added download and excel data parsing to file

Author: alexandriai168

build/liverpdo/04-experiments-liverpdo.py

@@ -0,0 +1,75 @@
+import pandas as pd
+import numpy as np
+import os
+import math
+import argparse
+import synapseclient 
+
+
+def download_experiments_data(synID:str , save_path:str = None, synToken:str = None):
+    """ 
+    Download omics data from Synapse at synapseID syn66401303. Requires a synapse token, which requires you to make a Synapse account
+    and create a Personal Access Token.  More information here: https://help.synapse.org/docs/Managing-Your-Account.2055405596.html#ManagingYourAccount-PersonalAccessTokens 
+    
+    Parameters
+    ----------
+    synID : string
+        SynapseID of dataset to download. Default is synapseID of the omics dataset.
+        
+    save_path : string
+        atal path where the downloaded file will be saved.
+
+    synToken : string
+        Synapse Personal Access Token of user.  Requires a Synapse account. More information at: https://help.synapse.org/docs/Managing-Your-Account.2055405596.html#ManagingYourAccount-PersonalAccessTokens
+        
+    Returns
+    -------
+    experiments_filepath : string
+        Path to downloaded file
+
+    """
+    
+    syn = synapseclient.Synapse() 
+    syn.login(authToken=synToken) 
+    
+    # Obtain a pointer and download the data 
+    downloaded_data = syn.get(entity=synID, downloadLocation = save_path) 
+
+    # Get the path to the local copy of the data file 
+    experiments_filepath = downloaded_data.path
+    
+    return(experiments_filepath)
+
+
+
+def parse_experiments_excel_sheets(first_file_path, second_file_path):
+    # read in the excel files
+    first_exp_excel = pd.ExcelFile(open(first_file_path, 'rb'))
+    first_experiments_dict = pd.read_excel(first_exp_excel, sheet_name=None, header=None)
+    rest_exp_excel = pd.ExcelFile(open(second_file_path, 'rb'))
+    rest_experiments_dict = pd.read_excel(rest_exp_excel, sheet_name=None, header=None)
+    # use for loops to interate through the dictionaries, melt the df's into longer df's instead of matrices, and then concat
+    list_of_exp_excels = [first_experiments_dict,rest_experiments_dict]
+    full_df_list = []
+    for dictionary in list_of_exp_excels:
+        list_of_finished_dfs = []
+        for experiment_key in dictionary.keys():
+            one_sample_df = dictionary[experiment_key] # get 1 df from the df dictionary
+            one_sample_df = one_sample_df.fillna(value={0:"concentration"}) # for many of the pages, they didn't write "concentration" but just left it blank. fill these na's with "concentration"
+            list_of_dfs = [] # initiate empty list of df's for each conc type
+            conc_indexes = one_sample_df[one_sample_df[0] == "concentration"].index.to_list() # get indexes of rows with concentrations in them (these will be column names)
+            conc_indexes = conc_indexes + [one_sample_df.index[-1]+1]
+            for index in range(0,(len(conc_indexes)-1)):
+                one_conc_df = one_sample_df.loc[conc_indexes[index]:(conc_indexes[(index+1)]-1)]
+                one_conc_df.columns = one_conc_df.iloc[0]
+                one_conc_df = one_conc_df[1:]
+                one_conc_df = pd.melt(one_conc_df, id_vars=['concentration'], value_vars=one_conc_df.columns[one_conc_df.columns != 'concentration'])
+                one_conc_df = one_conc_df.rename(columns={"concentration":"drug_id",one_conc_df.columns[1]:"concentration","value":"count"})
+                list_of_dfs.append(one_conc_df)
+            elongated_df = pd.concat(list_of_dfs)
+            elongated_df['sample_name'] = experiment_key
+            list_of_finished_dfs.append(elongated_df)
+        full_experiments_df = pd.concat(list_of_finished_dfs)
+        full_df_list.append(full_experiments_df)
+    experiments_df = pd.concat(full_df_list)
+    return(experiments_df)