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I want to convert this file to pandas dataframe.
import pandas as pd
import scipy.io
mat = scipy.io.loadmat('cardio.mat')
cardio_df = pd.DataFrame(mat)
I get this error :
Exception: Data must be 1-dimensional
842
Load data from a MAT-fileThe function loadmat loads all variables stored in the MAT-file into a simple Python data structure, using only Python's dict and list objects. Numeric and cell arrays are converted to row-ordered nested lists. Arrays are squeezed to eliminate arrays with only one element.
mat-file is a compressed binary file. It is not possible to open it with a text editor (except you have a special plugin as Dennis Jaheruddin says). Otherwise you will have to convert it into a text file (csv for example) with a script. This could be done by python for example: Read .
It seems mat is a dict containing X of shape (1831, 21), y with shape (1831, 1), and some metadata. Assuming X is the data and y are the labels for the same, you can stack them horizontally with np.hstack and load them into pandas:
In [1755]: mat = scipy.io.loadmat('cardio.mat')
In [1758]: cardio_df = pd.DataFrame(np.hstack((mat['X'], mat['y'])))
In [1759]: cardio_df.head()
Out[1759]:
0 1 2 3 4 5 6 \
0 0.004912 0.693191 -0.203640 0.595322 0.353190 -0.061401 -0.278295
1 0.110729 -0.079903 -0.203640 1.268942 0.396246 -0.061401 -0.278295
2 0.216546 -0.272445 -0.203640 1.050988 0.148753 -0.061401 -0.278295
3 0.004912 0.727346 -0.203640 1.212171 -0.683598 -0.061401 -0.278295
4 -0.100905 0.363595 1.321366 1.027120 0.141359 -0.061401 -0.278295
In [1760]: cardio_df.shape
Out[1760]: (1831, 22)
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