返回不在另一个数据帧范围内的数据帧的范围

Question

我有以下主数据帧：

first.seqnames  first.start first.end   first.width first.strand    second.seqnames second.start    second.end  second.width    second.strand
0   chr1    346212  346975  7   *   chr1    10882   10888   7   *
1   chr1    3135476 3136100 2   *   chr1    10890   10891   2   *
2   chr1    11473   11484   12  *   chr1    10893   10904   12  *
3   chr1    5388140 5388730 2   *   chr1    11096   11097   2   *
4   chr1    346213  346984  68  *   chr1    11202   11269   68  *

我想返回在以下数据帧范围内不存在的上述数据帧的行：

first.seqnames  first.start first.end   3   4   5
3503    chr1    346213  346984  .   0   .
3504    chr1    3135466 3136202 .   0   .
3505    chr1    3190760 3191377 .   0   .
3506    chr1    3354604 3355258 .   0   .
3507    chr1    5388136 5388749 .   0   .

这里，第一个数据帧的"first.start"one_answers"first.end"不应存在于范围(34621346984(内，。。。。。。。

我尝试了以下代码，它创建了内存和时间复杂性。甚至结果也不准确。这里，一些df1范围正好存在于df2范围和一些重叠之间。在重叠的情况下，可以忽略范围。

def range_subset(range1, range2):
"""Whether range1 is a subset of range2."""
if not range1:
return True  # empty range is subset of anything
if not range2:
return False  # non-empty range can't be subset of empty range
if len(range1) > 1 and range1.step % range2.step:
return False  # must have a single value or integer multiple step
return range1.start in range2 and range1[-1] in range2
for a,b in zip(df1['first.start'], df1['first.end']):
for i,j in zip(df2['first.start'], df2['first.end']):
if(range_subset(range(a, b), range(i, j)) == True):
print(a,b)

输出：

first.seqnames  first.start first.end   first.width first.strand    second.seqnames second.start    second.end  second.width    second.strand
0   chr1    346212  346975  7   *   chr1    10882   10888   7   *
2   chr1    11473   11484   12  *   chr1    10893   10904   12  *

Answer 1

我最初从(df1['first.start'], df1['first.end']) and (df2['first.start'], df2['first.end'])创建了元组对，以便应用range((函数。然后，我提出了一个条件，即df1_ranges是否在df2_ranges的范围内。这里的边缘情况是df1['first.start'] = df1['first.end']。我从迭代中收集过滤后的索引，然后传递到df1中。

df2_lst=[]
for i,j in zip(temp_df2['first.start'], temp_df2['first.end']):
df2_lst.append(i)
df2_lst.append(j)
df1_lst=[]
for i,j in zip(df1['first.start'], df1['first.end']):
df1_lst.append(i)
df1_lst.append(j)
def range_subset(range1, range2):
"""Whether range1 is a subset of range2."""
if not range1:
return True  # empty range is subset of anything
if not range2:
return False  # non-empty range can't be subset of empty range
if len(range1) > 1 and range1.step % range2.step:
return False  # must have a single value or integer multiple step
return range1.start in range2 and range1[-1] in range2
##### FUNCTION FOR CREATING CHUNKS OF LISTS ####
def chunks(lst, n):
"""Yield successive n-sized chunks from lst."""
for i in range(0, len(lst), n):
yield lst[i],lst[i+1]
df1_lst2 = list(chunks(df1_lst,2))
df2_lst2 = list(chunks(df2_lst,2))
indices=[]
for idx,i in enumerate(df1_lst2): #main list
x,y = i
for j in df2_lst2: #filter list
m,n = j
if((x!=y) & (range_subset(range(x,y), range(m,n)))): #checking if the main list exists in the filter range or not
indices.append(idx) #collecting the filtered indices
df1.iloc[indices]