在 DataFrame 中找到最频繁的组合

Question

I have a DataFrame with two columns From and To , and I need to know the most frequent combination of locations From and To .

Example:

From        To
------------------
Home        Office
Home        Office
Home        Office
Airport     Home
Restaurant  Office

Answer 1

if the order does matter:

df['FROM_TO'] = df['FROM'] + df['TO']

df['COUNT'] = 1

df.groupby(['FROM_TO'])['COUNT'].sum()

gives you all the occurrences in one go. Simply take the max to find the largest occurrence.

If the order does matter first sort the values before:

df.loc[:,:] = np.sort(df.values,axis=1) # if the df only consists of the FROM adn TO columns.

Answer 2

You can group by the two columns together and count the number of occurrences of each pair, then sort the pairs by this count.

The following code does the job:

df.groupby(["From", "To"]).size().sort_values(ascending=False)

and, for the example of the question, it returns:

From        To
-----------------------
Home        Office    3
Restaurant  Office    1
Airport     Home      1

Answer 3

IIUC, SeriesGroupBy.value_counts and Series.idxmax

df.groupby('From')['To'].value_counts().idxmax()

Output

('Home', 'Office')

in general groupby.value_counts is faster than groupby.size

Another way:

df.apply(tuple, axis=1).value_counts().idxmax()

Or

df.apply(tuple, axis=1).mode()

Output

0    (Home, Office)
dtype: object