使用 python 将文件文本的一部分读入 pandas 数据帧
Read portion of file text into pandas dataframe with python
例如，我有以下格式的数据文本：
HEADER NODE DATA, AIR
-10000, 15., -1.0
HEADER CONDUCTOR DATA, AIR
1, AIR.10000, S25D.1, 56.84441 $ AIR CONV
2, AIR.10000, S25D.2, 56.45712 $ AIR CONV
3, AIR.10000, S25D.3, 53.35623 $ AIR CONV
4, AIR.10000, S25D.4, 45.09633 $ AIR CONV
5, AIR.10000, S25D.9, 77.00067 $ AIR CONV
6, AIR.10000, S25D.10, 80.35013 $ AIR CONV
7, AIR.10000, S25D.11, 50.4933 $ AIR CONV
8, AIR.10000, S25D.12, 91.61026 $ AIR CONV
9, AIR.10000, S25D.13, 53.75025 $ AIR CONV
10, AIR.10000, S25D.14, 75.68577 $ AIR CONV
11, AIR.10000, S25D.15, 110.0111 $ AIR CONV
12, AIR.10000, S25D.16, 114.7913 $ AIR CONV
13, AIR.10000, S25D.17, 81.12207 $ AIR CONV
14, AIR.10000, S25D.18, 72.80061 $ AIR CONV
15, AIR.10000, S25D.19, 72.21327 $ AIR CONV
16, AIR.10000, S25D.20, 90.99183 $ AIR CONV
17, AIR.10000, S25D.21, 66.35648 $ AIR CONV
18, AIR.10000, S25D.22, 76.9787 $ AIR CONV
19, AIR.10000, S25D.23, 52.46601 $ AIR CONV
20, AIR.10000, S25D.24, 68.30105 $ AIR CONV
21, AIR.10000, S25D.25, 114.0903 $ AIR CONV
22, AIR.10000, S25D.26, 70.51425 $ AIR CONV
23, AIR.10000, S25D.27, 36.39104 $ AIR CONV
24, AIR.10000, S25D.28, 78.88668 $ AIR CONV
25, AIR.10000, S25D.29, 70.77477 $ AIR CONV
26, AIR.10000, S25D.30, 87.04871 $ AIR CONV
27, AIR.10000, S25D.31, 64.50918 $ AIR CONV
28, AIR.10000, S25D.32, 76.20373 $ AIR CONV
29, AIR.10000, S25D.33, 90.69899 $ AIR CONV
30, AIR.10000, S25D.34, 83.89708 $ AIR CONV
31, AIR.10000, S25D.35, 88.59924 $ AIR CONV
32, AIR.10000, S25D.36, 72.06826 $ AIR CONV
33, AIR.10000, S25D.65, 157.6095 $ AIR CONV
34, AIR.10000, S25D.66, 140.3513 $ AIR CONV
35, AIR.10000, S25D.67, 215.1395 $ AIR CONV
36, AIR.10000, S25D.68, 131.7191 $ AIR CONV
37, AIR.10000, S25D.69, 173.7129 $ AIR CONV
38, AIR.10000, S25D.70, 106.8654 $ AIR CONV
39, AIR.10000, S25D.71, 153.2247 $ AIR CONV
40, AIR.10000, S25D.72, 151.2406 $ AIR CONV
41, AIR.10000, S25D.73, 136.0113 $ AIR CONV
42, AIR.10000, S25D.74, 217.2005 $ AIR CONV
43, AIR.10000, S25D.75, 121.0298 $ AIR CONV
44, AIR.10000, S25D.76, 178.8008 $ AIR CONV
45, AIR.10000, S25D.77, 160.7517 $ AIR CONV
46, AIR.10000, S25D.78, 132.528 $ AIR CONV
47, AIR.10000, S25D.79, 126.503 $ AIR CONV
48, AIR.10000, S25D.80, 223.1756 $ AIR CONV
49, AIR.10000, S25D.81, 151.6868 $ AIR CONV
50, AIR.10000, S25D.82, 176.8964 $ AIR CONV
51, AIR.10000, S25D.83, 155.6967 $ AIR CONV
52, AIR.10000, S25D.84, 153.6341 $ AIR CONV
53, AIR.10000, S25D.85, 110.9477 $ AIR CONV
54, AIR.10000, S25D.86, 165.114 $ AIR CONV
55, AIR.10000, S25D.87, 139.9079 $ AIR CONV
56, AIR.10000, S25D.88, 137.9431 $ AIR CONV
57, AIR.10000, S25D.89, 138.1562 $ AIR CONV
58, AIR.10000, S25D.90, 204.7094 $ AIR CONV
59, AIR.10000, S25D.91, 159.8541 $ AIR CONV
60, AIR.10000, S25D.92, 174.5026 $ AIR CONV
61, AIR.10000, S25D.93, 160.5398 $ AIR CONV
62, AIR.10000, S25D.94, 143.0478 $ AIR CONV
63, AIR.10000, S25D.95, 175.8055 $ AIR CONV
64, AIR.10000, S25D.96, 99.97353 $ AIR CONV
65, AIR.10000, S25D.97, 119.0528 $ AIR CONV
66, AIR.10000, S25D.98, 147.533 $ AIR CONV
67, AIR.10000, S25D.99, 122.7583 $ AIR CONV
68, AIR.10000, S25D.100, 191.2955 $ AIR CONV
69, AIR.10000, S25D.101, 197.3013 $ AIR CONV
70, AIR.10000, S25D.102, 173.0556 $ AIR CONV
71, AIR.10000, S25D.103, 193.2726 $ AIR CONV
72, AIR.10000, S25D.104, 128.1502 $ AIR CONV
73, AIR.10000, S25D.105, 102.519 $ AIR CONV
74, AIR.10000, S25D.106, 180.8979 $ AIR CONV
75, AIR.10000, S25D.107, 160.9948 $ AIR CONV
76, AIR.10000, S25D.108, 197.6314 $ AIR CONV
77, AIR.10000, S25D.109, 162.5766 $ AIR CONV
78, AIR.10000, S25D.110, 143.3984 $ AIR CONV
79, AIR.10000, S25D.111, 265.7273 $ AIR CONV
80, AIR.10000, S25D.112, 90.36677 $ AIR CONV
81, AIR.10000, S25D.113, 146.033 $ AIR CONV
82, AIR.10000, S25D.114, 182.0126 $ AIR CONV
83, AIR.10000, S25D.115, 142.1242 $ AIR CONV
84, AIR.10000, S25D.116, 156.4711 $ AIR CONV
85, AIR.10000, S25D.117, 263.3278 $ AIR CONV
86, AIR.10000, S25D.118, 133.7923 $ AIR CONV
87, AIR.10000, S25D.119, 134.4939 $ AIR CONV
88, AIR.10000, S25D.120, 87.09295 $ AIR CONV
89, AIR.10000, S25D.121, 168.8858 $ AIR CONV
90, AIR.10000, S25D.122, 133.792 $ AIR CONV
91, AIR.10000, S25D.123, 194.2227 $ AIR CONV
92, AIR.10000, S25D.124, 116.8372 $ AIR CONV
93, AIR.10000, S25D.125, 125.5161 $ AIR CONV
94, AIR.10000, S25D.126, 54.22872 $ AIR CONV
我想将其读入 pandas 数据框以供进一步分析。
如您所见，header 对于每个子集和数据格式都是不同的。
我想使用 re 模块和 pandas 将数据读入框架，但不知道如何以最有效的方式进行。
正如您所看到的，AIR 字符串对于两个 header 都是通用的。在完整文件中会有更多这样的字符串，所以我想为每个字符串创建一个 class 属性（节点，导体）将是一个具有相应数据的 pd 数据帧。
任何帮助将不胜感激:)
编辑：
按照亚历山大的建议，我稍微修改了一段代码，但仍然没有找到将数据放入 class
的方法
# import modules
import pandas as pd
from io import StringIO
class TableData:
def __init__(self,name):
self.name = name
self.nodes_table = self.add_nodes()
self.conductor_table = self.add_conductors()
def add_nodes(self):
pass
def add_conductors(self):
pass
out = []
submodels = set()
with open("case1.cc", "r") as f:
sub = ""
for line in f.readlines():
if ("VARIABLES" in line) or ("OPTIONS" in line): # skip non relevant
# blocks
continue
if line.startswith('C'): # skip comments line
continue
if ("HEADER" in line) and ("DATA" in line):
# Get submodel name and add to set if not present
submodels.add(line.split(',')[1])
# Get type of data
type = line.split()[1]
# Skip first insertion
if sub != "":
out.append(sub)
sub = ""
else: sub += line
# Append last sub (outside for loop)
out.append(sub)
# "out" is a list of pandas dataframes
out = [pd.read_csv(StringIO(o), sep=r",*\s{2,}", header=None, engine="python") for o in out]
还有更完整的示例文件：
HEADER OPTIONS
C SINDA Data generated with Thermal Desktop 6.0 Patch 2
C Generated on Fri Sep 01 14:39:30 2017
C From file: thermal.dwg
C Case Set: Case Set 1
C TDUNITS, Energy = J
C TDUNITS, Time = sec
C TDUNITS, Temp = C
C TDUNITS, Mass = kg
C TDUNITS, Length = m
C TDUNITS, Orbit = km
C TDUNITS, Pressure = Pa
C TDUNITS, Force = N
C TDUNITS, Angle = Degrees
C TDUNITS, Volt = volt
C TDUNITS, Current = amp
C TDUNITS, Resistance = ohm
HEADER NODE DATA, AIR
-10000, 15., -1.0
HEADER CONDUCTOR DATA, AIR
1, AIR.10000, S25D.1, 56.84441 $ AIR CONV
2, AIR.10000, S25D.2, 56.45712 $ AIR CONV
3, AIR.10000, S25D.3, 53.35623 $ AIR CONV
4, AIR.10000, S25D.4, 45.09633 $ AIR CONV
5, AIR.10000, S25D.9, 77.00067 $ AIR CONV
6, AIR.10000, S25D.10, 80.35013 $ AIR CONV
7, AIR.10000, S25D.11, 50.4933 $ AIR CONV
8, AIR.10000, S25D.12, 91.61026 $ AIR CONV
9, AIR.10000, S25D.13, 53.75025 $ AIR CONV
10, AIR.10000, S25D.14, 75.68577 $ AIR CONV
11, AIR.10000, S25D.15, 110.0111 $ AIR CONV
12, AIR.10000, S25D.16, 114.7913 $ AIR CONV
13, AIR.10000, S25D.17, 81.12207 $ AIR CONV
14, AIR.10000, S25D.18, 72.80061 $ AIR CONV
15, AIR.10000, S25D.19, 72.21327 $ AIR CONV
16, AIR.10000, S25D.20, 90.99183 $ AIR CONV
17, AIR.10000, S25D.21, 66.35648 $ AIR CONV
18, AIR.10000, S25D.22, 76.9787 $ AIR CONV
19, AIR.10000, S25D.23, 52.46601 $ AIR CONV
20, AIR.10000, S25D.24, 68.30105 $ AIR CONV
21, AIR.10000, S25D.25, 114.0903 $ AIR CONV
22, AIR.10000, S25D.26, 70.51425 $ AIR CONV
23, AIR.10000, S25D.27, 36.39104 $ AIR CONV
24, AIR.10000, S25D.28, 78.88668 $ AIR CONV
25, AIR.10000, S25D.29, 70.77477 $ AIR CONV
26, AIR.10000, S25D.30, 87.04871 $ AIR CONV
27, AIR.10000, S25D.31, 64.50918 $ AIR CONV
28, AIR.10000, S25D.32, 76.20373 $ AIR CONV
29, AIR.10000, S25D.33, 90.69899 $ AIR CONV
30, AIR.10000, S25D.34, 83.89708 $ AIR CONV
31, AIR.10000, S25D.35, 88.59924 $ AIR CONV
32, AIR.10000, S25D.36, 72.06826 $ AIR CONV
33, AIR.10000, S25D.65, 157.6095 $ AIR CONV
34, AIR.10000, S25D.66, 140.3513 $ AIR CONV
35, AIR.10000, S25D.67, 215.1395 $ AIR CONV
36, AIR.10000, S25D.68, 131.7191 $ AIR CONV
37, AIR.10000, S25D.69, 173.7129 $ AIR CONV
38, AIR.10000, S25D.70, 106.8654 $ AIR CONV
39, AIR.10000, S25D.71, 153.2247 $ AIR CONV
40, AIR.10000, S25D.72, 151.2406 $ AIR CONV
41, AIR.10000, S25D.73, 136.0113 $ AIR CONV
42, AIR.10000, S25D.74, 217.2005 $ AIR CONV
43, AIR.10000, S25D.75, 121.0298 $ AIR CONV
44, AIR.10000, S25D.76, 178.8008 $ AIR CONV
45, AIR.10000, S25D.77, 160.7517 $ AIR CONV
46, AIR.10000, S25D.78, 132.528 $ AIR CONV
47, AIR.10000, S25D.79, 126.503 $ AIR CONV
48, AIR.10000, S25D.80, 223.1756 $ AIR CONV
49, AIR.10000, S25D.81, 151.6868 $ AIR CONV
50, AIR.10000, S25D.82, 176.8964 $ AIR CONV
51, AIR.10000, S25D.83, 155.6967 $ AIR CONV
52, AIR.10000, S25D.84, 153.6341 $ AIR CONV
53, AIR.10000, S25D.85, 110.9477 $ AIR CONV
54, AIR.10000, S25D.86, 165.114 $ AIR CONV
55, AIR.10000, S25D.87, 139.9079 $ AIR CONV
56, AIR.10000, S25D.88, 137.9431 $ AIR CONV
57, AIR.10000, S25D.89, 138.1562 $ AIR CONV
58, AIR.10000, S25D.90, 204.7094 $ AIR CONV
59, AIR.10000, S25D.91, 159.8541 $ AIR CONV
60, AIR.10000, S25D.92, 174.5026 $ AIR CONV
61, AIR.10000, S25D.93, 160.5398 $ AIR CONV
62, AIR.10000, S25D.94, 143.0478 $ AIR CONV
63, AIR.10000, S25D.95, 175.8055 $ AIR CONV
64, AIR.10000, S25D.96, 99.97353 $ AIR CONV
65, AIR.10000, S25D.97, 119.0528 $ AIR CONV
66, AIR.10000, S25D.98, 147.533 $ AIR CONV
67, AIR.10000, S25D.99, 122.7583 $ AIR CONV
68, AIR.10000, S25D.100, 191.2955 $ AIR CONV
69, AIR.10000, S25D.101, 197.3013 $ AIR CONV
70, AIR.10000, S25D.102, 173.0556 $ AIR CONV
71, AIR.10000, S25D.103, 193.2726 $ AIR CONV
72, AIR.10000, S25D.104, 128.1502 $ AIR CONV
73, AIR.10000, S25D.105, 102.519 $ AIR CONV
74, AIR.10000, S25D.106, 180.8979 $ AIR CONV
75, AIR.10000, S25D.107, 160.9948 $ AIR CONV
76, AIR.10000, S25D.108, 197.6314 $ AIR CONV
77, AIR.10000, S25D.109, 162.5766 $ AIR CONV
78, AIR.10000, S25D.110, 143.3984 $ AIR CONV
79, AIR.10000, S25D.111, 265.7273 $ AIR CONV
80, AIR.10000, S25D.112, 90.36677 $ AIR CONV
81, AIR.10000, S25D.113, 146.033 $ AIR CONV
82, AIR.10000, S25D.114, 182.0126 $ AIR CONV
83, AIR.10000, S25D.115, 142.1242 $ AIR CONV
84, AIR.10000, S25D.116, 156.4711 $ AIR CONV
85, AIR.10000, S25D.117, 263.3278 $ AIR CONV
86, AIR.10000, S25D.118, 133.7923 $ AIR CONV
87, AIR.10000, S25D.119, 134.4939 $ AIR CONV
88, AIR.10000, S25D.120, 87.09295 $ AIR CONV
89, AIR.10000, S25D.121, 168.8858 $ AIR CONV
90, AIR.10000, S25D.122, 133.792 $ AIR CONV
91, AIR.10000, S25D.123, 194.2227 $ AIR CONV
92, AIR.10000, S25D.124, 116.8372 $ AIR CONV
93, AIR.10000, S25D.125, 125.5161 $ AIR CONV
94, AIR.10000, S25D.126, 54.22872 $ AIR CONV
HEADER VARIABLES 0, U1
C Heat Load-U1 POWER[U1]::DEA
S67C.Q1 = S67C.Q1 + 27.77842
S67C.Q2 = S67C.Q2 + 83.60381
S67C.Q3 = S67C.Q3 + 54.82939
S67C.Q4 = S67C.Q4 + 38.54834
S67C.Q5 = S67C.Q5 + 27.77842
S67C.Q6 = S67C.Q6 + 27.86794
S67C.Q7 = S67C.Q7 + 54.82939
S67C.Q8 = S67C.Q8 + 63.72669
S67C.Q9 = S67C.Q9 + 112.6502
S67C.Q10 = S67C.Q10 + 44.72019
S67C.Q11 = S67C.Q11 + 56.17543
S67C.Q12 = S67C.Q12 + 37.76753
S67C.Q13 = S67C.Q13 + 41.53661
S67C.Q14 = S67C.Q14 + 38.89015
S67C.Q15 = S67C.Q15 + 56.3575
S67C.Q16 = S67C.Q16 + 134.1606
S67C.Q17 = S67C.Q17 + 112.4682
S67C.Q18 = S67C.Q18 + 62.94588
S67C.Q19 = S67C.Q19 + 124.6098
S67C.Q20 = S67C.Q20 + 64.84931
S67C.Q21 = S67C.Q21 + 173.5864
S67C.Q22 = S67C.Q22 + 289.9135
S67C.Q23 = S67C.Q23 + 173.7685
S67C.Q24 = S67C.Q24 + 96.63783
HEADER NODE DATA, U2
HEADER CONDUCTOR DATA, U2
C Contact - Face Contactor-u2 contact[U2][1]::D4B
1, S25D.101, SB82.2, 0.222749
2, S25D.101, SB82.4, 4.481803
3, S25D.101, SB82.11, 0.3112232
4, S25D.101, SB82.12, 3.869354
5, S25D.101, SB82.18, 0.1023536
6, S25D.101, SB82.19, 1.919002
7, S25D.116, SB82.2, 2.166497
8, S25D.116, SB82.9, 0.1857799
9, S25D.116, SB82.12, 0.2024991
10, S25D.116, SB82.18, 0.2656026
11, S25D.117, SB82.4, 0.3480346
12, S25D.117, SB82.11, 0.4082713
13, S25D.117, SB82.19, 0.04685081
14, S25D.123, SB82.1, 6.771217
15, S25D.123, SB82.2, 5.789176
16, S25D.123, SB82.3, 7.999367
17, S25D.123, SB82.4, 1.898946
18, S25D.123, SB82.9, 9.955903
19, S25D.123, SB82.10, 9.947601
20, S25D.123, SB82.11, 9.160776
21, S25D.123, SB82.12, 5.900825
22, S25D.123, SB82.17, 14.49436
23, S25D.123, SB82.18, 18.01836
24, S25D.123, SB82.19, 12.362
25, S25D.123, SB82.20, 18.17145
HEADER VARIABLES 0, U2
C Heat Load-u2 power[U2]::D3F
SB82.Q1 = SB82.Q1 + 13.14304
SB82.Q2 = SB82.Q2 + 24.73277
SB82.Q3 = SB82.Q3 + 23.54379
SB82.Q4 = SB82.Q4 + 13.10696
SB82.Q5 = SB82.Q5 + 23.59044
SB82.Q6 = SB82.Q6 + 13.11356
SB82.Q7 = SB82.Q7 + 13.13522
SB82.Q8 = SB82.Q8 + 23.62498
SB82.Q9 = SB82.Q9 + 17.55859
SB82.Q10 = SB82.Q10 + 25.07847
SB82.Q11 = SB82.Q11 + 25.0472
SB82.Q12 = SB82.Q12 + 25.0852
SB82.Q13 = SB82.Q13 + 35.30753
SB82.Q14 = SB82.Q14 + 25.07439
SB82.Q15 = SB82.Q15 + 25.34528
SB82.Q16 = SB82.Q16 + 25.05068
SB82.Q17 = SB82.Q17 + 49.6953
SB82.Q18 = SB82.Q18 + 45.39197
SB82.Q19 = SB82.Q19 + 53.80839
SB82.Q20 = SB82.Q20 + 33.80833
SB82.Q21 = SB82.Q21 + 41.50079
SB82.Q22 = SB82.Q22 + 33.93809
SB82.Q23 = SB82.Q23 + 53.82713
SB82.Q24 = SB82.Q24 + 36.49191
HEADER NODE DATA, U3
HEADER CONDUCTOR DATA, U3
C Contact - Face Contactor-u3 contact[U3][1]::D53
1, S25D.69, SC04.6, 35.
2, S25D.69, SC04.13, 67.97
3, S25D.69, SC04.14, 66.71
4, S25D.69, SC04.16, 8.82
5, S25D.80, SC04.8, 34.72
6, S25D.80, SC04.14, 0.49
7, S25D.80, SC04.15, 38.78
8, S25D.80, SC04.16, 37.31
9, S25D.100, SC04.7, 35.
10, S25D.100, SC04.13, 2.66
11, S25D.100, SC04.14, 121.38
12, S25D.100, SC04.15, 97.72
13, S25D.100, SC04.16, 51.94
14, S25D.111, SC04.5, 35.
15, S25D.111, SC04.8, 0.28
16, S25D.111, SC04.13, 69.37
17, S25D.111, SC04.14, 21.42
18, S25D.111, SC04.15, 3.5
19, S25D.111, SC04.16, 111.93
HEADER VARIABLES 0, U3
C Heat Load-u3 power[U3]::D40
SC04.Q1 = SC04.Q1 + 23.4375
SC04.Q2 = SC04.Q2 + 31.25
SC04.Q3 = SC04.Q3 + 15.625
SC04.Q4 = SC04.Q4 + 31.25
SC04.Q5 = SC04.Q5 + 23.4375
SC04.Q6 = SC04.Q6 + 31.25
SC04.Q7 = SC04.Q7 + 46.875
SC04.Q8 = SC04.Q8 + 31.25
SC04.Q9 = SC04.Q9 + 164.0625
SC04.Q10 = SC04.Q10 + 218.75
SC04.Q11 = SC04.Q11 + 140.625
SC04.Q12 = SC04.Q12 + 101.5625
SC04.Q13 = SC04.Q13 + 70.3125
SC04.Q14 = SC04.Q14 + 156.25
SC04.Q15 = SC04.Q15 + 109.375
SC04.Q16 = SC04.Q16 + 257.8125
SC04.Q17 = SC04.Q17 + 46.875
HEADER SUBROUTINE
SUBROUTINE TDHTR
C This routine is to hold heaters at their midpoint temps
C for steady state solutions.
RETURN
END
SUBROUTINE TDREL
C This routine is to release heaters for transient runs
C for steady state solutions.
F RETURN
F END
F SUBROUTINE TDHTOT
C This routine prints out heater ontime and cycle summaries
F RETURN
F END
F SUBROUTINE TDHTRST
C This routine resets heater statistics
F RETURN
F END
F SUBROUTINE TDPREBL
C This routine executes logic before the build statement
M CALL COMMON
F RETURN
F END
F SUBROUTINE TDPOSTBL
C This routine executes logic after the build statement
M CALL COMMON
F RETURN
F END
F SUBROUTINE TDPOSTSL
C This routine executes logic after the solution
M CALL COMMON
F RETURN
F END
F SUBROUTINE BASEPLOT
CALL COMMON
F RETURN
F END
'''
您可以尝试以下方法：
- 使用
f.readlines() 逐行读取文件
- 对于每一行，检查该行是否包含
HEADER。
- 如果是这样，那就意味着这是一个新的子 df。将其添加到输出
- 否则：将当前行附加到当前子数据
- 将文本格式的
sub df 列表转换为 pandas 数据帧。这个 discussion 解释了如何。笔记：
- 使用的正则表达式是
,*\s{2,}，意思是：
- 匹配任何“
,”与“,*”
- 使用
"\s{2,} 匹配所有 2 和更多 space
- 参数
header=None 是必需的，第一行将用于添加列名称。
完整代码
# import modules
import pandas as pd
from io import StringIO
out = []
with open("data.txt", "r") as f:
sub = ""
for line in f.readlines():
if "HEADER" in line:
# Skip first insertion
if sub != "":
out.append(sub)
sub = ""
else: sub += line
# Append last sub (outside for loop)
out.append(sub)
# "out" is a list of pandas dataframes
out = [pd.read_csv(StringIO(o), sep=r",*\s{2,}", header=None, engine="python") for o in out]
print(out[0])
# 0 1 2
# 0 -10000 15.0 -1.0
print(out[1])
# 0 1 2 3 4
# 0 1 AIR.10000 S25D.1 56.84441 $ AIR CONV
# 1 2 AIR.10000 S25D.2 56.45712 $ AIR CONV
# 2 3 AIR.10000 S25D.3 53.35623 $ AIR CONV
# 3 4 AIR.10000 S25D.4 45.09633 $ AIR CONV
# 4 5 AIR.10000 S25D.9 77.00067 $ AIR CONV
# .. .. ... ... ... ...
# 89 90 AIR.10000 S25D.122 133.79200 $ AIR CONV
# 90 91 AIR.10000 S25D.123 194.22270 $ AIR CONV
# 91 92 AIR.10000 S25D.124 116.83720 $ AIR CONV
# 92 93 AIR.10000 S25D.125 125.51610 $ AIR CONV
# 93 94 AIR.10000 S25D.126 54.22872 $ AIR CONV
# [94 rows x 5 columns]
print(out[1].columns)
# Int64Index([0, 1, 2, 3, 4], dtype='int64')
希望对您有所帮助！
例如，我有以下格式的数据文本：
HEADER NODE DATA, AIR
-10000, 15., -1.0
HEADER CONDUCTOR DATA, AIR
1, AIR.10000, S25D.1, 56.84441 $ AIR CONV
2, AIR.10000, S25D.2, 56.45712 $ AIR CONV
3, AIR.10000, S25D.3, 53.35623 $ AIR CONV
4, AIR.10000, S25D.4, 45.09633 $ AIR CONV
5, AIR.10000, S25D.9, 77.00067 $ AIR CONV
6, AIR.10000, S25D.10, 80.35013 $ AIR CONV
7, AIR.10000, S25D.11, 50.4933 $ AIR CONV
8, AIR.10000, S25D.12, 91.61026 $ AIR CONV
9, AIR.10000, S25D.13, 53.75025 $ AIR CONV
10, AIR.10000, S25D.14, 75.68577 $ AIR CONV
11, AIR.10000, S25D.15, 110.0111 $ AIR CONV
12, AIR.10000, S25D.16, 114.7913 $ AIR CONV
13, AIR.10000, S25D.17, 81.12207 $ AIR CONV
14, AIR.10000, S25D.18, 72.80061 $ AIR CONV
15, AIR.10000, S25D.19, 72.21327 $ AIR CONV
16, AIR.10000, S25D.20, 90.99183 $ AIR CONV
17, AIR.10000, S25D.21, 66.35648 $ AIR CONV
18, AIR.10000, S25D.22, 76.9787 $ AIR CONV
19, AIR.10000, S25D.23, 52.46601 $ AIR CONV
20, AIR.10000, S25D.24, 68.30105 $ AIR CONV
21, AIR.10000, S25D.25, 114.0903 $ AIR CONV
22, AIR.10000, S25D.26, 70.51425 $ AIR CONV
23, AIR.10000, S25D.27, 36.39104 $ AIR CONV
24, AIR.10000, S25D.28, 78.88668 $ AIR CONV
25, AIR.10000, S25D.29, 70.77477 $ AIR CONV
26, AIR.10000, S25D.30, 87.04871 $ AIR CONV
27, AIR.10000, S25D.31, 64.50918 $ AIR CONV
28, AIR.10000, S25D.32, 76.20373 $ AIR CONV
29, AIR.10000, S25D.33, 90.69899 $ AIR CONV
30, AIR.10000, S25D.34, 83.89708 $ AIR CONV
31, AIR.10000, S25D.35, 88.59924 $ AIR CONV
32, AIR.10000, S25D.36, 72.06826 $ AIR CONV
33, AIR.10000, S25D.65, 157.6095 $ AIR CONV
34, AIR.10000, S25D.66, 140.3513 $ AIR CONV
35, AIR.10000, S25D.67, 215.1395 $ AIR CONV
36, AIR.10000, S25D.68, 131.7191 $ AIR CONV
37, AIR.10000, S25D.69, 173.7129 $ AIR CONV
38, AIR.10000, S25D.70, 106.8654 $ AIR CONV
39, AIR.10000, S25D.71, 153.2247 $ AIR CONV
40, AIR.10000, S25D.72, 151.2406 $ AIR CONV
41, AIR.10000, S25D.73, 136.0113 $ AIR CONV
42, AIR.10000, S25D.74, 217.2005 $ AIR CONV
43, AIR.10000, S25D.75, 121.0298 $ AIR CONV
44, AIR.10000, S25D.76, 178.8008 $ AIR CONV
45, AIR.10000, S25D.77, 160.7517 $ AIR CONV
46, AIR.10000, S25D.78, 132.528 $ AIR CONV
47, AIR.10000, S25D.79, 126.503 $ AIR CONV
48, AIR.10000, S25D.80, 223.1756 $ AIR CONV
49, AIR.10000, S25D.81, 151.6868 $ AIR CONV
50, AIR.10000, S25D.82, 176.8964 $ AIR CONV
51, AIR.10000, S25D.83, 155.6967 $ AIR CONV
52, AIR.10000, S25D.84, 153.6341 $ AIR CONV
53, AIR.10000, S25D.85, 110.9477 $ AIR CONV
54, AIR.10000, S25D.86, 165.114 $ AIR CONV
55, AIR.10000, S25D.87, 139.9079 $ AIR CONV
56, AIR.10000, S25D.88, 137.9431 $ AIR CONV
57, AIR.10000, S25D.89, 138.1562 $ AIR CONV
58, AIR.10000, S25D.90, 204.7094 $ AIR CONV
59, AIR.10000, S25D.91, 159.8541 $ AIR CONV
60, AIR.10000, S25D.92, 174.5026 $ AIR CONV
61, AIR.10000, S25D.93, 160.5398 $ AIR CONV
62, AIR.10000, S25D.94, 143.0478 $ AIR CONV
63, AIR.10000, S25D.95, 175.8055 $ AIR CONV
64, AIR.10000, S25D.96, 99.97353 $ AIR CONV
65, AIR.10000, S25D.97, 119.0528 $ AIR CONV
66, AIR.10000, S25D.98, 147.533 $ AIR CONV
67, AIR.10000, S25D.99, 122.7583 $ AIR CONV
68, AIR.10000, S25D.100, 191.2955 $ AIR CONV
69, AIR.10000, S25D.101, 197.3013 $ AIR CONV
70, AIR.10000, S25D.102, 173.0556 $ AIR CONV
71, AIR.10000, S25D.103, 193.2726 $ AIR CONV
72, AIR.10000, S25D.104, 128.1502 $ AIR CONV
73, AIR.10000, S25D.105, 102.519 $ AIR CONV
74, AIR.10000, S25D.106, 180.8979 $ AIR CONV
75, AIR.10000, S25D.107, 160.9948 $ AIR CONV
76, AIR.10000, S25D.108, 197.6314 $ AIR CONV
77, AIR.10000, S25D.109, 162.5766 $ AIR CONV
78, AIR.10000, S25D.110, 143.3984 $ AIR CONV
79, AIR.10000, S25D.111, 265.7273 $ AIR CONV
80, AIR.10000, S25D.112, 90.36677 $ AIR CONV
81, AIR.10000, S25D.113, 146.033 $ AIR CONV
82, AIR.10000, S25D.114, 182.0126 $ AIR CONV
83, AIR.10000, S25D.115, 142.1242 $ AIR CONV
84, AIR.10000, S25D.116, 156.4711 $ AIR CONV
85, AIR.10000, S25D.117, 263.3278 $ AIR CONV
86, AIR.10000, S25D.118, 133.7923 $ AIR CONV
87, AIR.10000, S25D.119, 134.4939 $ AIR CONV
88, AIR.10000, S25D.120, 87.09295 $ AIR CONV
89, AIR.10000, S25D.121, 168.8858 $ AIR CONV
90, AIR.10000, S25D.122, 133.792 $ AIR CONV
91, AIR.10000, S25D.123, 194.2227 $ AIR CONV
92, AIR.10000, S25D.124, 116.8372 $ AIR CONV
93, AIR.10000, S25D.125, 125.5161 $ AIR CONV
94, AIR.10000, S25D.126, 54.22872 $ AIR CONV
我想将其读入 pandas 数据框以供进一步分析。 如您所见，header 对于每个子集和数据格式都是不同的。 我想使用 re 模块和 pandas 将数据读入框架，但不知道如何以最有效的方式进行。 正如您所看到的，AIR 字符串对于两个 header 都是通用的。在完整文件中会有更多这样的字符串，所以我想为每个字符串创建一个 class 属性（节点，导体）将是一个具有相应数据的 pd 数据帧。
任何帮助将不胜感激:)
编辑： 按照亚历山大的建议，我稍微修改了一段代码，但仍然没有找到将数据放入 class
的方法# import modules
import pandas as pd
from io import StringIO
class TableData:
def __init__(self,name):
self.name = name
self.nodes_table = self.add_nodes()
self.conductor_table = self.add_conductors()
def add_nodes(self):
pass
def add_conductors(self):
pass
out = []
submodels = set()
with open("case1.cc", "r") as f:
sub = ""
for line in f.readlines():
if ("VARIABLES" in line) or ("OPTIONS" in line): # skip non relevant
# blocks
continue
if line.startswith('C'): # skip comments line
continue
if ("HEADER" in line) and ("DATA" in line):
# Get submodel name and add to set if not present
submodels.add(line.split(',')[1])
# Get type of data
type = line.split()[1]
# Skip first insertion
if sub != "":
out.append(sub)
sub = ""
else: sub += line
# Append last sub (outside for loop)
out.append(sub)
# "out" is a list of pandas dataframes
out = [pd.read_csv(StringIO(o), sep=r",*\s{2,}", header=None, engine="python") for o in out]
还有更完整的示例文件：
HEADER OPTIONS
C SINDA Data generated with Thermal Desktop 6.0 Patch 2
C Generated on Fri Sep 01 14:39:30 2017
C From file: thermal.dwg
C Case Set: Case Set 1
C TDUNITS, Energy = J
C TDUNITS, Time = sec
C TDUNITS, Temp = C
C TDUNITS, Mass = kg
C TDUNITS, Length = m
C TDUNITS, Orbit = km
C TDUNITS, Pressure = Pa
C TDUNITS, Force = N
C TDUNITS, Angle = Degrees
C TDUNITS, Volt = volt
C TDUNITS, Current = amp
C TDUNITS, Resistance = ohm
HEADER NODE DATA, AIR
-10000, 15., -1.0
HEADER CONDUCTOR DATA, AIR
1, AIR.10000, S25D.1, 56.84441 $ AIR CONV
2, AIR.10000, S25D.2, 56.45712 $ AIR CONV
3, AIR.10000, S25D.3, 53.35623 $ AIR CONV
4, AIR.10000, S25D.4, 45.09633 $ AIR CONV
5, AIR.10000, S25D.9, 77.00067 $ AIR CONV
6, AIR.10000, S25D.10, 80.35013 $ AIR CONV
7, AIR.10000, S25D.11, 50.4933 $ AIR CONV
8, AIR.10000, S25D.12, 91.61026 $ AIR CONV
9, AIR.10000, S25D.13, 53.75025 $ AIR CONV
10, AIR.10000, S25D.14, 75.68577 $ AIR CONV
11, AIR.10000, S25D.15, 110.0111 $ AIR CONV
12, AIR.10000, S25D.16, 114.7913 $ AIR CONV
13, AIR.10000, S25D.17, 81.12207 $ AIR CONV
14, AIR.10000, S25D.18, 72.80061 $ AIR CONV
15, AIR.10000, S25D.19, 72.21327 $ AIR CONV
16, AIR.10000, S25D.20, 90.99183 $ AIR CONV
17, AIR.10000, S25D.21, 66.35648 $ AIR CONV
18, AIR.10000, S25D.22, 76.9787 $ AIR CONV
19, AIR.10000, S25D.23, 52.46601 $ AIR CONV
20, AIR.10000, S25D.24, 68.30105 $ AIR CONV
21, AIR.10000, S25D.25, 114.0903 $ AIR CONV
22, AIR.10000, S25D.26, 70.51425 $ AIR CONV
23, AIR.10000, S25D.27, 36.39104 $ AIR CONV
24, AIR.10000, S25D.28, 78.88668 $ AIR CONV
25, AIR.10000, S25D.29, 70.77477 $ AIR CONV
26, AIR.10000, S25D.30, 87.04871 $ AIR CONV
27, AIR.10000, S25D.31, 64.50918 $ AIR CONV
28, AIR.10000, S25D.32, 76.20373 $ AIR CONV
29, AIR.10000, S25D.33, 90.69899 $ AIR CONV
30, AIR.10000, S25D.34, 83.89708 $ AIR CONV
31, AIR.10000, S25D.35, 88.59924 $ AIR CONV
32, AIR.10000, S25D.36, 72.06826 $ AIR CONV
33, AIR.10000, S25D.65, 157.6095 $ AIR CONV
34, AIR.10000, S25D.66, 140.3513 $ AIR CONV
35, AIR.10000, S25D.67, 215.1395 $ AIR CONV
36, AIR.10000, S25D.68, 131.7191 $ AIR CONV
37, AIR.10000, S25D.69, 173.7129 $ AIR CONV
38, AIR.10000, S25D.70, 106.8654 $ AIR CONV
39, AIR.10000, S25D.71, 153.2247 $ AIR CONV
40, AIR.10000, S25D.72, 151.2406 $ AIR CONV
41, AIR.10000, S25D.73, 136.0113 $ AIR CONV
42, AIR.10000, S25D.74, 217.2005 $ AIR CONV
43, AIR.10000, S25D.75, 121.0298 $ AIR CONV
44, AIR.10000, S25D.76, 178.8008 $ AIR CONV
45, AIR.10000, S25D.77, 160.7517 $ AIR CONV
46, AIR.10000, S25D.78, 132.528 $ AIR CONV
47, AIR.10000, S25D.79, 126.503 $ AIR CONV
48, AIR.10000, S25D.80, 223.1756 $ AIR CONV
49, AIR.10000, S25D.81, 151.6868 $ AIR CONV
50, AIR.10000, S25D.82, 176.8964 $ AIR CONV
51, AIR.10000, S25D.83, 155.6967 $ AIR CONV
52, AIR.10000, S25D.84, 153.6341 $ AIR CONV
53, AIR.10000, S25D.85, 110.9477 $ AIR CONV
54, AIR.10000, S25D.86, 165.114 $ AIR CONV
55, AIR.10000, S25D.87, 139.9079 $ AIR CONV
56, AIR.10000, S25D.88, 137.9431 $ AIR CONV
57, AIR.10000, S25D.89, 138.1562 $ AIR CONV
58, AIR.10000, S25D.90, 204.7094 $ AIR CONV
59, AIR.10000, S25D.91, 159.8541 $ AIR CONV
60, AIR.10000, S25D.92, 174.5026 $ AIR CONV
61, AIR.10000, S25D.93, 160.5398 $ AIR CONV
62, AIR.10000, S25D.94, 143.0478 $ AIR CONV
63, AIR.10000, S25D.95, 175.8055 $ AIR CONV
64, AIR.10000, S25D.96, 99.97353 $ AIR CONV
65, AIR.10000, S25D.97, 119.0528 $ AIR CONV
66, AIR.10000, S25D.98, 147.533 $ AIR CONV
67, AIR.10000, S25D.99, 122.7583 $ AIR CONV
68, AIR.10000, S25D.100, 191.2955 $ AIR CONV
69, AIR.10000, S25D.101, 197.3013 $ AIR CONV
70, AIR.10000, S25D.102, 173.0556 $ AIR CONV
71, AIR.10000, S25D.103, 193.2726 $ AIR CONV
72, AIR.10000, S25D.104, 128.1502 $ AIR CONV
73, AIR.10000, S25D.105, 102.519 $ AIR CONV
74, AIR.10000, S25D.106, 180.8979 $ AIR CONV
75, AIR.10000, S25D.107, 160.9948 $ AIR CONV
76, AIR.10000, S25D.108, 197.6314 $ AIR CONV
77, AIR.10000, S25D.109, 162.5766 $ AIR CONV
78, AIR.10000, S25D.110, 143.3984 $ AIR CONV
79, AIR.10000, S25D.111, 265.7273 $ AIR CONV
80, AIR.10000, S25D.112, 90.36677 $ AIR CONV
81, AIR.10000, S25D.113, 146.033 $ AIR CONV
82, AIR.10000, S25D.114, 182.0126 $ AIR CONV
83, AIR.10000, S25D.115, 142.1242 $ AIR CONV
84, AIR.10000, S25D.116, 156.4711 $ AIR CONV
85, AIR.10000, S25D.117, 263.3278 $ AIR CONV
86, AIR.10000, S25D.118, 133.7923 $ AIR CONV
87, AIR.10000, S25D.119, 134.4939 $ AIR CONV
88, AIR.10000, S25D.120, 87.09295 $ AIR CONV
89, AIR.10000, S25D.121, 168.8858 $ AIR CONV
90, AIR.10000, S25D.122, 133.792 $ AIR CONV
91, AIR.10000, S25D.123, 194.2227 $ AIR CONV
92, AIR.10000, S25D.124, 116.8372 $ AIR CONV
93, AIR.10000, S25D.125, 125.5161 $ AIR CONV
94, AIR.10000, S25D.126, 54.22872 $ AIR CONV
HEADER VARIABLES 0, U1
C Heat Load-U1 POWER[U1]::DEA
S67C.Q1 = S67C.Q1 + 27.77842
S67C.Q2 = S67C.Q2 + 83.60381
S67C.Q3 = S67C.Q3 + 54.82939
S67C.Q4 = S67C.Q4 + 38.54834
S67C.Q5 = S67C.Q5 + 27.77842
S67C.Q6 = S67C.Q6 + 27.86794
S67C.Q7 = S67C.Q7 + 54.82939
S67C.Q8 = S67C.Q8 + 63.72669
S67C.Q9 = S67C.Q9 + 112.6502
S67C.Q10 = S67C.Q10 + 44.72019
S67C.Q11 = S67C.Q11 + 56.17543
S67C.Q12 = S67C.Q12 + 37.76753
S67C.Q13 = S67C.Q13 + 41.53661
S67C.Q14 = S67C.Q14 + 38.89015
S67C.Q15 = S67C.Q15 + 56.3575
S67C.Q16 = S67C.Q16 + 134.1606
S67C.Q17 = S67C.Q17 + 112.4682
S67C.Q18 = S67C.Q18 + 62.94588
S67C.Q19 = S67C.Q19 + 124.6098
S67C.Q20 = S67C.Q20 + 64.84931
S67C.Q21 = S67C.Q21 + 173.5864
S67C.Q22 = S67C.Q22 + 289.9135
S67C.Q23 = S67C.Q23 + 173.7685
S67C.Q24 = S67C.Q24 + 96.63783
HEADER NODE DATA, U2
HEADER CONDUCTOR DATA, U2
C Contact - Face Contactor-u2 contact[U2][1]::D4B
1, S25D.101, SB82.2, 0.222749
2, S25D.101, SB82.4, 4.481803
3, S25D.101, SB82.11, 0.3112232
4, S25D.101, SB82.12, 3.869354
5, S25D.101, SB82.18, 0.1023536
6, S25D.101, SB82.19, 1.919002
7, S25D.116, SB82.2, 2.166497
8, S25D.116, SB82.9, 0.1857799
9, S25D.116, SB82.12, 0.2024991
10, S25D.116, SB82.18, 0.2656026
11, S25D.117, SB82.4, 0.3480346
12, S25D.117, SB82.11, 0.4082713
13, S25D.117, SB82.19, 0.04685081
14, S25D.123, SB82.1, 6.771217
15, S25D.123, SB82.2, 5.789176
16, S25D.123, SB82.3, 7.999367
17, S25D.123, SB82.4, 1.898946
18, S25D.123, SB82.9, 9.955903
19, S25D.123, SB82.10, 9.947601
20, S25D.123, SB82.11, 9.160776
21, S25D.123, SB82.12, 5.900825
22, S25D.123, SB82.17, 14.49436
23, S25D.123, SB82.18, 18.01836
24, S25D.123, SB82.19, 12.362
25, S25D.123, SB82.20, 18.17145
HEADER VARIABLES 0, U2
C Heat Load-u2 power[U2]::D3F
SB82.Q1 = SB82.Q1 + 13.14304
SB82.Q2 = SB82.Q2 + 24.73277
SB82.Q3 = SB82.Q3 + 23.54379
SB82.Q4 = SB82.Q4 + 13.10696
SB82.Q5 = SB82.Q5 + 23.59044
SB82.Q6 = SB82.Q6 + 13.11356
SB82.Q7 = SB82.Q7 + 13.13522
SB82.Q8 = SB82.Q8 + 23.62498
SB82.Q9 = SB82.Q9 + 17.55859
SB82.Q10 = SB82.Q10 + 25.07847
SB82.Q11 = SB82.Q11 + 25.0472
SB82.Q12 = SB82.Q12 + 25.0852
SB82.Q13 = SB82.Q13 + 35.30753
SB82.Q14 = SB82.Q14 + 25.07439
SB82.Q15 = SB82.Q15 + 25.34528
SB82.Q16 = SB82.Q16 + 25.05068
SB82.Q17 = SB82.Q17 + 49.6953
SB82.Q18 = SB82.Q18 + 45.39197
SB82.Q19 = SB82.Q19 + 53.80839
SB82.Q20 = SB82.Q20 + 33.80833
SB82.Q21 = SB82.Q21 + 41.50079
SB82.Q22 = SB82.Q22 + 33.93809
SB82.Q23 = SB82.Q23 + 53.82713
SB82.Q24 = SB82.Q24 + 36.49191
HEADER NODE DATA, U3
HEADER CONDUCTOR DATA, U3
C Contact - Face Contactor-u3 contact[U3][1]::D53
1, S25D.69, SC04.6, 35.
2, S25D.69, SC04.13, 67.97
3, S25D.69, SC04.14, 66.71
4, S25D.69, SC04.16, 8.82
5, S25D.80, SC04.8, 34.72
6, S25D.80, SC04.14, 0.49
7, S25D.80, SC04.15, 38.78
8, S25D.80, SC04.16, 37.31
9, S25D.100, SC04.7, 35.
10, S25D.100, SC04.13, 2.66
11, S25D.100, SC04.14, 121.38
12, S25D.100, SC04.15, 97.72
13, S25D.100, SC04.16, 51.94
14, S25D.111, SC04.5, 35.
15, S25D.111, SC04.8, 0.28
16, S25D.111, SC04.13, 69.37
17, S25D.111, SC04.14, 21.42
18, S25D.111, SC04.15, 3.5
19, S25D.111, SC04.16, 111.93
HEADER VARIABLES 0, U3
C Heat Load-u3 power[U3]::D40
SC04.Q1 = SC04.Q1 + 23.4375
SC04.Q2 = SC04.Q2 + 31.25
SC04.Q3 = SC04.Q3 + 15.625
SC04.Q4 = SC04.Q4 + 31.25
SC04.Q5 = SC04.Q5 + 23.4375
SC04.Q6 = SC04.Q6 + 31.25
SC04.Q7 = SC04.Q7 + 46.875
SC04.Q8 = SC04.Q8 + 31.25
SC04.Q9 = SC04.Q9 + 164.0625
SC04.Q10 = SC04.Q10 + 218.75
SC04.Q11 = SC04.Q11 + 140.625
SC04.Q12 = SC04.Q12 + 101.5625
SC04.Q13 = SC04.Q13 + 70.3125
SC04.Q14 = SC04.Q14 + 156.25
SC04.Q15 = SC04.Q15 + 109.375
SC04.Q16 = SC04.Q16 + 257.8125
SC04.Q17 = SC04.Q17 + 46.875
HEADER SUBROUTINE
SUBROUTINE TDHTR
C This routine is to hold heaters at their midpoint temps
C for steady state solutions.
RETURN
END
SUBROUTINE TDREL
C This routine is to release heaters for transient runs
C for steady state solutions.
F RETURN
F END
F SUBROUTINE TDHTOT
C This routine prints out heater ontime and cycle summaries
F RETURN
F END
F SUBROUTINE TDHTRST
C This routine resets heater statistics
F RETURN
F END
F SUBROUTINE TDPREBL
C This routine executes logic before the build statement
M CALL COMMON
F RETURN
F END
F SUBROUTINE TDPOSTBL
C This routine executes logic after the build statement
M CALL COMMON
F RETURN
F END
F SUBROUTINE TDPOSTSL
C This routine executes logic after the solution
M CALL COMMON
F RETURN
F END
F SUBROUTINE BASEPLOT
CALL COMMON
F RETURN
F END
'''
您可以尝试以下方法：
- 使用
f.readlines()逐行读取文件
- 对于每一行，检查该行是否包含
HEADER。- 如果是这样，那就意味着这是一个新的子 df。将其添加到输出
- 否则：将当前行附加到当前子数据
- 将文本格式的
subdf 列表转换为 pandas 数据帧。这个 discussion 解释了如何。笔记：- 使用的正则表达式是
,*\s{2,}，意思是：- 匹配任何“
,”与“,*” - 使用
"\s{2,} 匹配所有 2 和更多 space
- 匹配任何“
- 参数
header=None是必需的，第一行将用于添加列名称。
- 使用的正则表达式是
完整代码
# import modules
import pandas as pd
from io import StringIO
out = []
with open("data.txt", "r") as f:
sub = ""
for line in f.readlines():
if "HEADER" in line:
# Skip first insertion
if sub != "":
out.append(sub)
sub = ""
else: sub += line
# Append last sub (outside for loop)
out.append(sub)
# "out" is a list of pandas dataframes
out = [pd.read_csv(StringIO(o), sep=r",*\s{2,}", header=None, engine="python") for o in out]
print(out[0])
# 0 1 2
# 0 -10000 15.0 -1.0
print(out[1])
# 0 1 2 3 4
# 0 1 AIR.10000 S25D.1 56.84441 $ AIR CONV
# 1 2 AIR.10000 S25D.2 56.45712 $ AIR CONV
# 2 3 AIR.10000 S25D.3 53.35623 $ AIR CONV
# 3 4 AIR.10000 S25D.4 45.09633 $ AIR CONV
# 4 5 AIR.10000 S25D.9 77.00067 $ AIR CONV
# .. .. ... ... ... ...
# 89 90 AIR.10000 S25D.122 133.79200 $ AIR CONV
# 90 91 AIR.10000 S25D.123 194.22270 $ AIR CONV
# 91 92 AIR.10000 S25D.124 116.83720 $ AIR CONV
# 92 93 AIR.10000 S25D.125 125.51610 $ AIR CONV
# 93 94 AIR.10000 S25D.126 54.22872 $ AIR CONV
# [94 rows x 5 columns]
print(out[1].columns)
# Int64Index([0, 1, 2, 3, 4], dtype='int64')
希望对您有所帮助！