value_counts()函数

value_counts函数用于统计dataframe或series中不同数或字符串出现的次数

ascending=True时,按升序排列.

normalize=True时,可计算出不同字符出现的频率,画柱状图统计时可以用到.

# trian中标签的比例
label_proportion = train['label'].value_counts(normalize=True).reset_index().sort_values(by=['index'])
#    index     label
# 5      1  0.029851
# 2      2  0.199005
# 0      3  0.298507
# 1      4  0.248756
# 3      5  0.149254
# 4      6  0.074627

df1= DataFrame( {"a":[3,4,5,6,2,3,4,4], "b":[2,4,5,6,5,4,3,4]} )
print(df1)
#dataframe要借助apply来应用value_counts()
print(df1.apply(pd.value_counts))
# map中括号内是series类型,key是a列的数,values是出现的次数
print(df1['a'].map(df1['a'].value_counts()))

print(df1['a'].value_counts()) #加括号时可直接统计出a列每个元素出现的次数

   a  b
0  3  2
1  4  4
2  5  5
3  6  6
4  2  5
5  3  4
6  4  3
7  4  4
   a  b
2  1  1
3  2  1
4  3  3
5  1  2
6  1  1
0    2
1    3
2    1
3    1
4    1
5    2
6    3
7    3
Name: a, dtype: int64

输出

https://blog.csdn.net/qq_20412595/article/details/79921849

https://blog.csdn.net/qq_42665335/article/details/81177699