pandas adding new column to existing dataframe with condition

Question

I have a pandas data frame like so.

fruit	year	price
apple	2018	4
apple	2019	3
apple	2020	5
plum	2019	3
plum	2020	2

and I want to add column [last_year_price]

please help......

Answer 1

For this, you can use groupby and shift:

df['last_year_price'] = df.groupby('fruit').shift(1).price

Answer 2

You can use the shift function:

df['last_year_price'] = df.sort_values(by=['year'], ascending=True).groupby(['fruit'])['price'].shift(1)

Answer 3

Use DataFrameGroupBy.idxmax for rows with maximal years and join to oriinal DataFrame:

df = df.merge(df.loc[df.groupby('fruit')['year'].idxmax(), ['fruit','price']].rename(columns={'price':'last_year_price'}), on='fruit', how='left')
print (df)
   fruit  year  price  last_year_price
0  apple  2018      4                5
1  apple  2019      3                5
2  apple  2020      5                5
3   plum  2019      3                2
4   plum  2020      2                2