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pandas: How to get the most frequent item in pandas series?

How can I get the most frequent item in a pandas series?

Consider the series s

s = pd.Series("1 5 3 3 3 5 2 1 8 10 2 3 3 3".split()).astype(int)

The returned value should be 3

like image 777
mommomonthewind Avatar asked Aug 27 '18 12:08

mommomonthewind


2 Answers

You can just use pd.Series.mode and extract the first value:

res = s.mode().iloc[0]

This not necessarily inefficient. As always, test with your data to see what suits.

import numpy as np, pandas as pd
from scipy.stats.mstats import mode
from collections import Counter

np.random.seed(0)

s = pd.Series(np.random.randint(0, 100, 100000))

def jez_np(s):
    _, idx, counts = np.unique(s, return_index=True, return_counts=True)
    index = idx[np.argmax(counts)]
    val = s[index]
    return val

def pir(s):
    i, r = s.factorize()
    return r[np.bincount(i).argmax()]

%timeit s.mode().iloc[0]                 # 1.82 ms
%timeit pir(s)                           # 2.21 ms
%timeit s.value_counts().index[0]        # 2.52 ms
%timeit mode(s).mode[0]                  # 5.64 ms
%timeit jez_np(s)                        # 8.26 ms
%timeit Counter(s).most_common(1)[0][0]  # 8.27 ms
like image 118
jpp Avatar answered Sep 20 '22 12:09

jpp


Use value_counts and select first value by index:

val = s.value_counts().index[0]

Or Counter.most_common:

from collections import Counter

val = Counter(s).most_common(1)[0][0]

Or numpy solution:

_, idx, counts = np.unique(s, return_index=True, return_counts=True)
index = idx[np.argmax(counts)]
val = s[index]
like image 35
jezrael Avatar answered Sep 22 '22 12:09

jezrael