load matfile in python using scipy.io and pandas dataframe in python

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

1. Import the required libraries:

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

main.py
data = loadmat('your_file.mat')
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3. Extract the variables from the loaded .mat file:

main.py
variables = data.keys()
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4. Convert the variables into Pandas DataFrame:

main.py
df = pd.DataFrame({var: data[var] for var in variables})
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Here is the complete code:

main.py
import pandas as pd
from scipy.io import loadmat

# Load the .mat file
data = loadmat('your_file.mat')

# Extract the variables from the loaded .mat file
variables = data.keys()

# Convert the variables into a Pandas DataFrame
df = pd.DataFrame({var: data[var] for var in variables})
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Make sure to replace 'your_file.mat' with the actual file path of your .mat file. This code will create a Pandas DataFrame with the variables from the .mat file as columns.

Note: The keys extracted from the .mat file will include additional metadata. If you want to filter out only the variables, you can modify step 3 to: variables = [var for var in data.keys() if not var.startswith('__')].