尝试对 pandas 中的两列进行分组并根据条件返回最大值

Question

I need some help with a dataset that I am trying to perform a .groupby() on to find the .max() consumption value based on Entity and Year .

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The consumption column that I am using to perform the max function, sometimes has the same value for different Year s. When this occurs I would like to return the max Year for that occurrence.

df.groupby(['Entity','Year']).consumption.max().reset_index()

returns

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In the end I would like a DataFrame with ['Entity','Year','consumption'] as the columns and when the consumption is the same for a specific Entity Year pair, to return the highest Year of the two.

Answer 1

I worked up a solution

df4 = df.groupby('Entity').consumption.max().reset_index()
df5 = df4.merge(df, left_on=['Entity', 'consumption'] , right_on=['Entity', 'consumption'])
df5 = df5.groupby(['Entity', 'consumption']).max().reset_index()
df5.head(10)

Unique Countries with max consumption rates, and if the consumption rate was the same year-over-year, return the max year.