likert | Do not use averages with Likert scale data

I'm trying to plot a heat table with the likert package. Following code can be reproduced:

I'm using Plotly to produce a similar graph from https://plotly.com/python/horizontal-bar-charts/, section "Color Palette for Bar Chart".

Here's the code, based on the reference link, but with few modifications (values in x_data and showlegend = True) to show my problem:

I have survey data (picture sample below) I'm working with to find 95% confidence intervals for. The Q#d columns (Q1d, Q2d, etc.) each correspond to different questions on the survey (Likert scale with results dichotomized, 1 = yes, 0 = no). The intervention column describes whether the results were before intervention (FALSE) or after intervention (TRUE). What I want to do is get the 95% confidence intervals on the difference in proportions for each question before and after intervention.

For example, let's say for Q1d the proportion that answered "yes" before intervention is .2 and after the intervention is .5. The difference would be .3 or 30%, and I want to calculate the confidence interval (let's say between 25% and 35%) on the difference. I want to do this for every single question in the survey (all Q1d). I have not been able to find a way to iterate through and do this for all questions (columns). I've written a function that can successfully do it for one column, but iterating through column names isn't working for me, and I don't know how to store the results as a vector/dataframe. I've included the function below. Any guidance?

Thanks so much!!

lets say I have a data frame that looks like this:

I want to create a Vertical Likert Line Chart , is there anyway to plot it by ggplot2 or highcharter ？

here is the example chart:

data example :

A seemingly straightforward task has proven to be really difficult in R. I'm working with survey data containing propositions asking respondents to indicate their level of agreement or disagreement on a 7-point Likert Scale. I'm trying to create frequency tables (see Table 1 below) that show the proportion of respondents in each sex/age group category that selected strongly agreed, slightly agreed, agreed, neutral, etc., in response to each proposition.

How can I create Table 1 from Table 2 (this is the way my current dataframe is setup in R)? In Table 2, the columns headed Q31, Q32, Q33, and Q34 are each separate propositions and the values in the cells are numerical codes for the 7 options on the Likert scale.

Table 1

Table 2

Open to any suggestions, as I've been banging my head against this for too long! Thanks!

I have a survey that was conducted in 3 different classes ( math, phys, bio) at the beginning and at the end of the semester ( pre and post). In the survey, there were 3 groups of questions (A, B, C) and a Likert-type scale. I converted all the answer into the numerical score

I want to test for each course for each question type whether the is a difference in score between pre and post-term survey. I also want to add Bonferroni correction here to account for multiple comparisons:

My data has 5 observations for each statement that the respondent was asked to answer and then the variables 1-5 by respondent ID.

I managed to do a boxplot using base R, but my labels are way too long (5-8 words) and I can't seem to make it work with the par function.

I have a Likert Survey generator where a dynamic number of questions can be entered - then a user goes through and answers each question with 4 radio buttons (Strongly Disagree, Disagree, Agree, Strongly Agree).

I can output them easily enough - but can they be model bound on the post back or do I have to traverse the posted form elements (ie not use model binding)?

I've Googled a lot and can find no solution - is it posible?

Thanks.