Explode dataset based on a specific column in Python

Use df.index.repeat:

repeats = np.where(df['stat'] == 0, 1, df['stat'])
# OR
repeats = df['stat'].clip(lower=1)

out = df.reindex(df.index.repeat(repeats)).reset_index(drop=True)
print(out)

# Output
   id type     date  stat  energy
0  aa   ss  Q1 2022     3      10
1  aa   ss  Q1 2022     3      10
2  aa   ss  Q1 2022     3      10
3  aa   ss  Q2 2022     2      10
4  aa   ss  Q2 2022     2      10
5  bb   uu  Q1 2022     1      15
6  bb   uu  Q2 2022     3      15
7  bb   uu  Q2 2022     3      15
8  bb   uu  Q2 2022     3      15
9  cc   ii  Q1 2022     0       0

Another solution could be

df['stat'] = [[x]*x if x > 0 else [x] for x in df['stat']]
new = df.explode('stat')

Faster and neater way to do it is to use np.repeat

m=df['stat'].ge(1)#Isolate rows to be duplicated
df1 = (pd.DataFrame(np.repeat(df[m].values,df.loc[m,'stat'], axis=0)#convert to numpy array and duplicate conditionally
                    , columns=df.columns)#Convert back to df
       .append(df[~m])#Reappend rows that had had zero dup required
      )
print(df1)