Sorting and Top N

Ordering a table, and taking the few rows that matter.

sort_values returns a new table

by names the column, ascending chooses the direction, and the original is untouched.

import pandas as pd

df = pd.DataFrame({"name": ["Ada", "Alan"], "score": [92, 79]})
print(df.sort_values("score", ascending=False)["name"].tolist())

nlargest says what you meant

Sorting the whole table to look at three rows is more work than the question needs, and nlargest reads better besides.

import pandas as pd

df = pd.DataFrame({"name": ["Ada", "Grace", "Alan"], "score": [92, 88, 79]})
print(df.nlargest(2, "score")["name"].tolist())

Exercise

Try It Yourself

Write top_names(df, n) returning the names of the n highest scorers, best first.

import pandas as pd

def top_names(df, n):
    # The n best, highest first.
    return []

print(top_names(pd.DataFrame({"name": ["Ada", "Alan"], "score": [92, 79]}), 1))

Press Run to see output

Check Your Understanding

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