Pandas - drop last column of DataFrame

Question

I have a DataFrame and I would like to drop the last column of it. Until now I had just been dropping what I believed to be the final column with

if len(fish_frame.columns) == 4: del fish_frame[3].

Right before this command, however, I drop all columns of NaNs. So that removes column [3] because it is filled with NaNs, so it fails.

I would like to say just drop the final column of the entire DataFrame. I feel like that would work perfectly.

I tried fish_frame([:-1], axis=1) but that's invalid syntax.

Any help would be appreciated thanks.

The DataFrame:

fish_frame after dropna:

                              0        1      2           4
0                         #0721      NaN    NaN         NaN
1                       GBE COD      746  $2.00   $1,492.00
2                       GBW COD   13,894  $0.50   $6,947.00
3                       GOM COD       60  $2.00     $120.00
4            GB WINTER FLOUNDER   94,158  $0.25  $23,539.50
5           GOM WINTER FLOUNDER    3,030  $0.50   $1,515.00
6                   GBE HADDOCK   18,479  $0.02     $369.58
7                   GOM HADDOCK        0  $0.02       $0.00
8                   GBW HADDOCK  110,470  $0.02   $2,209.40
9                          HAKE      259  $1.30     $336.70
10                       PLAICE    3,738  $0.40   $1,495.20
11                      POLLOCK    3,265  $0.02      $65.30
12               WITCH FLOUNDER    1,134  $1.30   $1,474.20
13                       SNE YT    1,458  $0.65     $947.70
14                        GB YT    4,499  $0.70   $3,149.30
15                      REDFISH      841  $0.02      $16.82
16  54 DAS @ $8.00/DAY = 432.00      NaN    NaN        None

Answer 1

Use iloc and list indexing

fish_frame = fish_frame.iloc[:, :-1]

                              0        1      2
0                         #0721      NaN    NaN
1                       GBE COD      746  $2.00
2                       GBW COD   13,894  $0.50
3                       GOM COD       60  $2.00
4            GB WINTER FLOUNDER   94,158  $0.25
5           GOM WINTER FLOUNDER    3,030  $0.50
6                   GBE HADDOCK   18,479  $0.02
7                   GOM HADDOCK        0  $0.02
8                   GBW HADDOCK  110,470  $0.02
9                          HAKE      259  $1.30
10                       PLAICE    3,738  $0.40
11                      POLLOCK    3,265  $0.02
12               WITCH FLOUNDER    1,134  $1.30
13                       SNE YT    1,458  $0.65
14                        GB YT    4,499  $0.70
15                      REDFISH      841  $0.02
16  54 DAS @ $8.00/DAY = 432.00      NaN    NaN

Answer 2

If you want to drop the last column

df = df.iloc[:,:-1]

if particular column needs to be dropped with index

df = df.drop(df.columns[column_index],axis=1)

with column name

df = df.drop(['column_name'],axis =1)

Answer 3

Use drop with the columns index:

fish_frame = fish_frame.drop(fish_frame.columns[-1],axis=1)

Output:

                              0        1      2
0                         #0721      NaN    NaN
1                       GBE COD      746  $2.00
2                       GBW COD   13,894  $0.50
3                       GOM COD       60  $2.00
4            GB WINTER FLOUNDER   94,158  $0.25
5           GOM WINTER FLOUNDER    3,030  $0.50
6                   GBE HADDOCK   18,479  $0.02
7                   GOM HADDOCK        0  $0.02
8                   GBW HADDOCK  110,470  $0.02
9                          HAKE      259  $1.30
10                       PLAICE    3,738  $0.40
11                      POLLOCK    3,265  $0.02
12               WITCH FLOUNDER    1,134  $1.30
13                       SNE YT    1,458  $0.65
14                        GB YT    4,499  $0.70
15                      REDFISH      841  $0.02
16  54 DAS @ $8.00/DAY = 432.00      NaN    NaN