your data set :
0 1 2 3 4 5
0 AG 140.089584 18.775135 197.156000 17.526798 258.871000
1 AG 141.777557 14.103220 180.746000 2.285414 245.001000
2 AG 143.463440 15.038719 178.296982 0.344542 242.925000
3 AG 142.214218 14.445769 181.157000 2.383999 245.013000
4 AG 145.964310 13.961549 179.660843 2.026588 243.966000
#for columns
print(df[0])
0 AG
1 AG
2 AG
3 AG
4 AG
print(df[:2]) # you can use like, run for loop upto second line
0 1 2 3 4 5
0 AG 140.089584 18.775135 197.156 17.526798 258.871
1 AG 141.777557 14.103220 180.746 2.285414 245.001
print(df.iloc[1]) #iloc - default indexes (system generated)
print(df.loc[1]) # loc - table indexes or we manually given indexes
0 AG
1 141.777557
2 14.10322
3 180.746
4 2.285414
5 245.001
print(df[3][1]) column x row
180.746
print(df[1][3])
142.21421813964844
print(df[2][:]) all of 2nd column
0 18.775135
1 14.103220
2 15.038719
3 14.445769
print(df[4].iloc[:3]) and print(df[4].loc[:3])
# .loc
0 17.526798 0 17.526798
1 2.285414 1 2.285414
2 0.344542 2 0.344542
3 2.38399