Creating a Column with If-Else-Else Conditions in Pandas

To create a new column based on an if-elif-else condition, there are two main approaches:

Non-Vectorized Approach

This approach involves defining a function that operates on rows:

def f(row):
    if row['A'] == row['B']:
        val = 0
    elif row['A'] > row['B']:
        val = 1
    else:
        val = -1
    return val

Then, apply it to the dataframe along the rows:

df['C'] = df.apply(f, axis=1)

Vectorized Approach

The vectorized approach utilizes np.where to create the new column directly:

df['C'] = np.where(
    df['A'] == df['B'], 0, np.where(
    df['A'] >  df['B'], 1, -1)) 

This approach is more efficient for large datasets.

Here's an example using the provided dataframe:

Input DataFrame

Output DataFrame