问题
I'm curently learnig python and pandas (this question is based on a pevious post but with an additional query); at the moment have the 2 columns containing numeric sequences (ascending and/or descending) as described below:
Col 1: (col1 numeric incrememt and/or decrement = 1)
1
2
3
5
7
8
9
Col 2: (Col2 numeric increment and/or decrement = 4)
113
109
105
90
94
98
102
Need to extract the numeric ranges from both columns and print them according to the sequence break occurance on any of those 2 columns and the result should be as follow:
1,3,105,113
5,5,90,90
7,9,94,102
Already received a very useful way to do it using python's pandas library by @MaxU where it generates the numeric ranges based on the breaks detected on both columns using a criteria of col1 and col2 = increase and/or decreases by 1.
How can I extract numeric ranges from 2 columns and print the range from both columns as tuples?
The unique difference on this case is that the increment/decrement criteria applied for both columns are different for each one of them.
回答1:
Try this:
In [42]: df
Out[42]:
Col1 Col2
0 1 113
1 2 109
2 3 105
3 5 90
4 7 94
5 8 98
6 9 102
In [43]: df.groupby(df.diff().abs().ne([1,4]).any(1).cumsum()).agg(['min','max'])
Out[43]:
Col1 Col2
min max min max
1 1 3 105 113
2 5 5 90 90
3 7 9 94 102
Explanation: our goal is to group those rows with the increment/decrement [1,4] for Col1, Col2 correspondingly:
In [44]: df.diff().abs()
Out[44]:
Col1 Col2
0 NaN NaN
1 1.0 4.0
2 1.0 4.0
3 2.0 15.0
4 2.0 4.0
5 1.0 4.0
6 1.0 4.0
In [45]: df.diff().abs().ne([1,4])
Out[45]:
Col1 Col2
0 True True
1 False False
2 False False
3 True True
4 True False
5 False False
6 False False
In [46]: df.diff().abs().ne([1,4]).any(1)
Out[46]:
0 True
1 False
2 False
3 True
4 True
5 False
6 False
dtype: bool
In [47]: df.diff().abs().ne([1,4]).any(1).cumsum()
Out[47]:
0 1
1 1
2 1
3 2
4 3
5 3
6 3
dtype: int32
来源：https://stackoverflow.com/questions/40607709/how-to-extract-numeric-ranges-from-2-columns-containig-numeric-sequences-and-pri