combine df script with command line args and added method
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scripts/combine_dfs.py
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301
scripts/combine_dfs.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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'''
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Created on Tue Aug 6 12:56:03 2019
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@author: tanu
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'''
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# FIXME: change filename 4 (mcsm normalised data)
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# to be consistent like (pnca_complex_mcsm_norm.csv) : changed manually, but ensure this is done in the mcsm pipeline
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#=============================================================================
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# Task: combine 4 dfs with aa position as linking column
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# This is done in 2 steps:
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# merge 1: of 3 dfs (filenames in lowercase)
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# <gene.lower()>_dssp.csv
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# <gene.lower()>_kd.csv
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# <gene.lower()>_pnca_rd.csv
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# merge 2: of 2 dfs
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# pnca_complex_mcsm_norm.csv (!fix name)
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# output df from merge1
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# Input: 3 dfs
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# <gene.lower()>_dssp.csv
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# <gene.lower()>_kd.csv
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# <gene.lower()>_pnca_rd.csv
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# pnca_complex_mcsm_norm.csv (!fix name)
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# Output: .csv of all 4 dfs combined
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# useful link
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# https://stackoverflow.com/questions/23668427/pandas-three-way-joining-multiple-dataframes-on-columns
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#=============================================================================
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#%% load packages
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import sys, os
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import pandas as pd
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#import numpy as np
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import argparse
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#=======================================================================
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#%% specify input and curr dir
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homedir = os.path.expanduser('~')
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# set working dir
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os.getcwd()
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os.chdir(homedir + '/git/LSHTM_analysis/meta_data_analysis')
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os.getcwd()
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#=======================================================================
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#%% command line args
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arg_parser = argparse.ArgumentParser()
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#arg_parser.add_argument('-d', '--drug', help='drug name', default = 'pyrazinamide')
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#arg_parser.add_argument('-g', '--gene', help='gene name', default = 'pncA') # case sensitive
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arg_parser.add_argument('-d', '--drug', help='drug name', default = 'pyrazin')
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arg_parser.add_argument('-g', '--gene', help='gene name', default = 'pn') # case sensitive
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args = arg_parser.parse_args()
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#=======================================================================
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#%% variable assignment: input and output
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#drug = 'pyrazinamide'
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#gene = 'pncA'
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#gene_match = gene + '_p.'
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drug = args.drug
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gene = args.gene
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#==========
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# data dir
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#==========
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datadir = homedir + '/' + 'git/Data'
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#=======
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# input
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#=======
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indir = datadir + '/' + drug + '/' + 'output'
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in_filename1 = 'pnca_dssp.csv'
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in_filename2 = 'pnca_kd.csv'
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in_filename3 = 'pnca_rd.csv'
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#in_filename4 = 'mcsm_complex1_normalised.csv' # FIXNAME
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in_filename4 = 'pnca_complex_mcsm_norm.csv'
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infile1 = indir + '/' + in_filename1
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infile2 = indir + '/' + in_filename2
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infile3 = indir + '/' + in_filename3
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infile4 = indir + '/' + in_filename4
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print('\nInput path:', indir
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, '\nInput filename1:', in_filename1
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, '\nInput filename2:', in_filename2
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, '\nInput filename3:', in_filename3
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, '\nInput filename4:', in_filename4
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, '\n===================================================================')
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#=======
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# output
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#=======
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outdir = datadir + '/' + drug + '/' + 'output'
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out_filename = gene.lower() + '_mcsm_struct_params.csv'
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outfile = outdir + '/' + out_filename
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print('Output filename:', out_filename
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, '\nOutput path:', outdir
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, '\n===================================================================')
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#%% end of variable assignment for input and output files
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#=======================================================================
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#%% function/methd to combine 4 dfs
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def combine_dfs(dssp_csv, kd_csv, rd_csv, mcsm_csv, out_combined_csv):
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"""
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Combine 4 dfs
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@param dssp_df: csv file (output from dssp_df.py)
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@type dssp_df: string
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@param kd_df: csv file (output from kd_df.py)
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@type ks_df: string
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@param rd_df: csv file (output from rd_df.py)
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@type rd_df: string
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# FIXME
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@param mcsm_df: csv file (output of mcsm pipeline)CHECK}
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@type mcsm_df: string
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@param out_combined_csv: csv file output
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@type out_combined_csv: string
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@return: none, writes combined df as csv
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"""
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#========================
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# read input csv files to combine
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#========================
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dssp_df = pd.read_csv(dssp_csv, sep = ',')
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kd_df = pd.read_csv(kd_csv, sep = ',')
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rd_df = pd.read_csv(rd_csv, sep = ',')
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mcsm_df = pd.read_csv(mcsm_csv, sep = ',')
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print('Reading input files:'
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, '\ndssp file:', dssp_csv
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, '\nNo. of rows:', len(dssp_df)
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, '\nNo. of cols:', len(dssp_df.columns)
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, '\nColumn names:', dssp_df.columns
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, '\n==================================================================='
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, '\nkd file:', kd_csv
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, '\nNo. of rows:', len(kd_df)
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, '\nNo. of cols:', len(kd_df.columns)
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, '\nColumn names:', kd_df.columns
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, '\n==================================================================='
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, '\nrd file:', rd_csv
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, '\nNo. of rows:', len(rd_df)
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, '\nNo. of cols:', len(rd_df.columns)
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, '\nColumn names:', rd_df.columns
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, '\n==================================================================='
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, '\nrd file:', mcsm_csv
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, '\nNo. of rows:', len(mcsm_df)
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, '\nNo. of cols:', len(mcsm_df.columns)
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, '\nColumn names:', mcsm_df.columns
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, '\n===================================================================')
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#========================
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# merge 1 (combined_df1)
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# concatenating 3dfs:
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# dssp_df, kd_df, rd_df
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#========================
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print('starting first merge...\n')
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# checking no. of rows
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print('Checking if no. of rows of the 3 dfs are equal:\n'
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, len(dssp_df) == len(kd_df) == len(rd_df)
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, '\nReason: fasta files and pdb files vary since not all pos are part of the structure'
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, '\n===================================================================')
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# variables for sanity checks
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expected_rows_df1 = max(len(dssp_df), len(kd_df), len(rd_df))
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# beware of harcoding! used for sanity check
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ndfs = 3
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ncol_merge = 1
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offset = ndfs- ncol_merge
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expected_cols_df1 = len(dssp_df.columns) + len(kd_df.columns) + len(rd_df.columns) - offset
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print('Merge 1:'
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, '\ncombining 3dfs by commom col: position'
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, '\nExpected nrows in combined_df:', expected_rows_df1
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, '\nExpected ncols in combined_df:', expected_cols_df1
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, '\nResetting the common col as the index'
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, '\n===================================================================')
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#dssp_df.set_index('position', inplace = True)
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#kd_df.set_index('position', inplace = True)
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#rd_df.set_index('position', inplace =True)
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#combined_df = pd.concat([dssp_df, kd_df, rd_df], axis = 1, sort = False).reset_index()
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#combined_df.rename(columns = {'index':'position'})
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combined_df1 = pd.concat(
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(my_index.set_index('position') for my_index in [dssp_df, kd_df, rd_df])
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, axis = 1, join = 'outer').reset_index()
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# sanity check
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print('Checking dimensions of concatenated df1...')
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if len(combined_df1) == expected_rows_df1 and len(combined_df1.columns) == expected_cols_df1:
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print('PASS: combined df has expected dimensions'
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, '\nNo. of rows in combined df:', len(combined_df1)
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, '\nNo. of cols in combined df:', len(combined_df1.columns)
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, '\n===============================================================')
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else:
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print('FAIL: combined df does not have expected dimensions'
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, '\nNo. of rows in combined df:', len(combined_df1)
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, '\nNo. of cols in combined df:', len(combined_df1.columns)
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, '\n===============================================================')
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#========================
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# merge 2 (combined_df2)
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# concatenating 2dfs:
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# mcsm_df, combined_df1 (result of merge1)
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# sort the cols
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#========================
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print('starting second merge...\n')
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# rename col 'Position' in mcsm_df to lowercase 'position'
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# as it matches the combined_df1 colname to perfom merge
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#mcsm_df.columns
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#mcsm_df.rename(columns = {'Position':'position'}) # not working!
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# copy 'Position' column with the correct colname
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print('Firstly, copying \'Position\' col and renaming \'position\' to allow merging'
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, '\nNo. of cols before copying: ', len(mcsm_df.columns))
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mcsm_df['position'] = mcsm_df['Position']
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print('No. of cols after copying: ', len(mcsm_df.columns))
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# sanity check
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if mcsm_df['position'].equals(mcsm_df['Position']):
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print('PASS: Copying worked correctly'
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, '\ncopied col matches original column'
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, '\n===============================================================')
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else:
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print('FAIL: copied col does not match original column'
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, '\n================================================================')
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# variables for sanity checks
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expected_rows_df2 = len(mcsm_df)
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# beware of harcoding! used for sanity check
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ndfs = 2
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ncol_merge = 1
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offset = ndfs - ncol_merge
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expected_cols_df2 = len(mcsm_df.columns) + len(combined_df1.columns) - offset
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print('Merge 2:'
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, '\ncombining 2dfs by commom col: position'
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, '\nExpected nrows in combined_df:', expected_rows_df2
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, '\nExpected ncols in combined_df:', expected_cols_df2
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, '\n===================================================================')
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combined_df2 = mcsm_df.merge(combined_df1, on = 'position')
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# sanity check
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print('Checking dimensions of concatenated df2...')
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if len(combined_df2) == expected_rows_df2 and len(combined_df2.columns) == expected_cols_df2:
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print('PASS: combined df2 has expected dimensions'
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, '\nNo. of rows in combined df:', len(combined_df2)
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, '\nNo. of cols in combined df:', len(combined_df2.columns)
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, '\n===============================================================')
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else:
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print('FAIL: combined df2 does not have expected dimensions'
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, '\nNo. of rows in combined df:', len(combined_df2)
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, '\nNo. of cols in combined df:', len(combined_df2.columns)
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, '\n===============================================================')
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#===============
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# writing file
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#===============
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print('Writing file:'
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, '\nFilename:', out_combined_csv
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# , '\nPath:', outdir
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, '\nExpected no. of rows:', len(combined_df2)
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, '\nExpected no. of cols:', len(combined_df2.columns)
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, '\n=========================================================')
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combined_df2.to_csv(out_combined_csv, header = True, index = False)
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#%% end of function
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#=======================================================================
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#%% call function
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#combine_dfs(infile1, infile2, infile3, infile4, outfile)
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#=======================================================================
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def main():
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print('Combining 4 dfs:\n'
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, in_filename1, '\n'
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, in_filename2, '\n'
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, in_filename3, '\n'
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, in_filename4, '\n'
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, 'output csv:', out_filename)
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combine_dfs(infile1, infile2, infile3, infile4, outfile)
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print('Finished Writing file:'
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, '\nFilename:', out_filename
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, '\nPath:', outdir
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## , '\nNo. of rows:', ''
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## , '\nNo. of cols:', ''
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, '\n===========================================================')
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if __name__ == '__main__':
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main()
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#%% end of script
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#=======================================================================
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