sorting - Python Pandas sort by column, but keep index same -

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i created data frame consists of country, deal_category, , some_metric.

it looks 

    country     metric_count    channel 0   country1    123472          c1 1   country1    159392          c2 2   country2    14599           c3 3   country2    17382           c4

i indexed according country , channel using command

df2 = df.set_index(["country", "channel"])

this creates following dataframe. 

            metric_count country     channel      country1    category1   12347             category2   159392             category3   14599             category4   17382  country2    category1   1234

here's want do. i'd keep structure same , sort according metric counts. in other words, i'd display each country, top 3 channels based on metric count.

for instance, i'd dataframe display each country, top 3 categories ordered descending metric_counts. 

country2    top category1   12355555             top category2   159393             top category3   16759

i've tried sorting first, indexing, resulting data frame no longer partitions based on country. tips appreciated. thanks!

after taxing experimentation, able wanted. outline steps below

  1. groupby country

    group = df.groupby("country")

    at high-level, indicates @ each country differently. our goal determine top 3 metric counts , report corresponding channel. this, apply sort resulting data-frame , return top 3 results. can defining sort function returns top 3 results , use apply function in pandas. indicates panda "i want apply sort function each of our groups , return top 3 results each group".

  2. sort , return top 3 

    sort_function = lambda x: x.sort("metric_count", ascending = false)[:3] desired_df = group.apply(sort_function)

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