python df.iterrows()

#函数功能，遍历data，对data中的每行的取值执行加1操作
def fun(data, add):                  
    for index, row in data.iterrows():   
        #index是一个numpy.int64的类型
        print('index',index)
        print('index.type',type(index))
        #row是一个Series类型，它的index是data的列名
        print('row',row)
        print(type(row))
        print(row.index)
        for col_name in data.columns:
            row[col_name] = add(row[col_name]) 
    return data
inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
df = pd.DataFrame(inp)
for ss in df.iterrows():
    print(ss)
    #ss是一个tuple类型
    print(type(ss))
print('.................')
#第二个参数是一个函数   
temp = fun(df, lambda ele: ele+1 )
#print (temp)

可以查看下运行结果

(0, c1     10
c2    100
Name: 0, dtype: int64)

(1, c1     11
c2    110
Name: 1, dtype: int64)

(2, c1     12
c2    120
Name: 2, dtype: int64)

.................
index 0
index.type 
row c1     10
c2    100
Name: 0, dtype: int64

Index(['c1', 'c2'], dtype='object')
index 1
index.type 
row c1     11
c2    110
Name: 1, dtype: int64

Index(['c1', 'c2'], dtype='object')
index 2
index.type 
row c1     12
c2    120
Name: 2, dtype: int64

Index(['c1', 'c2'], dtype='object')