我有一个数据集,我想解析它以进行分析。我想拉出特定的列,然后在非统一行之前和之后将它们分开。下面是我的数据的示例:注意中间的三行与其他行的格式不匹配:
1386865618963 1 M subject_avatar 3.636229 1.000000 5.422941 30.200327 0.000000 0.000000
1386865618965 1 M subject_avatar 3.631835 1.000000 5.415390 30.200327 0.000000 0.000000
1386865618966 2 M subject_avatar 3.627432 1.000000 5.407826 30.200327 0.000000 0.000000
1386865618968 1 M subject_avatar 3.625223 1.000000 5.404030 30.200327 0.000000 0.000000
1386865618970 1 M subject_avatar 3.620788 1.000000 5.396411 30.200327 0.000000 0.000000
1386865618970 0 D 4345048336
1386865618970 0 D 4345763672
1386865618971 0 I BOXGEOM (45.0, 0.0, -45.0, 19.0, 3.5, 19.0) {'callback': <bound method YCEnvironment.dropoff of <navigate.YCEnvironment instance at 0x103065440>>, 'cbargs': (0, {'width': 1.75, 'image': <pyepl.display.Image object at 0x102f9da90>, 'height': 4.75, 'volbitSize': (0.5, 0.71999999999999997), 'name': 'Julia'}, {'width': 0.69999999999999996, 'name': 'Flower Patch', 'realpos': (45.0, 0.0, -45.0), 'image': <pyepl.display.Image object at 0x102fc3f50>, 'realsize': (7.0, 3.5, 7.0), 'type': 'store', 'volbitSize': (0.5, 0.5), 'height': 0.34999999999999998}), 'permiable': True} 4926595152
1386865618972 1 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865618992 2 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865618996 1 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865618998 2 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865619002 1 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865619005 1 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
1386865619008 1 M subject_avatar 3.621182 1.000000 5.396492 30.200327 0.000000 0.000000
我之前问了一个问题(Parsing specific columns from a dataset in python)将这些数据解析为列,但是,列只显示列中的项目数而不是项目本身。
我意识到这是两个不同的问题(分成列,在非统一行之前和之后分离),但是对解析的任何帮助都将不胜感激!
答案 0 :(得分:1)
一个直截了当的想法:
您可以预处理原始文件以跳过所有不相关的行,可能是:
with open('raw.txt', 'r') as infile:
f = infile.readlines()
with open('filtered.txt', 'w') as outfile:
for line in f:
if 'subject_avatar' in line: # or other better rules
outfile.write(line)
然后使用filtered.txt
或其他方式处理pandas
干净数据。
with open('d.txt', 'r') as infile:
f = infile.readlines()
with open('filtered_part1.txt', 'w') as outfile:
for i in range(len(f)):
line = f[i]
if line[16] == '0':
i += 1
break
outfile.write(line)
while f[i][16] == '0': # skip a few lines
i += 1
with open('filtered_part2.txt', 'w') as outfile:
while i < len(f):
outfile.write(f[i])
i += 1
这里提供了丑陋但可行的分离。基本上找到0并跳过这些行。
答案 1 :(得分:0)
如果您想省略非均匀线条,您只需检查每一行的长度:
rows = []
for line in lines:
row = line.split()
if len(row) == 10:
rows.append(row)