in predict.averaging(avgm, dataset$x1), se.fit = TRUE, :

'predict' for models '2211', '163', '147', '179', '2227', '183', '131', '2195', '167', '2275', '227', '243', '211', '148', '1171', '435', '151', '3235', '247', '2215', '155', '2231', '659', '2291', '2219' and '171' caused errors.

In addition: There were 26 warnings (use warnings() to see them)

Warning messages: 1: In eval(predvars, data, env) : object 'x3' not found

2-13: In eval(predvars, data, env) : object 'x3' not found

14: In eval(predvars, data, env) : object 'x5' not found

15-26: In eval(predvars, data, env) : object 'x3' not found

I have looked into this a lot, but I still don't understand where the error comes from or how to work around it. I would be very grateful for any suggestions. Thank you!

I'm trying to exponentiate coefficients and standard errors from multiple Poisson models from a MuMIn::dredge object to use with texreg::screenreg. In the case of one model we can do this:

I want to automate turning lists of names into regression equations for use in the Dredge command from the MuMIn package.

Making this:

I have a global model using a GLMM with 5 fixed effects with interactions, as well as two random effects.

I am building a small website example project using HTML, CSS and JS. I have a button that after click should download PDF example data (for now it is not necessary where to save the documents).

The problem: How to I download PDF documents using an HTML button?

I am using reactstrap Card for each component I would like to download the data. This is an example only, and the real website will contain for each card a button with specific downloadable information.

Below SideBar.js: