Question

this is my code to predict a housing price based on data but i get a lot errors, how do i resolve all these errors

9]: import seaborn as sns from sklearn.linear model import LinearRegression 20]: import numpy as np import matplotlib.pyplot as plt %matplotlib inline import pandas as pd data- pd.read_csv('C:\\Users \\Downloads \\house-prices -advanced-regression-techniques\\test.csv) I data 20]: ScreenPorch PoolArea PoolQC Fence Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape LandContour Utilities NaN MnPry 120 Lvl AlPub Pave NaN Reg 20 RH 80.0 11622 0 1461 C NaN NaN Lv AllPub 14267 Pave NaN IR1 20 RL 81.0 1 1462 NaN MnPry AIPub 0 Lv IR1 74.0 13830 Pave NaN 60 RL 2 1463 NaN 9978 Pave 0 0 NaN Lvl AllPub NaN IR1 60 78.0 RL 1464 NaN NaN AlIPub 144 IR1 HLS 5005 Pave NaN 43.0 120 RL 4 1465 NaN 0 NaN Lv AllPub IR1 10000 Pave NaN RL 75.0 60 5 1466 NaN GdPry C AllPub IR1 Lvl Pave NaN NaN 7980 20 RL 6 1467 NaN C NaN Lv AIPub NaN IR1 8402 Pave 63.0 RL 60 7 1468 NaN NaN C Lvl AlIPub NaN Reg 85.0 Pave 10176 RL 20 8 1469 0 NaN MnPry Reg AlIlPub Lv Pave NaN 8400 70.0 RL 20 9 1470 NaN NaN Lvl AIPub IR1 NaN 5858 Pave 26.0 RH 120 10 1471

Answer 1

In the line df_train_original=pd.read_csv :

use df_train_original.data in subsequent steps OR change the "cols_train" to cols_train

Subsequent errors are result of df_train which is not defined unless these errors are removed.