Here is the list
['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', '00', 'STOP/HOLD ADD', '5', '', '00', 'TOWER INQ', 'T', '', '00', 'ACCT FIELD MNT', '2', '', '00', 'COMB STMT MAINT', 'C', '', '00', 'MONETARY IM80', 'W', '', '00', 'MONETARY-IM201', 'D', '', '00', 'OCF INQ', 'G', '', '00', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', '', '00', 'NAME/ADDR CHG', '4', '', '00', 'MEMO POST', 'Z', '', '00', 'FLOOR LIMITS', '0']
I would like to remove '' and '00' from the list
result should be like this
['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', 'STOP/HOLD ADD', '5', 'TOWER INQ', 'T', 'ACCT FIELD MNT', '2', 'COMB STMT MAINT', 'C', 'MONETARY IM80', 'W', 'MONETARY-IM201', 'D', 'OCF INQ', 'G', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', 'NAME/ADDR CHG', '4', 'MEMO POST', 'Z', 'FLOOR LIMITS', '0']
I tried this
apa= [aa for aa in apa if aa != "''" or aa != "00"]
getting same result
Here's how I would do it:
for i in list:
if i = "00":
del list[i]
You can also use:
list.remove('00');
lst=['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', '00',
'STOP/HOLD ADD', '5', '', '00', 'TOWER INQ', 'T', '', '00',
'ACCT FIELD MNT', '2', '', '00', 'COMB STMT MAINT', 'C', '',
'00', 'MONETARY IM80', 'W', '', '00', 'MONETARY-IM201', 'D',
'', '00', 'OCF INQ', 'G', '', '00', 'ACCESS ALL FUNC', 'NO',
'RATE INQ', 'K', '', '00', 'NAME/ADDR CHG', '4', '', '00',
'MEMO POST', 'Z', '', '00', 'FLOOR LIMITS', '0']
print [x for x in lst if x != '00' and x != '']
#Output
['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', 'STOP/HOLD ADD',
'5', 'TOWER INQ', 'T', 'ACCT FIELD MNT', '2', 'COMB STMT MAINT',
'C', 'MONETARY IM80', 'W', 'MONETARY-IM201', 'D', 'OCF INQ', 'G',
'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', 'NAME/ADDR CHG', '4',
'MEMO POST', 'Z', 'FLOOR LIMITS', '0']
res=['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', '00', 'STOP/HOLD ADD', '5', '', '00', 'TOWER INQ', 'T', '', '00', 'ACCT FIELD MNT', '2', '', '00', 'COMB STMT MAINT', 'C', '', '00', 'MONETARY IM80', 'W', '', '00', 'MONETARY-IM201', 'D', '', '00', 'OCF INQ', 'G', '', '00', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', '', '00', 'NAME/ADDR CHG', '4', '', '00', 'MEMO POST', 'Z', '', '00', 'FLOOR LIMITS', '0']
res=[x for x in res if x not in ('00','')]
print res
['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', 'STOP/HOLD ADD', '5', 'TOWER INQ', 'T', 'ACCT FIELD MNT', '2', 'COMB STMT MAINT', 'C', 'MONETARY IM80', 'W', 'MONETARY-IM201', 'D', 'OCF INQ', 'G', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', 'NAME/ADDR CHG', '4', 'MEMO POST', 'Z', 'FLOOR LIMITS', '0']
Use while loop
list1 = ['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', '00', 'STOP/HOLD ADD', '5', '', '00', 'TOWER INQ', 'T', '', '00', 'ACCT FIELD MNT', '2', '', '00', 'COMB STMT MAINT', 'C', '', '00', 'MONETARY IM80', 'W', '', '00', 'MONETARY-IM201', 'D', '', '00', 'OCF INQ', 'G', '', '00', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', '', '00', 'NAME/ADDR CHG', '4', '', '00', 'MEMO POST', 'Z', '', '00', 'FLOOR LIMITS', '0']
while '00' in list1: list1.remove('00')
print(list1)
The output will be
['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', 'STOP/HOLD ADD', '5', '', 'TOWER INQ', 'T', '', 'ACCT FIELD MNT', '2', '', 'COMB STMT MAINT', 'C', '', 'MONETARY IM80', 'W', '', 'MONETARY-IM201', 'D', '', 'OCF INQ', 'G', '', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', '', 'NAME/ADDR CHG', '4', '', 'MEMO POST', 'Z', '', 'FLOOR LIMITS', '0']
With all the '00' terms removed
Single liner:
filter(lambda a: a!='' and a!='00', ['DEFAULT SECURITY', 'YES', 'ACCT INQ', '3', '', '00', 'STOP/HOLD ADD', '5', '', '00', 'TOWER INQ', 'T', '', '00', 'ACCT FIELD MNT', '2', '', '00', 'COMB STMT MAINT', 'C', '', '00', 'MONETARY IM80', 'W', '', '00', 'MONETARY-IM201', 'D', '', '00', 'OCF INQ', 'G', '', '00', 'ACCESS ALL FUNC', 'NO', 'RATE INQ', 'K', '', '00', 'NAME/ADDR CHG', '4', '', '00', 'MEMO POST', 'Z', '', '00', 'FLOOR LIMITS', '0'])
See https://stackoverflow.com/a/1157160/761963
Related
i have alot of this line
('235753', 'BayEnesYT', '$2y$12$laiU7F7HWJoXuryMTmgb6uKDfiOcxqD/R6Mxjg.KVNn2TK/Ra2Vwq', 'BNnuyZNL', 'zb6WPCvWYDwQmwZJQI7sypkc6oqVjZpSvnlg8gYYztJm6JYmJh', 'm.enesberber2009#gmail.com', '0', '0', '', '', '', '2', '', '0', '', '1560100802', '1560689379', '1560102670', '0', '', '0', '', '', '', '', '', 'all', '', '1', '0', '0', '0', '1', '0', '1', '0', '1', '0', 'linear', '1', '1', '1', '1', '1', '1', '0', '0', '0', '', '', '', '0', '0', '', '', '0', '0', '0', '0', '', '', '', '0', '0', '0', 0x51D69F63, 0x5567522E, '', '1894', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '', '0', '0.00', '1', '0', '0', '0', '', '1', '1', '2', '0', '0', '0', '0', '[]', '1', null, null, null, '1', '', '', '0', '0', '0', '', '', '', '', '', '0', '', '', '', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '', '0', '', '0', '0', '0', '', '', '', '', '', '', '', '', '', '', '0', '', 'mybb_bcrypt', '0', '');
and i need to remove text before the 5th comma and after the 6th comma
so the result would be m.enesberber2009#gmail.com only
i want to use regex replacement method with notepad++
Replace this expression
^\(?(?:'[^']*',\s*){5}('[^']+').+
with the first captured group, see a demo on regex101.com.
I am trying to filter a csv file from a column contains many minus numbers.
I found a source code on the website, which worked on small lists, but it does not work on data from a csv file.
here is an example of the data I have.
691
609
627
211
-226
921
829
1
972
173
181
-66
-96
573
and here is the code I am using
import pandas as pd
from pandas import DataFrame
import numpy as np
import re
import csv
from re import findall
ful = pd.read_csv(r'/home/aziz/Desktop/testminplus.csv')
ful1 = ful[0:]
#full = ['1', '-3']
full = ful1
regex = re.compile(r'(-\d*)')
# use only one of the following lines, whichever you prefer
#filtered = filter(lambda i: not regex.search(i), full)
filtered = [i for i in full if not regex.search(i)]
print(filtered)
The results are as the following:
[' ', ' ', ' ', ' ', '8', '2', '3', '\n', '0', ' ', ' ', ' ', ' ', '6', '0', '9', '\n', '1', ' ', ' ', ' ', ' ', '6', '2', '7', '\n', '2', ' ', ' ', ' ', ' ', '2', '1', '1', '\n', '3', ' ', ' ', ' ', '2', '2', '6', '\n', '4', ' ', ' ', ' ', ' ', '9', '2', '1', '\n', '5', ' ', ' ', ' ', ' ', '8', '2', '9', '\n', '6', ' ', ' ', ' ', ' ', ' ', ' ', '1', '\n', '7', ' ', ' ', ' ', ' ', '9', '7', '2', '\n', '8', ' ', ' ', ' ', ' ', '1', '7', '3', '\n', '9', ' ', ' ', ' ', ' ', '1', '8', '1', '\n', '1', '0', ' ', ' ', ' ', '6', '6', '\n', '1', '1', ' ', ' ', ' ', '9', '6', '\n', '1', '2', ' ', ' ', ' ', '5', '7', '3', '\n', '1', '3', ' ', ' ', ' ', '8', '9', '5', '\n', '1', '4', ' ', ' ', ' ', '1', '1', '8', '\n', '1', '5', ' ', ' ', ' ', ' ', '7', '\n', '1', '6', ' ', ' ', '6', '9', '8', '\n', '1', '7', ' ', ' ', ' ', '3', '5', '1', '\n', '1', '8', ' ', ' ', ' ', '9', '3', '3', '\n', '1', '9', ' ', ' ', ' ', '9', '3', '2', '\n', '2', '0', ' ', ' ', ' ', '7', '3', '2', '\n', '2', '1', ' ', ' ', '6', '6', '0', '\n', '2', '2', ' ', ' ', '4', '6', '5', '\n', '2', '3', ' ', ' ', ' ', '3', '4', '5', '\n', '2', '4', ' ', ' ', ' ', ' ', '1', '8', '\n', '2', '5', ' ', ' ', ' ', '1', '2', '0', '\n', '2', '6', ' ', ' ', '2', '7', '0', '\n', '2', '7', ' ', ' ', '2', '3', '3', '\n', '2', '8', ' ', ' ', '1', '5', '2', '\n', '2', '9', ' ', ' ', ' ', '1', '8', '6', '\n', '3', '0', ' ', ' ', '3', '9', '6', '\n', '3', '1', ' ', ' ', '5', '3', '5', '\n', '3', '2', ' ', ' ', ' ', '3', '5', '9', '\n', '3', '3', ' ', ' ', ' ', ' ', '1', '\n', '3', '4', ' ', ' ', '5', '3', '3', '\n', '3', '5', ' ', ' ', ' ', '8', '1', '2', '\n', '3', '6', ' ', ' ', ' ', '5', '4', '6']
The desired output is something like the following:
123
213
2
5
Any idea how to solve this problem?
If you've just got a file with one number per line (and not an actual CSV file with multiple fields which doesn't appear to be your case) then you can do:
with open('/home/aziz/Desktop/testminplus.csv') as fin:
# generator to yield each line as an integer
data = (int(line) for line in fin)
# list-comp to only include positive numbers...
positive = [n for n in data if n >= 0]
Pandas solution is probably an overkill here, but also works quite well
import pandas as pd
# read file
df = pd.read_csv("/home/aziz/Desktop/testminplus.csv",
header=None,
converters={0: int}) # spits an error if non-numbers are present
# filter positives
df = df[df[0]>=0]
# write back
df.to_csv("/home/aziz/Desktop/positives_only.csv",
header=False,
index=False)
I have two lists:
A: [ True True True False True False True ]
B: ['A', 'B', 'C', 'D', 'E', 'F', 'G']
I want to get only those values from list B where list A is True.
Desired output:
['A', 'B', 'C', 'E', 'G']
You can use itertools.compress(...):
import itertools
a = [ True, True, True, False, True, False, True ]
b = ['A', 'B', 'C', 'D', 'E', 'F', 'G']
ab = itertools.compress(b, a)
print(list(ba))
If you do not want to import itertools, simple list comprehension with zip built-in function would be enough.
conditions = [True, True, True, False, True, False, True]
objects = ['A', 'B', 'C', 'D', 'E', 'F', 'G']
result = [o for o, c in zip(objects, conditions) if c]
assert result == ['A', 'B', 'C', 'E', 'G']
Fairly simple problem to be posted as a question; here is the solution. Would appreciate if you could try it before asking here.
Code:
a = [True, True, True, False, True, False, True]
b = ['A', 'B', 'C', 'D', 'E', 'F', 'G']
res = []
for x in range(len(a)):
if a[x]==True:
res.append(b[x])
print res
Output:
['A', 'B', 'C', 'E', 'G']
I hope this works for python 2 as well; I have only 3 on this PC, but still:
a = [ True, True, True, False, True, False, True ]
b = ['A', 'B', 'C', 'D', 'E', 'F', 'G']
ab = []
for i, j in enumerate(a):
if j == True:
ab.append(b[i])
# in python 3 this was print(ab) :) I ported :)
print ab
I have a list that stores lists with 5 elements. I want to create 5 new lists that store elements of each indexes. I have the following code but it seems not smart way.
>>> stats
[['1', '0', '36', '36', '3'], ['10', '0', '41', '77', '5'], ['1', '0', '631', '631', '63'], ['1', '0', '98', '98', '9'], ['9', '0', '52', '81', '6'], ['2', '0', '111', '167', '13'], ['1', '0', '98', '98', '9'], ['1', '0', '92', '92', '9'], ['2', '0', '241', '287', '26'], ['1', '0', '210', '210', '21'], ['2', '0', '336', '358', '34'], ['2', '0', '49', '57', '5'], ['5', '0', '52', '148', '7'], ['2', '0', '46', '76', '6'], ['3', '0', '33', '50', '4'], ['7', '0', '47', '70', '6'], ['1', '0', '94', '94', '9'], ['1', '0', '65', '65', '6'], ['1', '0', '66', '66', '6'], ['1', '0', '429', '429', '42'], ['1', '0', '337', '337', '33'], ['12', '0', '49', '126', '6'], ['1', '0', '47', '47', '4'], ['1', '0', '63', '63', '6'], ['1', '0', '79', '79', '7'], ['2', '0', '96', '100', '9'], ['1', '0', '36', '36', '3'], ['1', '0', '69', '69', '6'], ['6', '0', '44', '67', '5'], ['3', '0', '269', '385', '31'], ['2', '0', '78', '115', '9'], ['2', '0', '49', '52', '5'], ['3', '0', '26', '134', '9'], ['2', '0', '255', '561', '40'], ['1', '0', '75', '75', '7'], ['1', '0', '59', '59', '5'], ['2', '0', '59', '64', '6'], ['1', '0', '86', '86', '8'], ['1', '0', '63', '63', '6'], ['2', '0', '79', '100', '8'], ['4', '0', '825', '888', '86'], ['1', '0', '82', '82', '8'], ['3', '0', '65', '94', '7'], ['1', '0', '88', '88', '8'], ['1', '0', '344', '344', '34'], ['1', '0', '286', '286', '28'], ['1', '0', '73', '73', '7'], ['3', '0', '42', '69', '5'], ['1', '0', '151', '151', '15'], ['1', '0', '286', '286', '28'], ['2', '0', '47', '59', '5'], ['9', '0', '15', '41', '2'], ['2', '0', '343', '355', '34'], ['1', '0', '305', '305', '30'], ['1', '0', '238', '238', '23'], ['2', '0', '974', '2101', '153'], ['2', '0', '138', '142', '14'], ['7', '0', '45', '70', '5'], ['1', '0', '39', '39', '3']]
>>>
>>> num_requests,num_failures,min_response_time,max_response_time,avg_response_time = [], [], [], [], []
>>>
>>> for l in stats:
... num_requests.append(l[0])
... num_failures.append(l[1])
... min_response_time.append(l[2])
... max_response_time.append(l[3])
... avg_response_time.append(l[4])
...
>>> num_requests
['1', '10', '1', '1', '9', '2', '1', '1', '2', '1', '2', '2', '5', '2', '3', '7', '1', '1', '1', '1', '1', '12', '1', '1', '1', '2', '1', '1', '6', '3', '2', '2', '3', '2', '1', '1', '2', '1', '1', '2', '4', '1', '3', '1', '1', '1', '1', '3', '1', '1', '2', '9', '2', '1', '1', '2', '2', '7', '1']
It could be stored in one list which stores 5 sublist.
Solution
Just use zip with *:
(num_requests, num_failures, min_response_time, max_response_time,
avg_response_time) = zip(*stats)
This gives you tuples. Convert to lists if you need lists:
(num_requests, num_failures, min_response_time, max_response_time,
avg_response_time) = (list(x) for x in zip(*stats))
Details
A shorter example:
>>> data = [[1, 2, 3], [10, 20, 30], [100, 200, 300]]
>>> a, b, c = zip(*data)
>>> a
(1, 10, 100)
>>> b
(2, 20, 200)
>>> c
(3, 30, 300)
This is equivalent to:
a, b, c = zip(data[0], data[1], data[2])
but works for any number of sublists.
The left side uses tuple unpacking. For example, this:
x, y, z = (10, 20, 30)
assigns 10 to x, 20 to y, and 30 to z.
Performance
Measure how fast it is.
Version with append:
%%timeit
num_requests,num_failures,min_response_time,max_response_time,avg_response_time = [], [], [], [], []
for l in stats:
num_requests.append(l[0])
num_failures.append(l[1])
min_response_time.append(l[2])
max_response_time.append(l[3])
avg_response_time.append(l[4])
10000 loops, best of 3: 51 µs per loop
Version with zip:
%%timeit
(num_requests, num_failures, min_response_time, max_response_time,
avg_response_time) = zip(*stats)
100000 loops, best of 3: 8.58 µs per loop
It is about five times faster.
It takes a bit longer when you convert the tuples to lists:
%%timeit
(num_requests, num_failures, min_response_time, max_response_time,
avg_response_time) = (list(x) for x in zip(*stats))
100000 loops, best of 3: 13.3 µs per loop
Still, about four times faster.
This is my current code:
predict_results = []
with open ("newTesting.predict") as inputfile:
for line in inputfile:
predict_results.append(line.strip())
print predict_results
first_list = []
with open ("newTesting") as inputfile:
for line in inputfile:
first_list.append(line.strip().split()[0])
print first_list
if predict_results [0] == first_list[0]:
print True
else:
print False
This is my current output:
['-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '1', '-1', '1', '-1', '1', '-1', '1', '-1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '1', '1', '-1', '-1', '-1', '-1', '-1', '1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '-1']
['1', '-1', '1', '-1', '-1', '-1', '-1', '-1', '-1', '1', '1', '-1', '1', '1', '1', '1', '-1', '1', '-1', '1', '1', '1', '1', '-1', '1', '-1', '1', '1', '-1', '-1', '1', '1', '-1', '1', '1', '-1', '1', '1', '1', '1', '-1', '-1', '1', '1', '1', '1', '1', '1', '1', '-1', '-1', '1', '1', '-1', '1', '-1', '1', '-1', '-1', '1', '1', '-1', '1', '1', '1', '-1', '-1', '-1', '1', '-1', '-1', '1', '1', '1', '-1', '1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '1', '1', '-1', '-1', '-1', '-1', '-1', '1', '1', '-1', '-1', '1', '-1', '1', '1', '1', '-1', '1', '-1', '-1', '-1', '1', '1', '-1', '1', '1', '-1', '-1', '-1', '-1', '-1', '1', '-1', '-1', '-1', '-1', '-1']
False
I can only check index [0] which is correct. How do I check all indexes in predict_results with first_list
Thanks
Hope this will help:
>>> from pandas import *
>>> L1 = [1,2,3]
>>> L2 = [2,2,3]
>>> S1 = Series(L1)
>>> S2 = Series(L2)
>>> RES = S1==S2
>>> RES
0 False
1 True
2 True
For your case:
>>> S1 = Series(predict_results)
>>> S2 = Series(first_list)
>>> RES = S1==S2
>>> RES[0] # check predict_results[0]==first_list[0]
>>> RES[1] # check predict_results[1]==first_list[1]
And you can use loop:
for x,y in zip(predict_results,first_list):
if(x==y):
print False
else:
print True