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Convert a matrix from string to integer

I'm trying to change a matrix of numbers from string to integer but it just doesn't work.
for element in list:
for i in element:
i = int(i)
What am I doing wrong?
Edit:
This is the whole code:
import numpy as np
t_list = []
t_list = np.array(t_list)
list_rains_per_months = [['63', '65', '50', '77', '66', '69'],
['65', '65', '67', '50', '54', '58'],
['77', '73', '80', '83', '89', '100'],
['90', '85', '90', '90', '84', '90'],
['129', '113', '120', '135', '117', '130'],
['99', '116', '114', '111', '119', '100'],
['105', '98', '112', '113', '102', '100'],
['131', '120', '111', '141', '130', '126'],
['85', '101', '88', '89', '94', '91'],
['122', '103', '119', '98', '101', '107'],
['121', '101', '104', '121', '115', '104'],
['67', '44', '58', '61', '64', '58']]
for element in t_list:
for i in element:
i = int(i)
I apologize for any mistakes, I'm new to python

What you're doing wrong, is that you're not changing the list or any list element: the 'i' inside the loop starts by pointing to each element of the list, then you make it point to something else, but that doesn't affect your list (also, avoid using 'list' as an identifier, it's an existing type, that's asking for trouble).
One way to do it is with list comprehensions. Assuming your matrix is a list of (inner) lists, for example:
a_list = [["3", "56", "78"], ["2", "39", "60"], ["87", "9", "71"]]
then two nested list comprehensions should do the trick:
a_list = [[int(i) for i in inner_list] for inner_list in a_list]
This builds a new list, formed by going over your initial list, applying the change you want, and saving it a another (or the same) list.

In numpy you do it that way.
import numpy as np
list_rains_per_months = [['63', '65', '50', '77', '66', '69'],
['65', '65', '67', '50', '54', '58'],
['77', '73', '80', '83', '89', '100'],
['90', '85', '90', '90', '84', '90'],
['129', '113', '120', '135', '117', '130'],
['99', '116', '114', '111', '119', '100'],
['105', '98', '112', '113', '102', '100'],
['131', '120', '111', '141', '130', '126'],
['85', '101', '88', '89', '94', '91'],
['122', '103', '119', '98', '101', '107'],
['121', '101', '104', '121', '115', '104'],
['67', '44', '58', '61', '64', '58']]
list_rains_per_months = np.array(list_rains_per_months)
myfunc = np.vectorize(lambda x: int(x))
list_rains_per_months = myfunc(list_rains_per_months)
print(list_rains_per_months)
Output
[[ 63 65 50 77 66 69]
[ 65 65 67 50 54 58]
[ 77 73 80 83 89 100]
[ 90 85 90 90 84 90]
[129 113 120 135 117 130]
[ 99 116 114 111 119 100]
[105 98 112 113 102 100]
[131 120 111 141 130 126]
[ 85 101 88 89 94 91]
[122 103 119 98 101 107]
[121 101 104 121 115 104]
[ 67 44 58 61 64 58]]

You could use enumerate object in loops:
list = [["12", "10", "0"],
["0", "33", "60"]]
for h, i in enumerate(list):
for j, k in enumerate(i):
list[h][j] = int(k)
print(list)

Could also just map each row's values to int:
for row in list_rains_per_months:
row[:] = map(int, row)
Note that I assign to row[:], i.e., into the row and thus into the matrix. If I assigned to row instead, I'd have the same problem as you with your i: I'd only assign to the variable, not into the row/matrix.

How would I slice a value of a key in a dictionary

hello I'm new to coding and I have to Define a function named filterByMonth with two parameters. The first argument passed to the function should be a list of dictionaries (the data), the second a number (representing a month, 1 through 12). This function must return a list of all the dictionaries from the input list whose 'issued' date is in the indicated month. 'slice' a string to more easily extract the relevant portion of a date from a string. Sample function call: filterByMonth(data,9)
With a list of dictionaries I need to slice the month which is a part of the value for the key 'issued' which is the third key in the dictionaries.
data = [
{'apno': 'FEND19-9487084', 'aptype': 'FENDRIVE', 'issued': '2019-09-05T00:00:00.000', 'stname': '129 PARKSIDE CT', 'city': 'BUFFALO', 'state': 'NY', 'zip': '14214', 'applicant': 'PETER CICERO', 'fees': '150', 'value': '3500', 'plans': '0', 'sbl': '0795300004001000', 'landuse': '411', 'inspector': 'ANDREW BLERSCH', 'expdate': '2020-03-05T00:00:00.000', 'descofwork': 'REMOVE EXISTING DRIVEWAY AND REPLACE IN KIND WITH CONCRETE TO CODE ON SOUTH / RIGHT SIDE OF STRUCTURE TO CODE - SURVEY SCANNED', 'location_1': {'latitude': '42.95116080935555', 'longitude': '-78.83406536395538', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}, 'latitude': '42.95116080935555', 'longitude': '-78.83406536395538', 'council_district': 'UNIVERSITY', 'police_district': 'District D', 'census': '45', 'census_block_group': '1', 'census_block': '1010', 'neighborhood': 'UNKNOWN', ':#computed_region_fk4y_hpmh': '5', ':#computed_region_eziv_p4ck': '64', ':#computed_region_tmcg_v66k': '8', ':#computed_region_kwzn_pe6v': '18', ':#computed_region_uh5x_q5mi': '88', ':#computed_region_dwzh_dtk5': '1573', ':#computed_region_b3rm_3c8a': '37', ':#computed_region_xbxg_7ifr': '24', ':#computed_region_urdz_b6n8': '7'},
{'apno': 'SWIM19-9485898', 'aptype': 'SWIM POOL', 'issued': '2019-08-19T00:00:00.000', 'stname': '341 NORWALK', 'city': 'BUFFALO', 'state': 'NY', 'zip': '14216', 'applicant': 'MS CHRISTINE SALAMONE', 'fees': '75', 'value': '500', 'plans': '0', 'sbl': '0785000006033000', 'landuse': '210', 'inspector': 'ANDREW BLERSCH', 'expdate': '2020-02-19T00:00:00.000', 'descofwork': 'INSTALLATION OF AN ABOVE GROUND SWIMMING POOL SUBMITTED THROUGH IDT', 'location_1': {'latitude': '42.95333872723409', 'longitude': '-78.85429233887896', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}, 'latitude': '42.95333872723409', 'longitude': '-78.85429233887896', 'council_district': 'DELAWARE', 'police_district': 'District D', 'census': '49', 'census_block_group': '1', 'census_block': '1000', 'neighborhood': 'UNKNOWN', ':#computed_region_fk4y_hpmh': '5', ':#computed_region_eziv_p4ck': '51', ':#computed_region_tmcg_v66k': '7', ':#computed_region_kwzn_pe6v': '5', ':#computed_region_uh5x_q5mi': '190', ':#computed_region_dwzh_dtk5': '944', ':#computed_region_b3rm_3c8a': '28', ':#computed_region_xbxg_7ifr': '25', ':#computed_region_urdz_b6n8': '2'},
]
def filterByMonth(dta,month):
result=[]
for x in dta:
for y in x:
for x['issued'] in y
if month== x[6]:
result.append(x)
return result
print(filterByMonth(data,9))

You could do this more easily with the datetime module like so
from datetime import datetime
data = [
{'apno': 'FEND19-9487084', 'aptype': 'FENDRIVE', 'issued': '2019-09-05T00:00:00.000', 'stname': '129 PARKSIDE CT', 'city': 'BUFFALO', 'state': 'NY', 'zip': '14214', 'applicant': 'PETER CICERO', 'fees': '150', 'value': '3500', 'plans': '0', 'sbl': '0795300004001000', 'landuse': '411', 'inspector': 'ANDREW BLERSCH', 'expdate': '2020-03-05T00:00:00.000', 'descofwork': 'REMOVE EXISTING DRIVEWAY AND REPLACE IN KIND WITH CONCRETE TO CODE ON SOUTH / RIGHT SIDE OF STRUCTURE TO CODE - SURVEY SCANNED', 'location_1': {'latitude': '42.95116080935555', 'longitude': '-78.83406536395538', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}, 'latitude': '42.95116080935555', 'longitude': '-78.83406536395538', 'council_district': 'UNIVERSITY', 'police_district': 'District D', 'census': '45', 'census_block_group': '1', 'census_block': '1010', 'neighborhood': 'UNKNOWN', ':#computed_region_fk4y_hpmh': '5', ':#computed_region_eziv_p4ck': '64', ':#computed_region_tmcg_v66k': '8', ':#computed_region_kwzn_pe6v': '18', ':#computed_region_uh5x_q5mi': '88', ':#computed_region_dwzh_dtk5': '1573', ':#computed_region_b3rm_3c8a': '37', ':#computed_region_xbxg_7ifr': '24', ':#computed_region_urdz_b6n8': '7'},
{'apno': 'SWIM19-9485898', 'aptype': 'SWIM POOL', 'issued': '2019-08-19T00:00:00.000', 'stname': '341 NORWALK', 'city': 'BUFFALO', 'state': 'NY', 'zip': '14216', 'applicant': 'MS CHRISTINE SALAMONE', 'fees': '75', 'value': '500', 'plans': '0', 'sbl': '0785000006033000', 'landuse': '210', 'inspector': 'ANDREW BLERSCH', 'expdate': '2020-02-19T00:00:00.000', 'descofwork': 'INSTALLATION OF AN ABOVE GROUND SWIMMING POOL SUBMITTED THROUGH IDT', 'location_1': {'latitude': '42.95333872723409', 'longitude': '-78.85429233887896', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}, 'latitude': '42.95333872723409', 'longitude': '-78.85429233887896', 'council_district': 'DELAWARE', 'police_district': 'District D', 'census': '49', 'census_block_group': '1', 'census_block': '1000', 'neighborhood': 'UNKNOWN', ':#computed_region_fk4y_hpmh': '5', ':#computed_region_eziv_p4ck': '51', ':#computed_region_tmcg_v66k': '7', ':#computed_region_kwzn_pe6v': '5', ':#computed_region_uh5x_q5mi': '190', ':#computed_region_dwzh_dtk5': '944', ':#computed_region_b3rm_3c8a': '28', ':#computed_region_xbxg_7ifr': '25', ':#computed_region_urdz_b6n8': '2'}
]
def filterByMonth(data, month):
result = []
for item in data:
datestring = item['issued']
dt = datetime.strptime(datestring, '%Y-%m-%dT%H:%M:%S.%f')
if dt.month == month:
result.append(item)
return result
print(filterByMonth(data, 9))
and a more pythonic way would be this
def filterByMonth(data, month):
return [item for item in data if datetime.strptime(item['issued'], '%Y-%m-%dT%H:%M:%S.%f').month == month]

Print nested dictionary in python and export all on a csv file

I have a dictionary like this:
{'https://github.com/project1': {'Batchfile': '91', 'Gradle': '110', 'INI': '25', 'Java': '1879', 'Markdown': '393', 'QMake': '52', 'Shell': '161', 'Text': '202', 'XML': '943'}}
{'https://github.com/project2': {'Batchfile': '91', 'Gradle': '123', 'INI': '25', 'Java': '1305', 'Markdown': '121', 'QMake': '52', 'Shell': '161', 'XML': '234'}}
{'https://github.com/project3': {'Batchfile': '91', 'Gradle': '360', 'INI': '27', 'Java': '805', 'Markdown': '27', 'QMake': '156', 'Shell': '161', 'XML': '380'}}
It is a structured in this way:
{'url': {'lang1': 'locs', 'lang2': 'locs', ...}}
{'url2': {'lang6': 'locs', 'lang5': 'locs', ...}}
where lang stay for languages and locs stay for line of codes (related to the previous language).
What i want to do is print this dictionary in a pretty way,so i can see the results before the export.
After that i want to export the dictionary into a csv file to make other operation. The problem is the languages are not sorted. That is what i mean:
{'https://github.com/Project4': {'HTML': '29', 'Java': '229', 'Markdown': '101', 'Maven POM': '88', 'XML': '62'}}
{'https://github.com/Project5': {'Batchfile': '85', 'Gradle': '84', 'INI': '22', 'Java': '2422', 'Markdown': '25', 'Prolog': '25', 'Shell': '173', 'XML': '3243', 'YAML': '43'}}
Any idea?

You could use pandas:
import pandas as pd
t = [{'https://github.com/project1': {'Batchfile': '91', 'Gradle': '110', 'INI': '25', 'Java': '1879', 'Markdown': '393', 'QMake': '52', 'Shell': '161', 'Text': '202', 'XML': '943'}},
{'https://github.com/project2': {'Batchfile': '91', 'Gradle': '123', 'INI': '25', 'Java': '1305', 'Markdown': '121', 'QMake': '52', 'Shell': '161', 'XML': '234'}},
{'https://github.com/project3': {'Batchfile': '91', 'Gradle': '360', 'INI': '27', 'Java': '805', 'Markdown': '27', 'QMake': '156', 'Shell': '161', 'XML': '380'}}]
columns = set([lang for x in t for l in x.values() for lang in l])
index = [p for x in t for p in x.keys()]
rows = [l for x in t for l in x.values() ]
df = pd.DataFrame(rows, columns=columns, index=index).fillna('N/A')
df.to_csv('projects.csv')
Which gives:
>>> df
Gradle INI Markdown ... Batchfile Java QMake
https://github.com/project1 110 25 393 ... 91 1879 52
https://github.com/project2 123 25 121 ... 91 1305 52
https://github.com/project3 360 27 27 ... 91 805 156
[3 rows x 9 columns]
And in the csv:

Writing columns from a text file to a list of dicts in python

I have a text file with four columns:
time serial domain server
the contents of the text file are as follows:
15 14 google.com 8.8.8.8
19 45 google.com 8.8.4.4
98 76 google.com 208.67.222.222
20 23 intuit.com 8.8.8.8
45 89 intuit.com 8.8.4.4
43 21 intuit.com 208.67.222.222
78 14 google.com 8.8.8.8
92 76 google.com 8.8.4.4
64 54 google.com 208.67.222.222
91 18 intuit.com 8.8.8.8
93 74 intuit.com 8.8.4.4
65 59 intuit.com 208.67.222.222
What would be the best way to read this file and create a list of dict as follows:
[{"server":"8.8.8.8",
"domains":[{"google.com":[{"time":15, "serial":14}, {"time":78, "serial":14}]},
{"intuit.com":[{"time":20, "serial":23}, {"time":91, "serial":18}]}
]
},
{"server":"8.8.4.4",
"domains":[{"google.com":[{"time":19, "serial":45}, {"time":92, "serial":76}]},
{"intuit.com":[{"time":45, "serial":89}, {"time":93, "serial":74}]}
]
},
{"server":"206.67.222.222",
"domains":[{"google.com":[{"time":98, "serial":76}, {"time":64, "serial":54}]},
{"intuit.com":[{"time":43, "serial":21}, {"time":65, "serial":59}]}
]
}]
The order of the rows could change but the columns always remain the same.

Perhaps not the best way, but a way that is beneficial in some ways:
servers = {}
file_path = './test.file'
from pprint import pprint
with open(file_path,'rb') as f:
for line in f:
_time, serial, domain, ip = line.split()
current_domains = servers.get(ip, {})
times = current_domains.get(domain, [])
times.append({"time": _time, "serial": serial})
current_domains[domain] = times
servers[ip] = current_domains
pprint(servers)
pprint([{"server": ip, "domains": [{domain: _time} for domain, _time in domains.items()]} for ip, domains in servers.items()])
Output:
{'208.67.222.222': {'google.com': [{'serial': '76', 'time': '98'},
{'serial': '54', 'time': '64'}],
'intuit.com': [{'serial': '21', 'time': '43'},
{'serial': '59', 'time': '65'}]},
'8.8.4.4': {'google.com': [{'serial': '45', 'time': '19'},
{'serial': '76', 'time': '92'}],
'intuit.com': [{'serial': '89', 'time': '45'},
{'serial': '74', 'time': '93'}]},
'8.8.8.8': {'google.com': [{'serial': '14', 'time': '15'},
{'serial': '14', 'time': '78'}],
'intuit.com': [{'serial': '23', 'time': '20'},
{'serial': '18', 'time': '91'}]}}
[{'domains': [{'intuit.com': [{'serial': '21', 'time': '43'},
{'serial': '59', 'time': '65'}]},
{'google.com': [{'serial': '76', 'time': '98'},
{'serial': '54', 'time': '64'}]}],
'server': '208.67.222.222'},
{'domains': [{'intuit.com': [{'serial': '23', 'time': '20'},
{'serial': '18', 'time': '91'}]},
{'google.com': [{'serial': '14', 'time': '15'},
{'serial': '14', 'time': '78'}]}],
'server': '8.8.8.8'},
{'domains': [{'intuit.com': [{'serial': '89', 'time': '45'},
{'serial': '74', 'time': '93'}]},
{'google.com': [{'serial': '45', 'time': '19'},
{'serial': '76', 'time': '92'}]}],
'server': '8.8.4.4'}]
The benefits being, easily keying into the dictionaries, only looping over once to create the insertions.
The only downside to this is that it is not in the same format, and has to be looped over 1 more time to do so, this however still beats having to iterate over the list for every line being inserted.

sorting by dictionary value in array python

Okay so I've been working on processing some annotated text output. What I have so far is a dictionary with annotation as key and relations an array of elements:
'Adenotonsillectomy': ['0', '18', '1869', '1716'],
'OSAS': ['57', '61'],
'apnea': ['41', '46'],
'can': ['94', '97', '1796', '1746'],
'deleterious': ['103', '114'],
'effects': ['122', '129', '1806', '1752'],
'for': ['19', '22'],
'gain': ['82', '86', '1776', '1734'],
'have': ['98', '102', ['1776 1786 1796 1806 1816'], '1702'],
'health': ['115', '121'],
'lead': ['67', '71', ['1869 1879 1889'], '1695'],
'leading': ['135', '142', ['1842 1852'], '1709'],
'may': ['63', '66', '1879', '1722'],
'obesity': ['146', '153'],
'obstructive': ['23', '34'],
'sleep': ['35', '40'],
'syndrome': ['47', '55'],
'to': ['143', '145', '1852', '1770'],
'weight': ['75', '81'],
'when': ['130', '134', '1842', '1758'],
'which': ['88', '93', '1786', '1740']}
What I want to do is sort this by the first element in the array and reorder the dict as:
'Adenotonsillectomy': ['0', '18', '1869', '1716']
'for': ['19', '22'],
'obstructive': ['23', '34'],
'sleep': ['35', '40'],
'apnea': ['41', '46'],
etc...
right now I've tried to use operator to sort by value:
sorted(dependency_dict.items(), key=lambda x: x[1][0])
However the output I'm getting is still incorrect:
[('Adenotonsillectomy', ['0', '18', '1869', '1716']),
('deleterious', ['103', '114']),
('health', ['115', '121']),
('effects', ['122', '129', '1806', '1752']),
('when', ['130', '134', '1842', '1758']),
('leading', ['135', '142', ['1842 1852'], '1709']),
('to', ['143', '145', '1852', '1770']),
('obesity', ['146', '153']),
('for', ['19', '22']),
('obstructive', ['23', '34']),
('sleep', ['35', '40']),
('apnea', ['41', '46']),
('syndrome', ['47', '55']),
('OSAS', ['57', '61']),
('may', ['63', '66', '1879', '1722']),
('lead', ['67', '71', ['1869 1879 1889'], '1695']),
('weight', ['75', '81']),
('gain', ['82', '86', '1776', '1734']),
('which', ['88', '93', '1786', '1740']),
('can', ['94', '97', '1796', '1746']),
('have', ['98', '102', ['1776 1786 1796 1806 1816'], '1702'])]
I'm not sure whats going wrong. Any help is appreciated.

The entries are sorted in alphabetical order. If you want to sort them on integer value, convert the value to int first:
sorted(dependency_dict.items(), key=lambda x: int(x[1][0]))