data_Q1 = pd.read_csv("LoanStats_2018Q1.csv", skiprows=1, skipfooter=2, engine='python')
data_Q2 = pd.read_csv("LoanStats_2018Q2.csv", skiprows=1, skipfooter=2, engine='python')
data_Q3 = pd.read_csv("LoanStats_2018Q2.csv", skiprows=1, skipfooter=2, engine='python')
data_Q4 = pd.read_csv("LoanStats_2018Q2.csv", skiprows=1, skipfooter=2, engine='python')

frames = [data_Q1,data_Q2,data_Q3,data_Q4]

result = pd.concat(frames)

id  member_id   loan_amnt   funded_amnt funded_amnt_inv term    int_rate    installment grade   sub_grade   ... orig_projected_additional_accrued_interest  hardship_payoff_balance_amount  hardship_last_payment_amount    debt_settlement_flag    debt_settlement_flag_date   settlement_status   settlement_date settlement_amount   settlement_percentage   settlement_term
0   NaN NaN 35000   35000   35000.0 60 months   13.58%  806.79  C   C2  ... NaN NaN NaN N   NaN NaN NaN NaN NaN NaN
1   NaN NaN 24000   24000   24000.0 36 months   21.85%  914.71  D   D5  ... NaN NaN NaN N   NaN NaN NaN NaN NaN NaN
2   NaN NaN 2500    2500    2500.0  36 months   6.71%   76.87   A   A3  ... NaN NaN NaN N   NaN NaN NaN NaN NaN NaN