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......
为此,您可以使用groupby
和shift
:
df['last_year_price'] = df.groupby('fruit').shift(1).price
您可以使用移位功能:
df['last_year_price'] = df.sort_values(by=['year'], ascending=True).groupby(['fruit'])['price'].shift(1)
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
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