How can I concatenate np.arrays into a DataFrame in for loop?

I am getting error while appending np.arrays into a DataFrame. Each np.array has varying length, so np.vstack will not work. What is the best way to deal with this?

Also, "y" needs to be sorted accordingly and the data I processed comes with different initial point --- I think it is easier to sort in DataFrame, but I haven't got to that point yet. Unless there's other suggestion? Thank you!

# For example:# In "n" loop, I will get y0, x0. Then in "n+1" loop, I will get y1, x1 and "n+1" loop to get y2, x2, etc.y0 = np.array([6,7,8,9])y1 = np.array([1,2,3,4,5])x0 = np.array([600, 700, 800, 900])x1 = np.array([0.1, 0.2, 0.3, 0.4, 0.5])# Ultimately, the DataFrame should return this:print(df)   y    x  0  1    0.11  2    0.22  3    0.33  4    0.44  5    0.55  6    6006  7    7007  8    8008  9    900

My current code:

df = pd.DataFrame({"data_y":[], "data_x":[]})for i in range(100):    # Initiate lists    data_y = []    data_x = []    # Data processed using list    data_y, data_x = ....    # Convert list to np.array    data_y, data_x = ....    # Compile data to DataFrame    df["data_y"] = data_y.tolist()    df["data_x"] = data_x.tolist()# ValueError: Length of values (111) does not match length of index (256)