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eate a new 2D array with 2 random rows from array `A` | A[(np.random.choice(A.shape[0], 2, replace=False)), :] |
eate a new 2 dimensional array containing two random rows from array `A` | A[(np.random.randint(A.shape[0], size=2)), :] |
mbining rows in pandas by adding their value | df.groupby(df.index).sum() |
find all `owl:Class` tags by parsing xml with namespace | root.findall('{http://www.w3.org/2002/07/owl#}Class') |
generate a random string of length `x` containing lower cased ASCII letter | """""".join(random.choice(string.lowercase) for x in range(X)) |
dd a path `/path/to/2014_07_13_test` to system path | sys.path.append('/path/to/2014_07_13_test') |
d number `x` to nearest integer | int(round(x)) |
d number `h` to nearest integer | h = int(round(h)) |
d number 32.268907563 up to 3 decimal po | round(32.268907563, 3) |
d number `value` up to `significantDigit` decimal place | round(value, significantDigit) |
d number 1.0005 up to 3 decimal place | round(1.0005, 3) |
d number 2.0005 up to 3 decimal place | round(2.0005, 3) |
d number 3.0005 up to 3 decimal place | round(3.0005, 3) |
d number 4.0005 up to 3 decimal place | round(4.0005, 3) |
d number 8.005 up to 2 decimal place | round(8.005, 2) |
d number 7.005 up to 2 decimal place | round(7.005, 2) |
d number 6.005 up to 2 decimal place | round(6.005, 2) |
d number 1.005 up to 2 decimal place | round(1.005, 2) |
fill missing value in one column 'Cat1' with the value of another column 'Cat2' | df['Cat1'].fillna(df['Cat2']) |
vert the argument `date` with string formatting in logging | logging.info('date=%s', date) |
Log message of level 'info' with value of `date` in the message | logging.info('date={}'.format(date)) |
vert values in dictionary `d` into integer | {k: int(v) for k, v in d.items()} |
m elements at the same index of each list in list `lists` | map(sum, zip(*lists)) |
Convert a string `s` containing hex bytes to a hex string | s.decode('hex') |
vert a string `s` containing hex bytes to a hex string | binascii.a2b_hex(s) |
end data 'HTTP/1.0 200 OK\r\n\r\n' to socket `connection` | connection.send('HTTP/1.0 200 established\r\n\r\n') |
end data 'HTTP/1.0 200 OK\r\n\r\n' to socket `connection` | connection.send('HTTP/1.0 200 OK\r\n\r\n') |
et the value of cell `['x']['C']` equal to 10 in dataframe `df` | df['x']['C'] = 10 |
malize the dataframe `df` along the row | np.sqrt(np.square(df).sum(axis=1)) |
emove identical items from list `my_list` and sort it alphabetically | sorted(set(my_list)) |
find the index of the element with the maximum value from a list 'a'. | max(enumerate(a), key=lambda x: x[1])[0] |
eate a list where each element is a value of the key 'Name' for each dictionary `d` in the list `thisismylist` | [d['Name'] for d in thisismylist] |
eate a list of tuples with the values of keys 'Name' and 'Age' from each dictionary `d` in the list `thisismylist` | [(d['Name'], d['Age']) for d in thisismylist] |
grab one random item from a database `model` in django/postgresql | model.objects.all().order_by('?')[0] |
python script 'script2.py' from another python script, passing in 1 as an argume | os.system('script2.py 1') |
python regex for hyphenated words in `text` | re.findall('\\w+(?:-\\w+)+', text) |
eate variable key/value pairs with argparse | parser.add_argument('--conf', nargs=2, action='append') |
Get `3` unique items from a l | random.sample(list(range(1, 16)), 3) |
list `strings` in alphabetical order based on the letter after percent character `%` in each eleme | strings.sort(key=lambda str: re.sub('.*%(.).*', '\\1', str)) |
a list of strings `strings` based on regex match | strings.sort(key=lambda str: re.sub('.*%', '', str)) |
Create list `listy` containing 3 empty l | listy = [[] for i in range(3)] |
mpy float array `A` column by colum | A = np.array(sorted(A, key=tuple)) |
Get a list from two strings `12345` and `ab` with values as each character concatenated | [(x + y) for x in '12345' for y in 'ab'] |
m string Hello | ' Hello '.strip() |
m string `myString ` | myString.strip() |
Trimming a string Hello | ' Hello '.strip() |
Trimming a string Hello | ' Hello'.strip() |
Trimming a string Bob has a cat | 'Bob has a cat'.strip() |
Trimming a string Hello | ' Hello '.strip() |
Trimming a string `str` | str.strip() |
Trimming \n from string `myString` | myString.strip('\n') |
left trimming \n\r from string `myString` | myString.lstrip('\n\r') |
ght trimming \n\t from string `myString` | myString.rstrip('\n\t') |
Trimming a string Hello\n by space | ' Hello\n'.strip(' ') |
a list of tuples 'unsorted' based on two elements, second and third | sorted(unsorted, key=lambda element: (element[1], element[2])) |
decode string `content` to UTF8 code | print(content.decode('utf8')) |
find the index of the maximum value in the array `arr` where the boolean condition in array `cond` is true | np.ma.array(np.tile(arr, 2).reshape(2, 3), mask=~cond).argmax(axis=1) |
vert a dataframe `df`'s column `ID` into datetime, after removing the first and last 3 letter | pd.to_datetime(df.ID.str[1:-3]) |
ead CSV file 'my.csv' into a dataframe `df` with datatype of float for column 'my_column' considering character 'n/a' as NaN value | df = pd.read_csv('my.csv', dtype={'my_column': np.float64}, na_values=['n/a']) |
vert nan values to ‘n/a’ while reading rows from a csv `read_csv` with pand | df = pd.read_csv('my.csv', na_values=['n/a']) |
eate a list containing all cartesian products of elements in list `a` | list(itertools.product(*a)) |
emove uppercased characters in string `s` | re.sub('[^A-Z]', '', s) |
vert string '2011221' into a DateTime object using format '%Y%W%w' | datetime.strptime('2011221', '%Y%W%w') |
ead file 'myfile' using encoding 'iso88591' | codecs.open('myfile', 'r', 'iso-8859-1').read() |
eate a list containing elements from list `list` that are predicate to function `f` | [f(x) for x in list] |
egex matching 5digit substrings not enclosed with digits in `s` | re.findall('(?<!\\d)\\d{5}(?!\\d)', s) |
eate a list containing elements of list `a` if the sum of the element is greater than 10 | [item for item in a if sum(item) > 10] |
vert currency string `dollars` to decimal `cents_int` | cents_int = int(round(float(dollars.strip('$')) * 100)) |
emove letters from string `example_line` if the letter exist in list `bad_chars` | """""".join(dropwhile(lambda x: x in bad_chars, example_line[::-1]))[::-1] |
Creating an empty list `l` | l = [] |
Creating an empty list `l` | l = list() |
Creating an empty l | list() |
Creating an empty l | [] |
properly quit a program | sys.exit(0) |
dd string `` in `4th` position of a string `s` | s[:4] + '-' + s[4:] |
ppend 3 lists in one l | [[] for i in range(3)] |
alize a list of empty lists `a` of size 3 | a = [[] for i in range(3)] |
equest URL `url` using http header `{'referer': my_referer}` | requests.get(url, headers={'referer': my_referer}) |
et the y axis range to `0, 1000` in subplot using pylab | pylab.ylim([0, 1000]) |
vert a column of list in series `s` to dummie | pd.get_dummies(s.apply(pd.Series).stack()).sum(level=0) |
Finding the largest delta between two integers in a list in pytho | max(abs(x - y) for x, y in zip(values[1:], values[:-1])) |
vert a hex string `x` to string | y = str(int(x, 16)) |
heck if string `a` is an integer | a.isdigit() |
function to check if a string is a number | isdigit() |
heck if string `b` is a number | b.isdigit() |
pandas read commaseparated CSV file `s` and skip commented lines starting with '#' | pd.read_csv(StringIO(s), sep=',', comment='#') |
pandas: change all the values of a column 'Date' into int(str(x)[4:]) | df['Date'] = df['Date'].apply(lambda x: int(str(x)[-4:])) |
m a list of numbers `list_of_nums` | sum(list_of_nums) |
Get an item from a list of dictionary `lst` which has maximum value in the key `score` using lambda functio | max(lst, key=lambda x: x['score']) |
BeautifulSoup find all tags with attribute 'name' equal to 'description' | soup.findAll(attrs={'name': 'description'}) |
emove all spaces from a string converted from dictionary `{'a': 1, 'b': 'as df'}` | str({'a': 1, 'b': 'as df'}).replace(': ', ':').replace(', ', ',') |
vert dictionary `dict` into a string formatted objec | '{' + ','.join('{0!r}:{1!r}'.format(*x) for x in list(dct.items())) + '}' |
atenate items from list `parts` into a string starting from the second eleme | """""".join(parts[1:]) |
ert a character ',' into a string in front of '+' character in second part of the string | """,+""".join(c.rsplit('+', 1)) |
delete all rows in a numpy array `a` where any value in a row is zero `0` | a[np.all(a != 0, axis=1)] |
extract only alphabetic characters from a string `your string` | """ """.join(re.split('[^a-zA-Z]*', 'your string')) |
Extract only characters from a string as a l | re.split('[^a-zA-Z]*', 'your string') |
get the union set from list of lists `results_list` | results_union = set().union(*results_list) |
get the union of values in list of lists `result_list` | return list(set(itertools.chain(*result_list))) |
heck if a numpy array `a1` contains any element of another array `a2` | np.any(np.in1d(a1, a2)) |