I have two dimensional list like that
x_irp_group = [['x1_1_4', 'x1_2_4', 'x1_3_4', 'x1_4_4', 'x1_5_4', 'x1_6_4', 'x1_7_4', 'x1_8_4', 'x1_9_4', 'x1_10_4', 'x1_1_5', 'x1_2_5', 'x1_3_5', 'x1_4_5', 'x1_5_5', 'x1_6_5', 'x1_7_5', 'x1_8_5', 'x1_9_5', 'x1_10_5', 'x1_1_6', 'x1_2_6', 'x1_3_6', 'x1_4_6', 'x1_5_6', 'x1_6_6', 'x1_7_6', 'x1_8_6', 'x1_9_6', 'x1_10_6', 'x1_1_7', 'x1_2_7', 'x1_3_7', 'x1_4_7', 'x1_5_7', 'x1_6_7', 'x1_7_7', 'x1_8_7', 'x1_9_7', 'x1_10_7', 'x1_1_8', 'x1_2_8', 'x1_3_8', 'x1_4_8', 'x1_5_8', 'x1_6_8', 'x1_7_8', 'x1_8_8', 'x1_9_8', 'x1_10_8'], ['x1_1_8', 'x1_2_8', 'x1_3_8', 'x1_4_8', 'x1_5_8', 'x1_6_8', 'x1_7_8', 'x1_8_8', 'x1_9_8', 'x1_10_8', 'x1_1_9', 'x1_2_9', 'x1_3_9', 'x1_4_9', 'x1_5_9', 'x1_6_9', 'x1_7_9', 'x1_8_9', 'x1_9_9', 'x1_10_9', 'x1_1_10', 'x1_2_10', 'x1_3_10', 'x1_4_10', 'x1_5_10', 'x1_6_10', 'x1_7_10', 'x1_8_10', 'x1_9_10', 'x1_10_10', 'x1_1_11', 'x1_2_11', 'x1_3_11', 'x1_4_11', 'x1_5_11', 'x1_6_11', 'x1_7_11', 'x1_8_11', 'x1_9_11', 'x1_10_11', 'x1_1_12', 'x1_2_12', 'x1_3_12', 'x1_4_12', 'x1_5_12', 'x1_6_12', 'x1_7_12', 'x1_8_12', 'x1_9_12', 'x1_10_12']]
I wanna eliminate this two dimensional list if the elements in another one dimensional list like that
x_irp_eliminated_list = ['x1_1_4', 'x1_1_8', 'x1_1_12', 'x1_1_16', 'x1_1_19', 'x1_1_22', 'x1_1_26', 'x1_1_30', 'x1_1_34', 'x1_1_37', 'x1_1_43', 'x1_1_49', 'x1_1_55', 'x1_1_61', 'x1_1_68', 'x1_1_75', 'x1_1_81', 'x1_1_87', 'x1_1_92', 'x1_1_96', 'x1_1_101', 'x1_1_107', 'x1_1_112', 'x1_1_116', 'x1_1_121', 'x1_1_126', 'x1_1_131', 'x1_1_134', 'x1_1_137', 'x1_1_141', 'x1_1_145', 'x1_1_149', 'x1_1_152', 'x1_1_155', 'x1_1_160', 'x1_1_164', 'x1_1_169', 'x1_1_173', 'x1_1_181', 'x1_1_189', 'x1_1_197', 'x1_1_205', 'x1_2_8', 'x1_2_10', 'x1_2_13', 'x1_2_17', 'x1_2_21', 'x1_2_25', 'x1_2_28', 'x1_2_30', 'x1_2_34', 'x1_2_40', 'x1_2_45', 'x1_2_51', 'x1_2_58', 'x1_2_66', 'x1_2_71', 'x1_2_77', 'x1_2_82', 'x1_2_86', 'x1_2_91', 'x1_2_97', 'x1_2_102', 'x1_2_106', 'x1_2_111', 'x1_2_117', 'x1_2_122', 'x1_2_125', 'x1_2_129', 'x1_2_132', 'x1_2_135', 'x1_2_139', 'x1_2_143', 'x1_2_147', 'x1_2_151', 'x1_2_154', 'x1_2_157', 'x1_2_161', 'x1_2_166', 'x1_2_172', 'x1_2_177', 'x1_2_181', 'x1_2_189', 'x1_2_197', 'x1_2_205', 'x1_2_214', 'x1_3_1', 'x1_3_4', 'x1_3_8', 'x1_3_11', 'x1_3_15', 'x1_3_18', 'x1_3_22', 'x1_3_25', 'x1_3_28', 'x1_3_32', 'x1_3_35', 'x1_3_39', 'x1_3_42', 'x1_3_46', 'x1_3_49', 'x1_3_52', 'x1_3_56', 'x1_3_59', 'x1_3_63', 'x1_3_66', 'x1_3_70', 'x1_3_73', 'x1_3_77', 'x1_3_81', 'x1_3_85', 'x1_3_88', 'x1_3_91', 'x1_3_94', 'x1_3_97', 'x1_3_101', 'x1_3_105', 'x1_3_109', 'x1_3_112', 'x1_3_115', 'x1_3_118', 'x1_3_122', 'x1_3_126', 'x1_3_130', 'x1_3_134', 'x1_3_137', 'x1_3_140', 'x1_3_143', 'x1_3_147', 'x1_3_151', 'x1_3_156', 'x1_3_159', 'x1_3_163']
I write a code like that but it did not work well.
x_final = [i for i, j in zip(x_irp_group, x_irp_eliminated_list) if i == j]
I shorten the lists. Normally their sizes are much bigger than that
the list comprehension you have isn't working because you are zipping the elements together, which isn't what the operation represents (they are not parallel arrays) what you want is something along the lines of:
x_final = [i for i in x_irp_group[0] if (i not in x_irp_eliminated_list)]
Note that for a 2d list you may need to nest this like:
# writing normal loops you'd write:
# for row in x_irp_group:
# for i in row:
# if (...):
# so I typically try to indent the loops similarly since nested array comprehension
# gets complicated, honestly I'd likely prefer using generator functions for this anyway
x_final = [[i for i in row
if (i not in x_irp_eliminated_list)
]for row in x_irp_group
]
although know that i not in x_irp_eliminated_list will be very slow for a list, changing it to a set would improve performance:
x_irp_eliminated_set = set(x_irp_eliminated_list)
x_final = [i for i in x_irp_group[0] if (i not in x_irp_eliminated_set)]
Or if the lists are trivially sorted, then you could convert them both to sets, do a subtraction then sort it again:
x_final = [ sorted(set(x_irp_group[0]) - set(x_irp_eliminated_list)) ]
although if you have super giant lists this would probably be less desirable.
x_irp_eliminated_list_set = set(x_irp_eliminated_list)
x_last = [i for row in x_irp_group
for i in row
if (i in x_irp_eliminated_list_set)]
print(x_last[:30])
I used this for faster operation. Set approach made it faster. Thanks for that information. I learn one new thing. But it creates one dimensional list. I would like to create two dimensional list like original x_irp_group
I have a list of strings in python like this
['AM_B0_D0.0_2016-04-01T010000.flac.h5',
'AM_B0_D3.7_2016-04-13T215000.flac.h5',
'AM_B0_D10.3_2017-03-17T110000.flac.h5',
'AM_B0_D0.7_2016-10-21T104000.flac.h5',
'AM_B0_D4.4_2016-08-05T151000.flac.h5',
'AM_B0_D0.0_2016-04-01T010000.flac.h5',
'AM_B0_D3.7_2016-04-13T215000.flac.h5',
'AM_B0_D10.3_2017-03-17T110000.flac.h5',
'AM_B0_D0.7_2016-10-21T104000.flac.h5',
'AM_B0_D4.4_2016-08-05T151000.flac.h5']
I want to parse only the date and time (for example, 2016-08-05 15:10:00 )from these strings.
So far I used a for loop like the one below but it's very time consuming, is there a better way to do this?
for files in glob.glob("AM_B0_*.flac.h5"):
if files[11]=='_':
year=files[12:16]
month=files[17:19]
day= files[20:22]
hour=files[23:25]
minute=files[25:27]
second=files[27:29]
tindex=pd.date_range(start= '%d-%02d-%02d %02d:%02d:%02d' %(int(year),int(month), int(day), int(hour), int(minute), int(second)), periods=60, freq='10S')
else:
year=files[11:15]
month=files[16:18]
day= files[19:21]
hour=files[22:24]
minute=files[24:26]
second=files[26:28]
tindex=pd.date_range(start= '%d-%02d-%02d %02d:%02d:%02d' %(int(year), int(month), int(day), int(hour), int(minute), int(second)), periods=60, freq='10S')
Try this (based on the 2nd last '-', no need of if-else case):
filesall = ['AM_B0_D0.0_2016-04-01T010000.flac.h5',
'AM_B0_D3.7_2016-04-13T215000.flac.h5',
'AM_B0_D10.3_2017-03-17T110000.flac.h5',
'AM_B0_D0.7_2016-10-21T104000.flac.h5',
'AM_B0_D4.4_2016-08-05T151000.flac.h5',
'AM_B0_D0.0_2016-04-01T010000.flac.h5',
'AM_B0_D3.7_2016-04-13T215000.flac.h5',
'AM_B0_D10.3_2017-03-17T110000.flac.h5',
'AM_B0_D0.7_2016-10-21T104000.flac.h5',
'AM_B0_D4.4_2016-08-05T151000.flac.h5']
def find_second_last(text, pattern):
return text.rfind(pattern, 0, text.rfind(pattern))
for files in filesall:
start = find_second_last(files,'-') - 4 # from yyyy- part
timepart = (files[start:start+17]).replace("T"," ")
#insert 2 ':'s
timepart = timepart[:13] + ':' + timepart[13:15] + ':' +timepart[15:]
# print(timepart)
tindex=pd.date_range(start= timepart, periods=60, freq='10S')
In Place of using file[11] as hard coded go for last or 2nd last index of _ then use your code then you don't have to write 2 times same code. Or use regex to parse the string.
I have some files with some lines in Linux like:
2013/08/16,name1,,5000,8761,09:00,09:30
2013/08/16,name1,,5000,9763,10:00,10:30
2013/08/16,name1,,5000,8866,11:00,11:30
2013/08/16,name1,,5000,5768,12:00,12:30
2013/08/16,name1,,5000,11764,13:00,13:30
2013/08/16,name2,,5000,2765,14:00,14:30
2013/08/16,name2,,5000,4765,15:00,15:30
2013/08/16,name2,,5000,6765,16:00,16:30
2013/08/16,name2,,5000,12765,17:00,17:30
2013/08/16,name2,,5000,25665,18:00,18:30
2013/08/16,name2,,5000,45765,09:00,10:30
2013/08/17,name1,,5000,33765,10:00,11:30
2013/08/17,name1,,5000,1765,11:00,12:30
2013/08/17,name1,,5000,34765,12:00,13:30
2013/08/17,name1,,5000,12765,13:00,14:30
2013/08/17,name2,,5000,1765,14:00,15:30
2013/08/17,name2,,5000,3765,15:00,16:30
2013/08/17,name2,,5000,7765,16:00,17:30
My column separator is "," and in the third column (currently ,,), I need the entry number within the same day. For example, with date
2013/08/16 I have 11 lines and with date 2013/08/17 7 lines, so I need add the numbers for example:
2013/08/16,name1,1,5000,8761,09:00,09:30
2013/08/16,name1,2,5000,9763,10:00,10:30
2013/08/16,name1,3,5000,8866,11:00,11:30
2013/08/16,name1,4,5000,5768,12:00,12:30
2013/08/16,name1,5,5000,11764,13:00,13:30
2013/08/16,name2,6,5000,2765,14:00,14:30
2013/08/16,name2,7,5000,4765,15:00,15:30
2013/08/16,name2,8,5000,6765,16:00,16:30
2013/08/16,name2,9,5000,12765,17:00,17:30
2013/08/16,name2,10,5000,25665,18:00,18:30
2013/08/16,name2,11,5000,45765,09:00,10:30
2013/08/17,name1,1,5000,33765,10:00,11:30
2013/08/17,name1,2,5000,1765,11:00,12:30
2013/08/17,name1,3,5000,34765,12:00,13:30
2013/08/17,name1,4,5000,12765,13:00,14:30
2013/08/17,name2,5,5000,1765,14:00,15:30
2013/08/17,name2,6,5000,3765,15:00,16:30
2013/08/17,name2,7,5000,7765,16:00,17:30
I need do it in bash. How can I do it?
This one's good too:
awk -F, 'sub(/,,/, ","++a[$1]",")1' file
Output:
2013/08/16,name1,1,5000,8761,09:00,09:30
2013/08/16,name1,2,5000,9763,10:00,10:30
2013/08/16,name1,3,5000,8866,11:00,11:30
2013/08/16,name1,4,5000,5768,12:00,12:30
2013/08/16,name1,5,5000,11764,13:00,13:30
2013/08/16,name2,6,5000,2765,14:00,14:30
2013/08/16,name2,7,5000,4765,15:00,15:30
2013/08/16,name2,8,5000,6765,16:00,16:30
2013/08/16,name2,9,5000,12765,17:00,17:30
2013/08/16,name2,10,5000,25665,18:00,18:30
2013/08/16,name2,11,5000,45765,09:00,10:30
2013/08/17,name1,1,5000,33765,10:00,11:30
2013/08/17,name1,2,5000,1765,11:00,12:30
2013/08/17,name1,3,5000,34765,12:00,13:30
2013/08/17,name1,4,5000,12765,13:00,14:30
2013/08/17,name2,5,5000,1765,14:00,15:30
2013/08/17,name2,6,5000,3765,15:00,16:30
2013/08/17,name2,7,5000,7765,16:00,17:30