mapup / mapup-data-assessment-f Goto Github PK

The dataset "dataset-1.csv" should have 342 rows, and currently only has 341.

Would you like us to update the missing value as 0, or something else?

.

Question 1: Distance Matrix Calculation
Create a function named calculate_distance_matrix that takes the dataset-3.csv as input and generates a DataFrame representing distances between IDs.

The resulting DataFrame should have cumulative distances along known routes, with diagonal values set to 0. If distances between toll locations A to B and B to C are known, then the distance from A to C should be the sum of these distances. Ensure the matrix is symmetric, accounting for bidirectional distances between toll locations (i.e. A to B is equal to B to A).

Since one of the element in the dataset-3.csv is missing that is 1001400 id_end and that is the reason why the matrices formed is not symmetrical.

Here is the step by step procedure:

1. Create the repo and make it private
2. Go to that repo and you can find an option called "import code" (found in bottom)
3. Now paste the link "https://github.com/mapup/MapUp-Data-Assessment-F" and import the code
4. Go to repo and there will be a option Add file click it and drag and drop your folder
5. Don't forgot add collaborators (which can be found under settings)

As you defined in the question we have to create four new columns ('start_day','start_time','end_day','end_time') . For these new columns how we can assign values in them , because we have to take the data from question4 and the output is using these four columns to make output
@Venkatesh1618,@saransh-mapup

Dear Sir,

Files are not opening. Unable to see excel assessment questions. Also for data sets 2 and 3 data sets not opening.

Kindly resolve the issues.

Regards,

Priya G

I have completed it and how to submit it.

weights_h = [[random.random() for e in range(len(inputs[0]))] for e in range(hiden_neurons)]

class Solution {
public:
int numBusesToDestination(vector<vector>& routes, int source,
int target) {
if (source == target)
return 0;

unordered_map<int, vector<int>> graph;  // {route: [buses]}
unordered_set<int> usedBuses;

for (int i = 0; i < routes.size(); ++i)
  for (const int route : routes[i])
    graph[route].push_back(i);

int ans = 0;
queue<int> q{{source}};

while (!q.empty()) {
  ++ans;
  for (int sz = q.size(); sz > 0; --sz) {
    const int route = q.front();
    q.pop();
    for (const int bus : graph[route])
      if (usedBuses.insert(bus).second)
        for (const int nextRoute : routes[bus]) {
          if (nextRoute == target)
            return ans;
          q.push(nextRoute);
        }
  }
}

return -1;

}
};

why every person is forking this repo
instead of cloning/copy/download the repo

they said in the form that you need to create a clone (which is not fork) and make it private (and add contributors). then add your submission into this clone, rather than forking it and committing it !

im i wrong or am i right?

Excel Assessment of Anjali Mahajan
C:\Users\hp\Desktop\Excel Assessment of Anjali Mahajan.xlsm

def check(letter):
list_of_vowels = ['a', 'e', 'i', 'o', 'u']
if letter in list_of_vowels:
return True
else:
return False
letters = ['u', 'a', 'q', 'c', 'i', 'd', 'z', 'p', 'e']
filtered_object = filter(check, letters)
print("The type of returned object is: ", type(filtered_object))
filtered_list = list(filtered_object)
print("The list of vowels is: ", filtered_list)

Dear MapUp Team,

I hope this message finds you well. I am currently working through the Python Task 1 of the assessment and have encountered a point of uncertainty that I would like to clarify regarding Question 1, titled "Car Matrix Generation".

The instructions specify that we are to create a new DataFrame with id_2 values as columns, id_1 values as indices, and car column values populating the matrix. However, I am seeking further guidance on how to handle instances where multiple car values may correspond to the same (id_1, id_2) pair. Could you please advise on the expected behaviour in such a scenario? Should we sum the values, take the average, or perhaps keep the first or last occurrence?

Additionally, I would appreciate if you could confirm whether the diagonal values of the matrix should be set to 0 before or after any aggregation is performed, should such a situation arise.

Understanding the intended approach to these cases will ensure that I adhere to the assessment criteria and that my submission aligns with your expectations.

Thank you for your assistance in this matter. I look forward to your guidance.

Best regards,
yihong1120

0

array = []
matrix = []

x = 0

while(x < 3):
array.append(".")
x += 1

x = 0

while(x < 3):
matrix.append(array)
x += 1