How to read every file in folder to dataframe named after filename and overlay column names? - pandas

Question

I am working on a project where I am downloading public data from (http://pdata.hcad.org/download/) and more particularly downloading the zip files "real_acct_ownership" and "real_building_land".
Each of these zip files contains data on homes built in the houston area, such as addresses, fixtures, sq ft, etc.
My goal is to organize the data so that all the files in the zip folder are data frames indexable by the column "account".
I am running into the issue as to how to create a function or for loop that will read and write the data into a data frame based on file name and how to overlay column names as the data in the zip folders does not contain the column names. The column names can be found in the access zip folder at the top left hand corner labeled "access.zip" of the website.
In my code so far I am calling each file from the above two folders and specifying each column name. I want this to be a iterative process as I will have to do this for other counties and would like a way to create a loop over the files in the folder.
my code so far with NO loops:
import pandas as pd
fixtures = pd.read_csv('/Users/Desktop/Real_building_land/fixtures.txt',header = None,
encoding= 'cp037', error_bad_lines=False, sep='\t')
real_acct =pd.read_csv('/Users/Desktop/Real_acct_owner/real_acct.txt', header = None,
encoding = 'cp037', error_bad_lines=False, sep='\t')
exterior = pd.read_csv('/Users/Desktop/Real_building_land/exterior.txt', header = None,
encoding = 'cp037', error_bad_lines=False, sep='\t')
fixtures.columns = ('ACCOUNT','BUILDING_NUMBER','FIXTURE_TYPE','FIXTURE_DESCRIPTION','UNITS')
real_acct.columns = ("ACCOUNT","TAX_YEAR","MAILTO","MAIL_ADDR_1","MAIL_ADDR_2","MAIL_CITY","MAIL_STATE",
"MAIL_ZIP","MAIL_COUNTRY","UNDELIVERABLE","STR_PFX" ,"STR_NUM", "STR_NUM_SFX","STR_NAME",
"STR_SFX","STR_SFX_DIR","STR_UNIT","SITE_ADDR_1","SITE_ADDR_2","SITE_ADDR_3","STATE_CLASS",
"SCHOOL_DIST","MAP_FACET","KEY_MAP","NEIGHBORHOOD_CODE","NEIGHBORHOOD_GROUP","MARKET_AREA_1",
"MARKET_AREA_1_DSCR","MARKET_AREA_2","MARKET_AREA_2_DSCR","ECON_AREA","ECON_BLD_CLASS",
"CENTER_CODE","YR_IMPR","YR_ANNEXED","SPLT_DT","DSC_CD","NXT_BUILDING","TOTAL_BUILDING_AREA",
"TOTAL_LAND_AREA","ACREAGE","CAP_ACCOUNT","SHARED_CAD_CODE","LAND_VALUE","IMPROVEMENT_VALUE",
"EXTRA_FEATURES_VALUE" ,"AG_VALUE","ASSESSED_VALUE","TOTAL_APPRAISED_VALUE","TOTAL_MARKET_VALUE",
"PRIOR_LND_VALUE","PRIOR_IMPR_VALUE","PRIOR_X_FEATURES_VALUE","PRIOR_AG_VALUE",
"PRIOR_TOTAL_APPRAISED_VALUE","PRIOR_TOTAL_MARKET_VALUE","NEW_CONSTRUCTION_VALUE",
"TOTAL_RCN_VALUE","VALUE_STATUS","NOTICED","NOTICE_DATE","PROTESTED","CERTIFIED_DATE",
"LAST_INSPECTED_DATE","LAST_INSPECTED_BY","NEW_OWNER_DATE","LEGAL_DSCR_1","LEGAL_DSCR_2",
"LEGAL_DSCR_3","LEGAL_DSCR_4","JURS")
exterior.columns = ("ACCOUNT","BUILDING_NUMBER","EXTERIOR_TYPE","EXTERIOR_DESCRIPTION","AREA")
df = fixtures.merge(real_acct,on='ACCOUNT').merge(exterior,on='ACCOUNT')
#df = df.loc[df['ACCOUNT'] == 10020000015]
print(df.shape)
Code with Few trials with loops nothing worked:
import pandas as pd
import glob
import os
dfs = {os.path.basename(f): pd.read_csv(f, sep='\t', header=None,encoding='cp037',
error_bad_lines=False) for f in glob.glob('/Users/Desktop/Real_building_land/*.txt')}
print(dfs)
path =r'path' # use your path
allFiles = glob.glob(path + "/*.csv")
frame = pd.DataFrame()
list_ = []
for file_ in allFiles:
df = pd.read_csv(file_,index_col=None, header=0)
list_.append(df)
frame = pd.concat(list_)
Thank you in advance.