Python not saving output file from script

[shaanali]

Need help understanding why my Python script is not saving an output file in the designated folder. Please let me know if you have any recommendations.

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import pandas as pd   folder_path = r'T:\04. Testing\3. Wear Testing\TESTS\CKUW\180604 OP STRAPLESS\Survey Response Data/' mapping_path = folder_path + 'Survey_MappingTable Strapless.xlsx'   # Read mapping table mapping = pd.ExcelFile(mapping_path) mapping.sheet_names # ['SurveyInfo', 'Question Mapping', 'Answer Mapping'] # Transform sheets to 3 tables (surveyinfo, Q_mapping, A_mapping) surveyinfo = mapping.parse("SurveyInfo") Q_mapping = mapping.parse("Question Mapping", skiprows = 2) A_mapping = mapping.parse("Answer Mapping", skiprows = 3)   # Get input file name and read the data. Table name is df. input_file_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Input File Name','Value'].to_string(index=False)   path = r'T:\04. Testing\3. Wear Testing\TESTS\CKUW\180604 OP STRAPLESS\Survey Response Data/'+input_file_name df = pd.read_csv(path,header=None,engine='python') # ,encoding='utf-8'  Tried this as a way to fix but it didn't work # Fill in previous colunmn names if blank, using the preceeding header df.iloc[0] = df.iloc[0].fillna(method='ffill')   # Read the count of columns n_col = len(df.iloc[0]) n_respondent = len(df)-2 c_name = [] for i in range(n_col): # Multiple columns; each columns with differnt single answer. and the question text is to combine the category ex. support, comfort, are both in the satisfaction category etc. # If it's satisfaction question, concatenate first row and second row     if "satisfaction" in df.iloc[0][i]:         c_name.append(df.iloc[0][i]+df.iloc[1][i])     elif "functionality" in df.iloc[0][i]:         c_name.append(df.iloc[0][i]+df.iloc[1][i])     elif ("shape" in df.iloc[0][i]) and ("please specify" in df.iloc[1][i]):         c_name.append(df.iloc[0][i]+df.iloc[1][i])     elif ("room in the cup" in df.iloc[0][i]) and ("please specify" in df.iloc[1][i]):         c_name.append(df.iloc[0][i]+df.iloc[1][i])       # - in the column header which is part of the question and part of the response     elif ("wire" in df.iloc[0][i]) and ("Response" not in df.iloc[1][i]):         if "-" in df.iloc[1][i]:             c_name.append(df.iloc[0][i]+df.iloc[1][i][df.iloc[1][i].find("-")+2:])         else:             c_name.append(df.iloc[0][i]+df.iloc[1][i])         for j in range(n_respondent):             if pd.notnull(df.iloc[j+2,i]) and "please specify" not in df.iloc[1,i]:                 df.iloc[j+2,i] = df.iloc[1,i][:df.iloc[1][i].find("-")-1]               # Multiple columns; each columns with differnt single answer. and the question text is not to combine the category. # Use to combine band and cup size     elif "size bra do you typically wear?" in df.iloc[0][i]:         c_name.append(df.iloc[0][i])         for j in range(n_respondent):             if pd.notnull(df.iloc[j+2,i]):                 df.iloc[j+2,i] = df.iloc[1,i] + df.iloc[j+2,i] # Single answer to the question; or multiple answers to the question but the answer is the same as the column header     else:         c_name.append(df.iloc[0][i])   # Make the column names as the first row df.columns = c_name   # Drop the first and second rows df2 = df.drop(df.index[[0,1]])   # Transform the wide dataset to a long dataset; r = list(range(10))+list(range(17,20))  # skipping "What size bra do you typically wear? (only select one size)" df_long = pd.melt(df2,id_vars = list(df.columns[r]), var_name = 'Question', value_name = 'Answer')   # Delete rows with null value to answer df_long_notnull = df_long[pd.notnull(df_long['Answer'])]   # Make typically wear as a column dimension sizewear = df_long_notnull.loc[df_long_notnull['Question'] == 'What size bra do you typically wear? (Only select one size)'] sizewear2 = sizewear[['Respondent ID','Collector ID','Email Address','Answer']] sizewear2.columns = ['Respondent ID','Collector ID','Email Address','What size bra do you typically wear?'] df_long_notnull2 = df_long_notnull[df_long_notnull['Question'] != 'What size bra do you typically wear? (Only select one size)'] df_final = pd.merge(df_long_notnull2, sizewear2, how='left', on=['Respondent ID','Collector ID','Email Address'])   # Join Answer description mapping table df_full = pd.merge(df_final, A_mapping, how='left', left_on = ['Question','Answer'], right_on = ['Question','Answer Description']) df_full.loc[df_full['Answer_y'].isnull(),'Answer_y'] = df_full['Answer_x'] df_full.loc[df_full['Answer Description'].isnull(),'Answer Description'] = df_full['Answer_x'] df_full = df_full.drop(labels = ['Answer_x'], axis=1) df_full = df_full.rename(columns = {'Answer_y':'Answer','Answer Description':'Answer Desc'})       # Join Question Mapping table df_full = pd.merge(df_full,Q_mapping, how='left', left_on = ['Question'], right_on = ['Raw Column Name']) df_full = df_full.drop(labels = ['Raw Column Name'], axis=1)   # Get Survey Info product_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Product Name','Value'].to_string(index=False)   if "," in surveyinfo.loc[surveyinfo['Parameter Name']=='Style Number','Value'].item():     style_number = surveyinfo.loc[surveyinfo['Parameter Name']=='Style Number','Value'].to_string(index=False).split(',')     style_number = [s.strip() for s in style_number] else:     style_number = surveyinfo.loc[surveyinfo['Parameter Name']=='Style Number','Value'].to_string(index=False)   if "," in surveyinfo.loc[surveyinfo['Parameter Name']=='Style Name','Value'].item():     style_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Style Name','Value'].to_string(index=False).split(',')     style_name = [s.strip() for s in style_name] else:     style_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Style Name','Value'].to_string(index=False)   # get survey information survey_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Survey Name','Value'].to_string(index=False) survey_id = surveyinfo.loc[surveyinfo['Parameter Name']=='Survey ID','Value'].item() survey_year = surveyinfo.loc[surveyinfo['Parameter Name']=='Survey Year','Value'].item() survey_mo = surveyinfo.loc[surveyinfo['Parameter Name']=='Survey Month','Value'].item() output_file_name = surveyinfo.loc[surveyinfo['Parameter Name']=='Output File Name','Value'].to_string(index=False)   # adding columns for survey information df_full['Product Name'] = product_name df_full['Survey Name'] = survey_name df_full['Survey ID'] = survey_id df_full['Survey Year'] = survey_year df_full['Survey Month'] = survey_mo   ### create a table with style_number and style_name if type(style_name) == list:     style_t = pd.DataFrame(list(zip(style_name, style_number)), columns = list(["Style_Name","Style_Number"]))     df_full = pd.merge(df_full, style_t, how='left', left_on = ['Which style did you receive?'], right_on = ['Style_Name']) else:     df_full['Style Name'] = style_name     df_full['Style Number'] = style_number         # Identify the path for saving output file path_out = 'T:/04. Testing/3. Wear Testing/PROJECTS/CKUW/Bras/Strapless Bra Survey/Survey Response Data/'+output_file_name   # Save as comma separated csv file df_full.to_csv(path_out, sep=',', index = False)

Error:
runfile('T:/04. Testing/3. Wear Testing/TESTS/CKUW/180604 OP STRAPLESS/Python Code/StraplessBra_comments_OPStrapless.py')

[shaanali]

Checked to make sure the directory is linked to correct folder/file path but still seem to be having the same issue.