Using Pandas to Find Minimum Values of Grouped Rows

Question

This might be a trivial question but I\'m still trying to figure out pandas/numpy.

So, suppose I have a table with the following structure:

group_id          


        

Answer 1

• focus on just ['col1', 'col2', 'col3']
• see if they are equal to 1 with eq(1) equivalent to == 1
• see if any are equal to one along axis=1 with any(1)
• use loc to make assignment

---

anyone = df[['col1', 'col2', 'col3']].eq(1).any(1)
df.loc[anyone, 'A'] = np.nan

numpy equivalent

anyone = (df[['col1', 'col2', 'col3']].values == 1).any(1)
df.A = np.where(anyone, np.nan, df.A)

Answer 2

To get the minimum of column A for each group use transform

df.groupby('group_id')['A'].transform('min')