将Apply功能与shift功能结合使用

Question

I'm trying to iterate thru a dataframe. My goal would be to increase the value in the column loop when in the column rpm the previous row and the actual row aren't equal.

df = pd.DataFrame({'rpm': [5000, 5000, 10000, 10000, 15000, 15000], 
                    'temp': [23, 23, 24, 23, 24, 25]})
df['loop'] = 0

def loop_no(x,y):
    if x.rpm != y.rpm:
        val = y.loop + 1
    else:
        val = x.loop
    return val

df['loop'] = df.apply(lambda x: loop_no(x, x.shift(-1)))

At this point, I get this error:

AttributeError: ("'Series' object has no attribute 'rpm'", u'occurred at index rpm').

When I use axis=1 , I don't get an error. But obviously it shifts then in column direction. So, I don't get the previous line.

df['loop'] = df.apply(lambda x: loop_no(x, x.shift(-1)), axis=1)

Answer 1

IIUC

(df.rpm!=df.rpm.shift(-1)).cumsum()
Out[796]: 
0    0
1    1
2    1
3    2
4    2
5    3
Name: rpm, dtype: int32

More info

df['loop']=(df.rpm!=df.rpm.shift(-1)).cumsum()
df
Out[799]: 
     rpm  temp  loop
0   5000    23     0
1   5000    23     1
2  10000    24     1
3  10000    23     2
4  15000    24     2
5  15000    25     3