2024_Ruthe_SND/code/transpose_csv.py

# -*- coding: utf-8 -*-
"""
Created on Mon Mar 18 22:12:25 2024

@author: arefk
"""

import pandas as pd
import os
# Get the directory where the code file is located
code_dir = os.path.dirname(os.path.abspath(__file__))
# Get the parent directory of the code directory
parent_dir = os.path.dirname(code_dir)

# Get the parent directory of the code directory
parent_dir = os.path.dirname(code_dir)

# Read the behavior data CSV file into a Pandas DataFrame
input_file_path_data = os.path.join(parent_dir, 'output',
                                        "Final_Quantitative_output",
                                        'Quantitative_results_from_dwi_processing.csv')
# Read the CSV file
df0 = pd.read_csv(input_file_path_data)

#filter anything?

df = df0[(df0["Qtype"] == "rd") &
         (df0["mask_name"] == "CC_MOp(dilated)_cut.tt") &
         (df0["dialation_amount"] == 0)]
Values = ["Value"]
#%%
# Create an empty DataFrame to store the transposed data
transposed_data = pd.DataFrame()
transpodeCloulmn = "Group"


for vv in Values:
    # Create an empty DataFrame to store the transposed data for this value
    value_transposed_data = pd.DataFrame()

    for group_value in df[transpodeCloulmn].unique():
        # Filter DataFrame for current group value
        filtered_df = df[df[transpodeCloulmn] == group_value]

        # Pivot the DataFrame for current value and group
        pivot_df = pd.pivot_table(filtered_df, values=vv, index="merged_timepoint", columns=["subjectID", transpodeCloulmn])

        # Concatenate pivot_df to value_transposed_data
        value_transposed_data = pd.concat([value_transposed_data, pivot_df], axis=1)

    # Rename the index in value_transposed_data
    value_transposed_data.index.name = vv

    # Concatenate value_transposed_data with transposed_data along the first dimension
    transposed_data = pd.concat([transposed_data, value_transposed_data, pd.DataFrame(index=[vv])])



# Define the output file path
output_file_path = os.path.join(parent_dir, 'output', "Final_Quantitative_output",'Transposed4Prism_FA_CC_MOP_dialated.csv')

transposed_data.to_csv(output_file_path, index=True, header=True)

print("Data restructured and saved successfully.")