Question: ```
fruit   year     value 
apple   1950      2
apple   1951      3
apple   1952      3
apple   1953      4
apple   1954      5
apple   1955      4
banana  1950     333
banana  1951     335 

```

How do i add a boolean if the value is lower than the value for the row above, per fruit? And if so the average of the previous 5 years

```
Expected Output
fruit   year     value  lower_than_before  5 year avg
apple   1950      2
apple   1951      3
apple   1952      3
apple   1953      4
apple   1954      5
apple   1955      4       True                 3.4
banana  1950     333
banana  1951     335 

```

Answer: 
Try this:

```
g = df.groupby('fruit')
df['lower_than_before'] = g['value'].diff().lt(0)
df['5 year avg'] = g['value'].apply(lambda x: x.rolling(5).mean().shift().where(df['lower_than_before'].cummax()))
df

```

Output:

```
    fruit  year  value  lower_than_before  5 year avg
0   apple  1950      2              False         NaN
1   apple  1951      3              False         NaN
2   apple  1952      3              False         NaN
3   apple  1953      4              False         NaN
4   apple  1954      5              False         NaN
5   apple  1955      4               True         3.4
6  banana  1950    333              False         NaN
7  banana  1951    335              False         NaN

```
Use shift function and handle the NaN, something like this:

```
df['lower_than_before'] = np.where((df.value - df.value.shift(1)) < 0, True, '')

df['5 year avg'] = np.where(df.lower_than_before=='True', df.value.rolling(window=5, min_periods=0).mean().shift(1), '')

```

Output:

```
    fruit  year  value lower_than_before 5 year avg
0   apple  1950      2                             
1   apple  1951      3                             
2   apple  1952      3                             
3   apple  1953      4                             
4   apple  1954      5                             
5   apple  1955      4              True        3.4
6  banana  1950    333                             
7  banana  1951    335                             

```