load matfile in python using scipy.io and pandas dataframe in python, how to solve error:valueerror: per-column arrays must each be 1-dimensional in python

To load a MATLAB .mat file in Python using scipy.io and convert it to a Pandas DataFrame, you can follow these steps:

1. Import the required libraries:

main.py
import scipy.io
import pandas as pd
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2. Load the .mat file using scipy.io.loadmat() function:

main.py
data = scipy.io.loadmat('your_file.mat')
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3. Extract the variables from the loaded .mat file using their respective keys:

main.py
variable_1 = data['variable_name_1']
variable_2 = data['variable_name_2']
# Repeat this for each variable you want to extract
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4. Ensure that each variable extracted is 1-dimensional using ndim attribute:

main.py
if variable_1.ndim > 1:
    variable_1 = variable_1.flatten()
# Repeat this for each variable
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5. Create a Pandas DataFrame with the extracted variables:

main.py
df = pd.DataFrame({
    'variable_1': variable_1,
    'variable_2': variable_2,
    # Add more columns if necessary
})
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You can then work with the df DataFrame as per your requirements.

If you encounter a ValueError: per-column arrays must each be 1-dimensional error, it means that one of the extracted variables is not 1-dimensional. Make sure to use the flatten() method to convert any multi-dimensional arrays to 1-dimensional before creating the DataFrame.