Python熊猫统计每列中的出现次数

Question

I am new to pandas. Can someone help me in calculating frequencies of values for each columns.

Dataframe:

id|flag1|flag2|flag3|  
---------------------
1 |  1  |   2 |   1 |  
2 |  3  |   1 |   1 |  
3 |  3  |   4 |   4 |  
4 |  4  |   1 |   4 |  
5 |  2  |   3 |   2 |  

I want something like

id|flag1|flag2|flag3|  
---------------------
1 |  1  |   2 |   2 |  
2 |  1  |   1 |   1 |  
3 |  2  |   1 |   0 |  
4 |  1  |   1 |   2 |  

Explanation - id 1 has 1 value in flag1, 2 values in flag2 and 2 values in flag3.

Answer 1

First filter only flag columns by filter or removing id column and then apply function value_counts , last replace NaN s to 0 and cast to int s:

df = df.filter(like='flag').apply(lambda x: x.value_counts()).fillna(0).astype(int)
print (df)
   flag1  flag2  flag3
1      1      2      2
2      1      1      1
3      2      1      0
4      1      1      2

Or:

df = df.drop('id', 1).apply(lambda x: x.value_counts()).fillna(0).astype(int)
print (df)
   flag1  flag2  flag3
1      1      2      2
2      1      1      1
3      2      1      0
4      1      1      2

Thank you, Bharath for suggestion:

df = df.filter(like='flag').apply(pd.Series.value_counts()).fillna(0).astype(int)