Pandas: Creating DataFrame from Series

Question

My current code is shown below - I\'m importing a MAT file and trying to create a DataFrame from variables within it:

mat = loadmat(file_path)  # load mat-fi         


        

Answer 1

I guess anther way, possibly faster, to achieve this is 1) Use dict comprehension to get desired dict (i.e., taking 2nd col of each array) 2) Then use pd.DataFrame to create an instance directly from the dict without loop over each col and concat.

Assuming your mat looks like this (you can ignore this since your mat is loaded from file):

In [135]: mat = {'a': np.random.randint(5, size=(4,2)),
   .....: 'b': np.random.randint(5, size=(4,2))}

In [136]: mat
Out[136]: 
{'a': array([[2, 0],
        [3, 4],
        [0, 1],
        [4, 2]]), 'b': array([[1, 0],
        [1, 1],
        [1, 0],
        [2, 1]])}

Then you can do:

In [137]: df = pd.DataFrame ({name:mat[name][:,1] for name in mat})

In [138]: df
Out[138]: 
   a  b
0  0  0
1  4  1
2  1  0
3  2  1

[4 rows x 2 columns]