[FIXED] How to select some values of a dataframe based on a list of coordinates?

Issue

My inputs are a dataframe and a list of coodinates :

df = pd.DataFrame({
 'col1': ['A', 'B', 'C', 'A', 'G'],
 'col2': ['B', 'E', 'F', 'F', 'H'],
 'col3': ['C', 'D', 'E', 'A', 'I']})

coords = [(2, 0), (3, 2)]

print(df)

  col1 col2 col3
0    A    B    C
1    B    E    D
2    C    F    E
3    A    F    A
4    G    H    I

Basically I'm trying to select some cells in df based on the coordinates X and Y that we take from the list coords. And since I may need to invert the selection, I created a function with a boolean so it has two workflows. Until now I was able to produce one of the two selections (the easy one):

def select(df, coords, inverted=False):
    if inverted is True:
        for c in coords:
            df.iat[c[0], c[1]] = ''
            
    return df

Can you guys show me how make the other one ?

My expected output is one of these two :

# inverted = False
  col1 col2 col3
0             
1             
2    C        
3              A
4              

# inverted = True
  col1 col2 col3
0    A    B    C
1    B    E    D
2         F    E
3    A    F    
4    G    H    I

Solution

If you convert your coords to a tuple of transposed coordinates, you can use that directly as an index into an ndarray. You can use that to either set values in a new array to '' or the corresponding value from the input dataframe, dependent on the value of inverted:

def select(df, coords, inverted=False):
    coords = tuple(np.array(coords).T)
    out = data = np.array(df)
    if inverted:
        out[coords] = ''
    else:
        out = np.full(data.shape, '')
        out[coords] = data[coords]
    return pd.DataFrame(out, columns=df.columns)

select(df, coords, True)
select(df, coords, False)

Output:

  col1 col2 col3
0    A    B    C
1    B    E    D
2         F    E
3    A    F
4    G    H    I

  col1 col2 col3
0
1
2    C
3              A
4

Answered By - Nick