我有这个文件:
:Product: Solar Radio Data 7day_rad.txt
:Issued: 0922 UTC 05 Feb 2016
#
# Prepared by the U.S. Dept. of Commerce, NOAA, Space Weather Prediction Center
# Please send comments and suggestions to SWPC.Webmaster@noaa.gov
# Units: 10^-22 W/m^2/Hz
# Missing Data: -1
#
# Daily local noon solar radio flux values - Updated once an hour
#
Freq Learmonth San Vito Sag Hill Penticton Penticton Palehua Penticton
MHZ 0500 UTC 1200 UTC 1700 UTC 1700 UTC 2000 UTC 2300 UTC 2300 UTC
2016 Jan 30
245 20 17 17 -1 -1 12 -1
410 38 34 37 -1 -1 35 -1
610 56 -1 56 -1 -1 50 -1
1415 104 73 72 -1 -1 78 -1
2695 106 106 98 -1 -1 101 -1
2800 -1 -1 -1 105 105 -1 105
4995 -1 149 134 -1 -1 145 -1
8800 287 269 261 -1 -1 275 -1
15400 514 573 536 -1 -1 515 -1
2016 Jan 31
245 21 18 20 -1 -1 32 -1
410 39 17 38 -1 -1 46 -1
610 58 -1 56 -1 -1 60 -1
1415 91 74 72 -1 -1 78 -1
2695 102 103 97 -1 -1 100 -1
2800 -1 -1 -1 102 101 -1 100
4995 -1 146 135 -1 -1 138 -1
8800 278 268 262 -1 -1 272 -1
15400 513 568 530 -1 -1 521 -1
2016 Feb 1
245 25 21 21 -1 -1 35 -1
410 45 40 40 -1 -1 49 -1
610 66 -1 59 -1 -1 63 -1
1415 65 72 68 -1 -1 78 -1
2695 99 101 90 -1 -1 97 -1
2800 -1 -1 -1 100 100 -1 100
4995 -1 140 131 -1 -1 139 -1
8800 278 258 266 -1 -1 275 -1
15400 508 565 528 -1 -1 526 -1
2016 Feb 2
245 23 20 21 -1 -1 36 -1
410 45 68 40 -1 -1 48 -1
610 68 -1 60 -1 -1 61 -1
1415 72 73 69 -1 -1 80 -1
2695 98 98 93 -1 -1 102 -1
2800 -1 -1 -1 102 102 -1 103
4995 -1 141 131 -1 -1 141 -1
8800 284 255 268 -1 -1 276 -1
15400 510 568 537 -1 -1 526 -1
2016 Feb 3
245 34 -1 20 -1 -1 36 -1
410 47 -1 41 -1 -1 50 -1
610 70 -1 63 -1 -1 66 -1
1415 68 76 76 -1 -1 86 -1
2695 105 -1 106 -1 -1 112 -1
2800 -1 -1 -1 113 112 -1 112
4995 -1 -1 140 -1 -1 152 -1
8800 284 -1 260 -1 -1 284 -1
15400 516 -1 455 -1 -1 535 -1
2016 Feb 4
245 -1 23 21 -1 -1 46 -1
410 -1 43 43 -1 -1 54 -1
610 -1 -1 65 -1 -1 68 -1
1415 -1 84 81 -1 -1 90 -1
2695 -1 114 120 -1 -1 118 -1
2800 -1 -1 -1 125 123 -1 120
4995 -1 162 154 -1 -1 158 -1
8800 -1 276 273 -1 -1 283 -1
15400 -1 564 523 -1 -1 547 -1
2016 Feb 5
245 34 -1 -1 -1 -1 -1 -1
410 52 -1 -1 -1 -1 -1 -1
610 78 -1 -1 -1 -1 -1 -1
1415 84 -1 -1 -1 -1 -1 -1
2695 115 -1 -1 -1 -1 -1 -1
2800 -1 -1 -1 -1 -1 -1 -1
4995 -1 -1 -1 -1 -1 -1 -1
8800 295 -1 -1 -1 -1 -1 -1
15400 508 -1 -1 -1 -1 -1 -1
现在我需要创建数据框，我可以在其中一次从 Pentiction 中读取日期数据...我可以创建数据框并用日期时间解析它，但在这种情况下不起作用...
请问有什么建议吗？
最佳答案
尝试read_csv :
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp),
sep="\s+",
skip_blank_lines=True,
index_col=None,
skiprows=14,
header=None,
names=['Freq','a','b','c','d','e','f','g'])
print df
Freq a b c d e f g
0 2016 Jan 30 NaN NaN NaN NaN NaN
1 245 20 17 17 -1 -1 12 -1
2 410 38 34 37 -1 -1 35 -1
3 610 56 -1 56 -1 -1 50 -1
4 1415 104 73 72 -1 -1 78 -1
5 2695 106 106 98 -1 -1 101 -1
6 2800 -1 -1 -1 105 105 -1 105
7 4995 -1 149 134 -1 -1 145 -1
8 8800 287 269 261 -1 -1 275 -1
9 15400 514 573 536 -1 -1 515 -1
10 2016 Jan 31 NaN NaN NaN NaN NaN
11 245 21 18 20 -1 -1 32 -1
12 410 39 17 38 -1 -1 46 -1
13 610 58 -1 56 -1 -1 60 -1
14 1415 91 74 72 -1 -1 78 -1
15 2695 102 103 97 -1 -1 100 -1
关于python - pandas 创建数据框 - 解析 key ，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/35223363/