如何用条件求和行?(熊猫)

Question

我有这个df

data={"col1":["n",3,"n",5,"n",2,6],
"col2":[4,"n",4,6,"n","n",5],
"col3":[7,"n",0,"n","n",6,7],
"col4":[14,11,22,8,6,"n",9],
"col5":[0,5,"n",3,8,"n",9],
"type":["B","n","n","n","B","A","B"],
"number":["one","n","n","n","one","two","n"]}
df=pd.DataFrame.from_dict(data)
print(df)

我喜欢有一个新的列，总和所有"；n〃；在每一排/可能是这样的：

df["sum_n"]=df[["list of all col"]].sum("n",axis=)

它需要看起来像这个

data={"col1":["n",3,"n",5,"n",2,6],
"col2":[4,"n",4,6,"n","n",5],
"col3":[7,"n",0,"n","n",6,7],
"col4":[14,11,22,8,6,"n",9],
"col5":[0,5,"n",3,8,"n",9],
"type":["B","n","n","n","B","A","B"],
"number":["one","n","n","n","one","two","n"],
"sum_n":[1,4,4,3,3,3,1]}
df=pd.DataFrame.from_dict(data)
df

Answer 1

Do：

df['sum_n'] = df.eq('n').sum(1)
print(df)

输出

col1 col2 col3 col4 col5 type number  sum_n
0    n    4    7   14    0    B    one      1
1    3    n    n   11    5    n      n      4
2    n    4    0   22    n    n      n      4
3    5    6    n    8    3    n      n      3
4    n    n    n    6    8    B    one      3
5    2    n    6    n    n    A    two      3
6    6    5    7    9    9    B      n      1