>>> import pandas as pd
>>> df=pd.Series(['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo'])
>>> df.value_counts()
foo    5
bar    3
dtype: int64
>>> max(df.value_counts())
5

>>> import pandas as pd
>>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo']})
>>> groups = df.groupby('A')
>>> groups['A'].count()
A
bar    3
foo    5
Name: A, dtype: int64
>>> max(groups['A'].count())
5

data=['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo']
data_dict=dict()
for d in data:
    if d in data_dict.keys():
        data_dict[d]+=1
    else:
        data_dict[d]=1
max(data_dict.values())

Python中的结构化数据分析利器-Pandas简介
pandas入门
《利用python进行数据分析》读书笔记--第五章 pandas入门