Shape of passed values blah indices imply blah
So I after implementing @Quang Hoang's suggestion  panda.reshape(array_name, (-1, 78)) on x_test, y_test and x_train this finally converted all nessasary arrays into the required 2D format.
I am attempting to pass my custom dataset which is loaded in from a CSV file using 
panda.readcsv() through sklearns MLPRegressor. 
My initial error was my 1D array needed to become a 2D array. Expected 2D array, got 1D array instead: array=[0. 0. 1. ... 0. 0. 1.].
So I used panda.reshape(x_test, (-1, 1)) on both the x_test and y_train to solve this issue. However this now presents me with the following error.
Shape of passed values is (16209258, 1), indices imply (207811, 78)
Have looked around a few other posts without success.