You'll have to convert this wide data to the long format on your own.
I think dplyr in R has a function called gather, which could help with this. However, you won't find any pre existing solutions.

Hi alioudosdiallo !
This code below should work! I've added in some data cleaning as well, which you can ignore if you'd like! This code works when the data is exactly as you laid out.
library(dplyr)
library(tidyr)
qual_pivot <- function(qualtrics){
  q <- 
    #Once Run you can select a file
    read.csv(file.choose())
  qual_c <- 
    qual %>% 
    # Remove Annoying Two Rows
    filter(Finished == "TRUE") %>% 
    # Remove 'Unneeded' Columns
    select(!StartDate:Duration..in.seconds.) %>% 
    select(!Finished:UserLanguage) %>% 
    # flag empty condition rows
    mutate_all(na_if,"") 
  # Subset Conditions A
  qual_a  <-  
    qual_c %>% 
    # Get Only A Conditions
    filter(Condition == "A") %>% 
    # Remove Duplicates
    select(!Q1.1:Q2.1)
  # Subset Conditions B
  qual_b <- 
    qual_c %>%
    # Get Only B Conditions
    filter(Condition == "B") %>% 
    # Remove Duplicates
    select(!Q1:Q2) %>% 
    # Rename Columns
    dplyr::rename(Q1 = Q1.1,
                  Q2 = Q2.1)
  # Combine and Pivot
  qual_full <- 
    # Combine
    bind_rows(qual_a,qual_b) %>% 
    # Combine the Questions
    # Changes Values to Q.Response
    # Change Question number to Q.Number
    pivot_longer(cols = starts_with("Q"),
                 values_to = "Q.Response",
                 names_to = "Q.Number")
  }
# Make sure to assign to something! Ex. data <- qual_pivot()
qual_pivot()
Starting with this:

The data will look like this:
Hope this helps!

Wow, excellent! Thank you DavidBrocker! This helps a lot!

https://community.qualtrics.com/XMcommunity/discussion/comment/45669#Comment_45669You're welcome! If this ends up working out for you, could you mark this as the answer?

This is a late response, but as an FYI for others, if you use R, the packages qualtRics and excluder are extremely useful to deal with some of the data cleaning steps, as well as recoding or not recoding answers.

qualtRics is definitely the way to go.  You can pretty easily remove the labels in rows 2 and 3 above. Heck, you download your survey and run t-tests, logistical regressions, etc., in the same script if you wanted.  

I made a video about this on YouTube since I didn’t see any others. It’s mostly catered to noobs, so I didn’t go into a lot of detail (I may in future videos if the video does well).  I mostly cover how to get the key info from the Qualtrics API and how to put it into R so you can export it. A link to my code is provided in the video description. 

Python has a good module that connects to the Qualtrics API too.